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• Last updated on August 7, 2024
• By Viktor. A
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Customers constantly demand deeper and more meaningful relationships with their chosen brands. That’s why organizations use CRM software to better serve their customers.

This article compiles practical CRM case studies from some of the world’s biggest brands, highlighting vital lessons you can replicate in your business.

Before we proceed, let’s look at the meaning of customer relationship management (CRM)

There are two main definitions of a CRM:

1. It refers to a business’s principles and strategies to better engage and retain customers.

2. It is a software system that helps businesses manage client relationships, leads, contacts, and campaigns, allowing companies to automate processes and increase productivity.

Examples of CRM software for lead generation, contact management, and automation include:

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Best CRM Case Studies

If you’ve ever looked at brands like Apple, McDonald’s, Amazon, or even Zara, you may wonder how they run such conglomerates and still provide efficient customer service. Keep reading, then; you’re about to find out.

Scott Cook said to focus on the customer instead of the competition. Most of these brands have no superpower. They’ve only learned to focus on one thing—the customer.

When you’re obsessed with delighting your customers, you will devise creative ways of satisfying them.

1. Coca-Cola CRM

The Coca-Cola Company is one of the world’s oldest and most influential brands. With a presence in over 200 countries, Coca-Cola started as a carbonated soft drink business. Today, it is a conglomerate with over 200 product lines servicing billions of customers globally.

Logically speaking, their existence across several decades and their continued relevance and competitiveness say a lot about their customer service. That said, let’s examine their customer relationship management (CRM). 

Coca-Cola CRM Case Study:

Inspiring optimism and happiness are at the core of Coca-Cola’s CRM strategy. This is evident in their  marketing campaigns , billboards, brochures, commercials, store locations, and products. Coca-Cola uses several enterprise CRM platforms to manage its clients’ relationships and stores globally. They use Salesforce and SAP primarily for contact management. System Applications and Products (SAP) is a strategic enterprise management platform that is quite robust and feature-rich.

While they use SAP globally, they use Salesforce on some of their country divisions to manage their business flow, connectivity, and contact management.

We have billions of transactions a day on Salesforce. And everything is connected collaborative, and mobile.

– Ulrik Nehammer, Coca-Cola Germany, CEO.

2. Zara CRM

When you hear the word “Zara”, what comes to mind is clothing, luxury, and lifestyle. Established in 1975, Zara is a Spanish multi-national retail clothing chain.

They specialize in clothing accessories, beauty, shoes, and other lifestyle products. Zara’s phenomenal success in fashion and beauty is a testament to its solid CRM strategy. They effortlessly delight their customers in a way that leaves them returning for more.

Zara CRM Case Study:

Zara’s CRM elevates its customer’s needs above the company objectives by leveraging transparency, incentives, support, personalization, swift check-out, and social media to achieve this.

Zara CRM starts with its website, which has a simple UI and is highly personalized to suit users’ needs. Then, it’s massively present on social media and contributes to social issues affecting its clientele.

The success of our business is based in principle on the idea of offering the latest fashions at low prices, in turn creating a formula for cutting costs: an integrated company in which it is manufactured, distributed, and sold.

– Amancio Ortega – Founder, Zara Fashion Chain

3. Unilever CRM

Unilever is a British multi-billion dollar conglomerate that deals primarily in consumer goods and consumables. They are arguably the largest producers of soap globally.

Brands like Unilever that have stood the test of time in quality, customer service, transparency, and consistency are worth emulating. With over 400 brands in about 190 countries, Unilever’s CRM strategy is paying off.

Unilever CRM Case Study:

Unilever’s CRM strategy focuses on elevating people’s well-being and helping them enjoy life to its fullest. This singular aim drives their excellent customer experience initiatives, marketing campaigns, products, and positioning.

Another main part of Unilever’s CRM strategy is centered around Value-Based Procurement. They are keen on supporting their suppliers with upfront value. They achieve this by empowering their suppliers and distributors with the tools to better relate to them.

They use Salesforce to support their business community and build solid relationships with their partners.

It’s about digitizing all the aspects of Unilever’s business to leverage the world of data and increase our digital capability in everything we do.

– Alan Jope, CEO at Unilever.

Bayerische Motoren Werke AG, known as BMW, is Germany’s leading automobile brand. They’re a luxury car brand and the  fourteenth largest producer of motor vehicles . BMW cars are known for their standard, uniqueness, and luxury. Let’s examine BMW’s CRM strategy. 

BMW CRM Case Study:

You’ll agree that BMW has become the world’s leading provider of premium automobile products. But the big question is, how did they get there?

BMW CRM case study is not too distant from the others. Firstly, the focus is on treating customers fairly, which is clearly stated in their  Supplier Programme . Their suppliers and end-users are at the core of their CRM strategy, which has kept them going.

Additionally, BMW CRM is focused on producing premium cars to attract new customers and retain the existing ones. Fortunately, it works for them. I’ve seen a couple of folks switch car brands to BMW because their cars are more reliable and have the highest quality.

I promise our customers will never have to compromise between driving pleasure and sustainable mobility.

– Oliver Zipse, CEO BMW AG.

5. Tesco CRM

Tesco PLC is one of the world’s leading grocery and general merchandise retailers. With operations in over 11 countries, Tesco is a hyper-growth company swiftly expanding across territories.

Although it started as a grocery store, it has now morphed into several industries such as banking, technology accessories, and a few others. Not just that, they’ve been named among the top customer-friendly organizations.

Tesco CRM Case Study:

Tesco is among the first multi-national brands to adopt CRM software. In 2009, Tesco announced that they were adopting the RightNow CRM (now acquired by Oracle).

Tesco’s CRM was primarily used in its call centres to support its electronics division. It was also used to amplify its omnichannel communication strategy by managing customer data and interactions across phone, chat, and email.

Adopting a CRM helped Tesco be present at all times for their customer when needed across channels. Most importantly, they were able to win the hearts of their customers.

The key to Tesco’s success is the customer-focused culture that has permeated the company.

– Jeremy Garlick, Partner, Insight Traction.

6. Uber CRM

With a presence in 72 countries, Uber redefines how we move and eat. Uber is an American mobility provider that allows people to move conveniently from one location to another. One of the things that makes Uber special is that it’s a mobility startup with no cars. That means it’s servicing two main customer bases: drivers and passengers.

As of the time of writing, Uber has a 72% market share for ride-sharing in the United States, with about 122 million monthly active users.

Uber CRM Case Study:

Uber’s mission is “ Transportation as reliable as running water, everywhere for everyone .” In other words, they aim to make transportation accessible at any time.

The big question is, what CRM does Uber use? Uber uses LiveRamp as its CRM anonymizer. Essentially, it uses LiveRamp CRM to segment users into specific life-cycle stages. This allows Uber to craft personalized and targeted campaigns that resonate with customers.

Furthermore, Uber uses CRM to gain deeper insights into how customers use their apps, the frequency, and overall interaction, and even sample their IDs. With these insights, Uber can better serve and delight its customers. More on Uber’s case study here.

There is a high cost to a bad reputation… it matters what people think of us, especially in a global business like ours, where actions in one part of the world can have serious consequences in another.” 

– Dan Khosroshahi.

7. McDonald’s CRM

McDonald’s is a fast-food conglomerate. It is currently the leading food service organization, operating over 30,000 restaurants in more than 100 countries. McDonald’s expansion strategy is based on franchises and joint ventures. It also has some sister brands in the fast-food industry that are doing incredibly well.

Mcdonald’s CRM Case Study:

McDonald’s mission statements depict McDonald’s passion for differentiation, uniqueness, and class. McDonald’s CRM case study hinges on its passion for differentiation, which is evident in the architectural designs of its restaurants, food recipes and taste, service delivery, and mode of operation.

McDonald’s uses PowerCenter CRM, which Astute Solutions powers. This CRM helps McDonald’s efficiently manage its huge volume of customer contacts, analyze data, and manage its store location.

The benefits of CRM software to a business are enormous, and McDonald’s is not left out. They use it equally to enhance their marketing efforts and close more deals.

Our sustained performance gives us confidence that our strategy is working, as more customers are experiencing a better McDonald’s daily.

– Steve Easterbrook, CEO, McDonald’s.

8. British Airways CRM

British Airways is a UK-based carrier and one of the most prominent airline groups in the world. Over the years, it has built a reputable brand that has also given birth to several sister brands.

BA Group is a founding member of the Oneworld alliance. It has over 45,000 employees in 100 countries and assists about 40 million passengers annually. So how does it maintain awesome customer service?

British Airways CRM Case Study:

British Airways’ CRM case study is centered around “making their passengers feel confident.”

British Airways uses TCRM BA as its enterprise management solution. The company adopted it in 2002, and since then, they’ve been using it to do the following:

• Campaign management

• Management of loyalty programs

• Leisure database

• External requirements

• Cost savings

Best of all, they use this platform to efficiently manage and schedule all their marketing campaigns internally and externally. They are also used for customer service across channels.

As we prepare for a safe return to travel, we remain focused on offering our customers the most convenient and affordable testing options to support and facilitate a seamless travel experience.

– Sean Doyle, CEO, of British Airways

9. Amazon CRM

Amazon is an American conglomerate that focuses on e-commerce, cloud computing, digital streaming, and artificial intelligence. It is among the top five most valuable companies worldwide and one of America’s biggest employers.

Amazon, which started as an online book store, is currently dominating up to seven industries. It’s also a customer-centric company famous for its outstanding customer service.

Amazon CRM Case Study:

Primarily, Amazon’s CRM case study follows these four guiding principles:

• Customer obsession rather than competitor focus

• Passion for invention

• Commitment to operational excellence

• Long-term thinking

They aim to become Earth’s most customer-centric company, Earth’s best employer, and Earth’s safest place to work. That drive to become the best led them to create innovative products like I-Click shopping, personalized recommendations, Amazon Echo, and Fire TV, to mention a few.

We see our customers as guests at a party, and we are the hosts. It’s our job every day to make every important aspect of the customer experience a little bit better.

– Jeff Bezos, CEO of Amazon

10. Apple CRM

Famously known for their slogan, think differently. Apple is a technology company specializing in consumer electronics, software, and online services. Apple is the world’s most valuable company and the first to hit a trillion in market capitalization.

Apple CRM Case Study:

Like Amazon, Apple is a customer-centric company that is truly obsessed with its customers.

Apple is also obsessed with its product quality. Their products are highly standardized and unique, which is why they enjoy a high level of brand loyalty. Apple’s customers are some of the most loyal globally.

The Apple CRM case study centers around four cardinal points: Apple customer-centric outlets, understanding customer needs, Apple ID, and irresistible branding that works. I explained them in detail here .

Additionally, like Amazon, Apple uses an in-house CRM to manage its customer data, marketing campaigns, and customer relationships. Apple loves owning its processes, so most of its operations are conducted in-house.

Conclusions

These case studies show us the efficacy and formidability of CRM software. When out to efficient use, it can be a potent tool. And it doesn’t matter the size of your business, whether big or small. All you need to do is pick a CRM that aligns with your business goals and run with it.

Looking for a CRM to start with? Here are our recommendations:  Zendesk ,  Pipedrive ,  Hubspot ,  Zoho , and  Freshsales . Click on any one of them to claim your free trial.

Frequently Asked Questions

Customer relationship management use cases are real-life examples and applications of CRM software and strategies. Like the 10 use cases from big brands listed in this article.

There are tons of use cases for CRM systems, but here are three profound ones: CRM systems can serve as a contact management system, a pipeline system for attracting and converting them paying customers, and a workflow automation station.

Essentially, the main components of CRM are contact and database management, workflow automation, omnichannel marketing capability, and integration options.

Viktor. A is a writer and researcher with experience writing about various topics, including CRM software, SaaS, finance, and technology. When he's not writing, he's swimming and traveling

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How Uber Is Building A New Age Of Intelligent Customer Experience

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By: Vicky Katsabaris, Director of Experience Management Solutions and Strategy, APJ, Qualtrics

As organizations continue to adapt to the changing world around us, every single business and government has a momentous opportunity to take the customer and employee experiences they deliver to an entirely new level.

During Qualtrics’ XM Live: Succeeding in the Age of Experience Transformation , we were privileged to get a rare glimpse into how iconic brands are building experience-centric organizations to drive business outcomes and success.

Uber is famous the world over for transforming the customer experience in the rideshare and food delivery industries. But like nearly every organization across the world, the pandemic challenged Uber to rethink how to make engagements easier and safer for customers, drivers and employees.

The solution to this challenge, according to Maisie Lam, Head of Customer Experience for Uber in Australia and New Zealand, was removing friction from the customer experience — not always an easy task when you have hangry customers.

“A negative peak or an end to an experience can completely bias a customer’s judgement. It means you need to know where in your users’ experience there is negative friction, or even positive peaks and resolutions,” Lam said.

Using insights and behavioral science to remove friction

Using behavioral science powered by insights from across the customer journey, Uber focused its efforts on removing friction from the customer journey to build a customer experience that was simple, intuitive, quick and easy. From using insights to improve the in-app help center for customers and riders, to identifying how it could optimize its Chat Support, Uber identified issues impacting its customer experience, and then took quick, targeted, meaningful action. The result has been a continual improvement to the company’s customer satisfaction across various channels.

A key pillar in Uber’s experience transformation is being aware of the bias blindspot.

“We can easily recognize the impact of biases on other people’s behavior and judgements, but we are very poor at noticing the impact of biases on ourselves,” Lam explained.

“It’s easy to underestimate the impact of a change in the context of your customers and support staff. And it’s easy to assume you understand user or agent experiences based on your own experience.”

“This means you need to be aware of cultural contexts when big change happens — in fact, this needs to be front and center of planning. You need to be conscious of the risk this change presents to the support channel. Using behavioral science and insights into your customer experience will help you diagnose where behavioral friction may be present.”

Driving continuous innovation

Uber’s constant desire to innovate by designing and continually improving experiences for customers’ and employees’ changing preferences and behaviors is why the company is a leader in the various sectors it operates. And it’s all possible because Uber is continuously listening and responding to the needs of the people it serves.

Find out how Uber is using data and insights to inform its business decisions by watching the full session from XM Live .

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Under the Hood of Uber’s Experimentation Platform

Experimentation is at the core of how Uber improves the customer experience. Uber applies several experimental methodologies to use cases as diverse as testing out a new feature to enhancing our app design.

Uber’s Experimentation Platform (XP) plays an important role in this process, enabling us to launch, debug, measure, and monitor the effects of new ideas, product features, marketing campaigns, promotions, and even machine learning models. The platform supports experiments across our driver, rider, Uber Eats, and Uber Freight apps and is widely used to run A/B/N, causal inference, and multi-armed bandit (MAB)-based continuous experiments.

There are over 1,000 experiments running on our platform at any given time. For example, before Uber launched our new driver app , completely redesigned with our driver-partners in mind, it went through extensive hypothesis testings through a series of experiments conducted with our XP.

At a high level, Uber’s XP allows engineers and data scientists to monitor treatment effects to ensure they do not cause regressions of any key metrics. The platform also lets users configure the universal holdout, used to measure the long-term effects of all experiments for a specific domain.

Below is a chart outlining the types of experimentation methodologies that the Experimentation Platform team uses:

There are various factors that determine which statistics methodology we should apply to a given use case. Broadly, we use four types of statistical methodologies: fixed horizon A/B/N tests (t-test, chi-squared, and rank-sum tests), sequential probability ratio tests (SPRT), causal inference tests (synthetic control and diff-in-diff tests), and continuous A/B/N tests using bandit algorithms (Thompson sampling, upper confidence bounds, and Bayesian optimization with contextual multi-armed-bandit tests, to name a few). We also apply block bootstrap and delta methods to estimate standard errors, as well as regression-based methods to measure bias correction when calculating the probability of type I and type II errors in our statistical analyses.

In this article, we discuss how each of these statistical methods are used by Uber’s Experimentation Platform to improve our services.

Classic A/B testing

Randomized A/B or A/B/N tests are considered the gold standard in many quantitative scientific fields for evaluating treatment effects. Uber applies this technique to make objective, data-driven, and scientifically rigorous product and business decisions. In essence, classic A/B testing enables us to randomly split users into control and treatment groups to compare the decision metrics between these groups and determine the experiment’s treatment effects.

A common use case for this methodology is feature release experiments. Suppose a product manager wants to evaluate whether a new feature increases user satisfaction with Uber’s platform. The product manager could use our XP to glean the following metrics:  the average values of the metric in both treatment and control groups, the lift (treatment effect), whether the lift is significant, and whether the sample sizes are large enough to wield high statistical power.

Statistics engine

One of our team’s main goals is to deliver one-size-fits-most methodologies of hypothesis testing that can be applied to use cases across the company. To accomplish this, we collaborated with multiple stakeholders to build a statistics engine.

When we analyze a randomized experiment, the first step is to pick a decision metric (e.g., rider gross bookings). This choice relates directly to the hypothesis being tested. Our XP enables experimenters to easily reuse pre-defined metrics and automatically handles data gathering and data validation. Depending on the metrics type, our statistics engine applies different statistical hypothesis testing procedures and generates easy-to-read reports. At Uber, we invest heavily in the research and validation of methodologies and are constantly improving the robustness and effectiveness of our statistics engine.

Figure 5, below, offers a high-level overview of this powerful tool:

Key components and statistical methodologies

After gathering data, our XP’s analytic platform validates the data and detects two major issues for experimenters to watch for and to keep a healthy skepticism in their A/B experiments:

• Sample size imbalance , meaning that the sample size ratio in the control and treatment groups is significantly different from what was expected. In these scenarios, experimenters must double check their randomization mechanisms.
• Flickers , which refers to users that have switched between control and treatment groups. For example, a rider purchases a new Android cell phone to replace an old iPhone, while the treatment of the experiment was only configured for iOS. The rider would switch from the treatment group to the control group. Existence of such users might contaminate the experiment results, so we would exclude these users (flickers) in our analyses.

Most of our use cases are randomized experiments and most of the time summarized data is sufficient for performing fixed horizon A/B tests. At the user level, there are three distinct types of metrics:

• Continuous metrics contain one numeric value column, e.g., gross bookings per user.
• Proportion metrics contain one binary indicator value column, e.g., to test the proportion of users who complete any trips after sign-up.
• Ratio metrics contain two numeric value columns, the numerator values and the denominator values, e.g., the trip completion ratio, where the numerator values are the number of completed trips, and the denominator values are the number of total trip requests.

Three variants of data preprocessing are applied to improve the robustness and effectiveness of our A/B analyses:

• Outlier detection removes irregularities in data and improves the robustness of analytic results. We use a clustering-based algorithm to perform outlier detection and removal.
• Variance reduction helps increase the statistical power of hypothesis testing, which is especially helpful when the experiment has a small user base or when we need to end the experiment prematurely without sacrificing scientific rigor. The CUPED Method  leverages extra information we have and reduces the variance in decision metrics.
• Pre-experiment bias is a big challenge at Uber because of our diversity of users. Sometimes, constructing robust counterfactual via mere randomization just doesn’t cut it. Difference in differences (diff-in-diff) is a well-accepted method in quantitative research and we use it to correct pre-experiment bias between groups so as to produce reliable treatment effects estimation.

The p-value calculation is central to our statistics engine. The p-value directly determines whether the XP reports that a result is significant. We compare the p-value to the false positive rate (Type-I error) we desire (0.05) in a common A/B test. Our XP leverages various procedures for p-value calculation, including:

• Welch’s t-test , the default test used for continuous metrics, e.g., completed trips.
• The Mann-Whitney U test , a nonparametric rank sum test used to detect severe skewness in the data. It requires weaker assumptions than the t-test and performs better with skewed data.
• The Chi-squared test , used for proportion metrics, e.g., rider retention rate.
• The Delta method ( Deng et al. 2011 ) and bootstrap methods, used for standard error estimation whenever suitable to generate robust results for experiments with ratio metrics or with small sample sizes, e.g., the ratio of trips cancelled by riders.

On top of these calculations, we use multiple comparison correction (the Benjamini-Hochberg procedure ) to control the overall false discovery rate (FDR) when there are two or more treatment groups (e.g., in an A/B/C test or  an A/B/N test).

The power calculation provides additional information about the level of confidence users should put into their analysis. An experiment with low power will suffer from high false negative rates (Type-II error) and high FDRs. In the power calculations our XP conducts, a t-test is always assumed. On the flipside, required sample size calculation is the opposite of a power calculation and estimates how many users are required by the experiment for it to achieve a high power (0.8).

Metrics management

As the number of the metrics used by the XP’s analytics component grows (incorporating 1,000+ metrics), it becomes more and more challenging for users to determine the proper metrics to evaluate the performance of an experiment. To make it easier for new users of our analytics tool to uncover these metrics, we built a recommendation engine that facilitates the discovery of metrics available on our platform.

At Uber, there are two common collaborative filtering methods used for content recommendation: item-based and user-based methods. We primarily use an item-based recommendation engine since the characteristics of the experimenter do not typically have a strong influence on their project. For instance, if an experimenter switches to the Uber Eats team from the Rider team, it’s not necessary for the algorithm to review the previous, Uber Eats-inspired choices of that experimenter when selecting metrics to evaluate.

Recommendation engine methodology

To determine how correlated two metrics are to each other, we add their popularity and absolute scores, enabling us to better understand their relationship. The two basic approaches to calculating these scores are:

• Popularity score: The more frequently two metrics are selected together across experiments, the higher the score assigned to their relationship. We use the Jaccard Index  to help users discover the most relevant metric once they select their initial metric. This score accounts for the experimenters’ metrics selection from past experiments.
• Absolute score: Using our XP, we can generate a pool of user samples from our metrics and calculate the Pearson correlation score of the two metrics. This accounts for serendipitous discovery; namely, the experimenter may not have considered adding a metric to the experiment since it is not directly related, but it might be moving with the user-selected metric.

After calculating these two scores, we add the score of the two steps above with relative weights on each term and recommend the metrics with the highest score to the experimenter based on their first choice of metrics.  

Insights discovery

As Uber continues to scale, it becomes more and more challenging to mine our metrics knowledge base. Our recommendation engine enables both global and local teams to access the information they need quickly and easily, allowing them to improve our services accordingly.  

For example, if an experimenter wants to measure the treatment effect on driver-partner supply hours, it may not be obvious to the experimenter to also add the number of trips taken by new riders as a metric, since this experiment focuses on the driver side of the trip equation. However, both metrics are important for this experiment because of the dynamics of our marketplace. Our recommendation engine helps data scientists and other users discover important metrics that may not have been obvious.

Sequential testing

While traditional A/B testing methods (for example, a t-test) inflate Type-I error by repeatedly taking subsamples, sequential testing offers a way to continuously monitor key business metrics.

One use case where a sequential test comes in handy for our team is when identifying outages caused by the experiments running on our platform. We cannot wait until a traditional A/B test collects sufficient sample sizes to determine the cause of an outage; we want to make sure experiments are not introducing key degradations of business metrics as soon as possible, in this case, during the experimentation period. Therefore, we built a monitoring system powered by a sequential testing algorithm to adjust the confidence intervals accordingly without inflating Type-I error.

Using our XP, we conduct periodic comparisons about these business metrics, such as app crash rates and trip frequency rates, between treatment and control groups for ongoing experiments. Experiments continue if there are no significant degradations, otherwise they will be given an alert or even paused. The workflow for this monitoring system is shown in Figure 6, below:

Methodologies

We leverage two main methodologies to perform sequential testing for metrics monitoring purposes: the mixture sequential probability ratio test (mSPRT) and variance estimation with FDR.

Mixture Sequential Probability Ratio Test

Variance estimation with FDR control

To apply sequential testing correctly, we need to estimate variance as accurately as possible.  Since we monitor the cumulative difference between our control and treatment groups on a daily basis, observations from the same users introduce correlations which violate the assumption of the mSPRT test. For example, if we are monitoring click through rates, then the metric from one user across multiple days may be correlated. To overcome this, we use delete-a-group jackknife variance estimation /block bootstrap methods to generalize mSPRT test under correlated data.

Since our monitoring system wants to evaluate the overall health of an ongoing experiment, we monitor many business metrics at the same time, potentially leading to false alarms. In theory, either the Bonferroni or BH correction could be applied in this scenario. However, since the potential loss of missing business degradations can be substantial, we apply BH correction here and also tune in parameters (MDE, power, tolerance for practical significance, etc.) for metrics with varying levels of importance and sensitivity.

Suppose we want to monitor a key business metric for a specific experiment, as depicted in Figure 7, below:

As time passes, we accumulate more samples and the confidence interval narrows. In Plot B, the confidence interval consistently deviates from zero starting on a given date, in this example, November 21. With an extra threshold (in other words, tolerance for our monitoring system) for practical significance imposed, metrics degradation is detected to be both statistically and practically significant after a certain date. In contrast, Plot A’s confidence interval shrinks but always includes 0. Thus, we didn’t detect any regressions for the crash monitored in Plot A.

Continuous experiments

To accelerate innovation and learning, the data science team at Uber is always looking to optimize driver, rider, eater, restaurant, and delivery-partner experiences through continuous experiments. Our team has implemented bandit and optimization-focused reinforcement learning methods to learn iteratively and rapidly from the continuous evaluation of related metric performance.

Recently, we completed an experiment using bandit techniques for content optimization to improve customer engagement. The technique helped improve customer engagement compared to classic hypothesis testing methods. Figure 9, below , outlines Uber’s various continuous experiment use cases, including content optimization, hyper-parameter tuning, spend optimization, and automated feature rollouts:  

In Case Study 1, we outline how bandits have helped optimize email campaigns and enhance  rider engagement at Uber. Here, the Uber Eats Customer Relationship Management (CRM) team in Europe, the Middle East, and Africa (EMEA) launched an email campaign to encourage order momentum early in the customer life cycle. The experimenters plan to run a campaign with ten different email subject lines and find out the best subject line in terms of the open rate and the number of open emails. Figure 10, below, details this case study:

A second example of how we leverage continuous experiments is parameter tuning. Unlike the first case, the second case study uses a more advanced bandit algorithm, the contextual multi-armed bandit technique, which combines statistical experiments and machine learning modeling. We use contextual MAB to choose the best parameters in a machine learning model.

As depicted in Figure 11, below, the Uber Eats Data Science team leveraged MAB testing to create a linear programming model, called the multiple-objective optimization (MOO), that ranks restaurants on the main feed of the Uber Eats app:

The algorithm behind MOO incorporates several metrics, such as session conversion rate, gross booking fee, and user retention rate. However, the mathematical solution contains a set of parameters that we need to give to the algorithm.

These experiments contain many parameter candidates for use with our ranking algorithms. The ranking results depend on the hyper-parameters we chose for the MOO model. Therefore, to improve the performance of the MOO model, we hope to figure out the best hyper-parameters via multi-armed bandits algorithm. The traditional A/B test framework is too time-intensive to handle each test, so we decided to utilize the MAB method for these experiments. MAB is able to provide a framework to quickly tune these parameters.

We chose the contextual MAB and the Bayesian optimization methods to find the maximizers of a black box function optimization problem. Figure 12, below, outlines the setup of this experiment:  

As shown above, contextual Bayesian optimization works well with both personalized information and exploration-exploitation trade-offs.

Moving Forward

As a result of its scale and global impact, Uber’s problem space poses unique challenges. As our methodologies evolve, we aspire to build an ever more intelligent experimentation platform. In the future, this platform will provide insights gleaned not only from current experiments, but also previous ones, and, over time, proactively predict metrics.  

Uber’s Experimentation Platform team is hiring. If you are passionate about experimentation and machine learning, please apply for this role.

Subscribe to our newsletter  to keep up with the latest innovations from Uber Engineering.

Anirban Deb

Anirban Deb is the former tech lead of the Experimentation, Segmentation, Personalization and Mobile App Development Platform data science teams at Uber and currently heading the Uber Freight data science organization.

Suman Bhattacharya

Suman Bhattacharya is a senior data scientist on Uber’s Experimentation Platform team.

Jeremy Gu is a data scientist on Uber’s Experimentation Platform team.

Tianxia Zhou

Tianxia Zhou is a data scientist on Uber's Experimentation Platform team.

Eva Feng is a data scientist on Uber's Experimentation Platform team.

Mandie Liu is a data scientist on Uber’s Experimentation Platform team.

Posted by Anirban Deb, Suman Bhattacharya, Jeremy Gu, Tianxia Zhou, Eva Feng, Mandie Liu

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4 Amazing CRM Case Studies You Should Go Through in 2022

Are you a business owner? Do you think your company has adapted to the evolving digital landscape?

While you may have figured out most of it, there is one important thing you should know if you want to be successful. 

Simply having the best product or offering the best services will not guarantee profitability. It is very important to forge strong relationships with your customers and work on boosting retention and loyalty. 

If you are wondering how you can improve customer relationship management, here are a few amazing CRM case studies for you. 

As more and more companies turn their attention to enhancing customer loyalty and retention, customer relationship management tools have become very popular. 

Besides, even the arrival of the COVID–19 pandemic has accelerated the demand for tools of CRM since 2020. The CRM market is expected to reach a market size of $129.9 globally by the end of 2028 [1]. 

So how have the big brands cracked the code and why are they so good at CRM? How do they do it?

To answer these questions, we are going to bring you some case studies which will give you a fair idea. 

Without wasting much time, let’s dive straight in. 

SEE ALSO: 7 Marketing Automation Trends to Look Out for in 2022

Understanding how big companies do CRM: Case studies

1. apple crm.

Apple, the brand itself does not need any introduction. 

The company which was founded by Steve Jobs is a global phenomenon and continues to send ripples of excitement during product launches. 

Apple has rolled out revolutionary products including the iMac, iPhone, iPad, and Apple TV. While there are no apprehensions pertaining to the quality of these products, Apple leaves no stone unturned to ensure customer satisfaction. 

Let’s explore how Apple leverages Apple ID.

If you have used iTunes, you will know that you need an Apple ID. Besides, even if you use an Apple device, you will need an Apple ID to register it. 

Your Apple ID syncs with all your devices to keep track of your movie and music choices and offer customized recommendations based on that information. 

What problem is this solving? It provides users with a higher level of convenience.

Apple uses the data it has collected to understand what its customers are looking for enabling them to improve their targeted marketing strategies. 

This is a classic case of a well-done CRM. 

2. Uber CRM

Uber hit the market in 2009 and since then has been at the forefront of the ride-sharing revolution. 

Today, Uber is a household name in many parts of the world, but the big question is, can it continue its dominance in the future? Well, we will have to wait and find out. In the meanwhile, we can take a look at how Uber has acquired more than 95 million customers worldwide. 

It is no secret that Salesforce has powered Uber’s CRM strategy and helped the company reach new milestones. 

Salesforce, one of the leading CRM vendors in the world helps Uber collect data from users who are engaging with the brand on social media. This approach helps Uber address customer queries and complaints in a timely manner. 

Besides, Uber can also keep track of all interactions with customers via an intuitive dashboard. 

Let’s not forget Uber’s loyalty program which allows customers to collect Uber Rewards. 

Every user earns points when they ride or eat with Uber, which can be redeemed across Uber’s plethora of services. 

It is safe to say that it is a textbook example of a brand acquiring customers by incentivizing them. 

3. McDonald’s

Did you know that McDonald’s serves around 1 million customers only in the UK? The number is projected to be anywhere close to 65-70 million across the world. 

So what is the secret sauce behind ensuring that customers keep coming back for more?

McDonald’s CRM strategy is second to none and this is why this is an interesting CRM case study. 

McDonald’s has joined hands with Astute Solutions. This partnership enables the global fast-food company to gain deep insights into customer feedback and their satisfaction levels. 

The company can also evaluate a restaurant’s performance based on region and swiftly identify gaps in customer relationships. Besides, this allows McDonald’s to step in before even the smallest of issues turn into serious problems. 

Astute Solutions works with McDonald’s to offer real-time customer information, integrate information from its restaurant into an advanced CRM tool, and enhance the accuracy of its reporting to facilitate sound decision-making. 

4. British Airways

The aviation industry is highly competitive and very consumer-oriented. Even a single bad experience is enough for customers to never look back.

So how does British Airways manage to fly more than 145,000 passengers to over 200 destinations each day? Why do customers love Birtish Airways?

The answer is clear – it’s Executive Club. 

The British Airways Executive Club is an excellent example of one should do CRM loyalty schemes. 

The program is free of cost and does have any ongoing charges. It allows passengers to earn ‘Avios’ points when you buy holiday packages, car rental, hotels, and flights via British Airways or its affiliated partners. 

These ‘Avios’ points can be redeemed for discounts on accommodation or flight tickets. Users can also choose their seat and meal preferences, paving the way for a flawless booking experience. 

As customers continue to fly with British Airways, they will be able to advance through the different tiers of the Executive Club membership (from blue to Gold). 

British Airways keeps track of this information using a CRM system named Teradata. It allows the airline operator to stay on top of all customer bookings and how they are engaging with their offers and deals. 

Learn, adapt, implement 

What are the key takeaways from all of these CRM case studies? 

Customer is the king, and if you treat the king right, your business will flourish. 

Having said that, it is important to have a full-proof CRM strategy in place to ensure you strengthen your relationship with your customers. It is critical that you start creating strategies to pull in more leads, manage deals in the pipeline, and foster healthy customer relationships. 

You will have to figure out a way to improve customer engagement, track your engagement, and also identify a way to improve your brand’s value. 

These CRM cast studies have made one thing very clear modern CRM software is a key part of this puzzle. 

If you are looking for a CRM software to take your customer relationship management to the next level, you can check out the different tools on our website. 

Read our reviews, compare different CRM solutions, and find a solution just for you. 

SEE ALSO: 5 Bold Predictions for CRM Software in 2022

Feature Image Source: rawpixel.com

Image 1 Source: rawpixel.com

Image 2 Source: rawpixel.com

[1] O’Connor. E (2022) “ TOP 50 CRM STATISTICS AND TRENDS FOR 2022 ” EPC Group [online] Accessed [March 2022]

Karandeep V

Karandeep was born in Pune, Maharashtra, an upcoming metropolitan city in the Western region of India. While most members of his family are engineers, he had different ideas. He was more inclined toward exploring the non-technical aspects of a business, which is why he studied Bachelors of Business Administration at Symbiosis International University, Pune.  Having said that, his love for new and upcoming technologies remained intact, which is why he has written extensively about technology throughout his career. After a brief stint with a gaming company at the beginning of his career, he discovered that his love for writing was not temporary.  Being a tech geek, he always liked installing and playing around with new applications on his mobile devices and the home desktop. He was fascinated by how technology can simplify even the most mundane and complex tasks with just a few commands. He keeps a close eye on how businesses use different tools to streamline their operations to boost productivity and efficiency. At ToolsMetric, he writes product reviews that cover the main features and specifications of different enterprise applications. The sheer amount of innovation and hard work that goes into building these tech solutions is one of the reasons why Karandeep loves reviewing these tools. Besides product reviews, he also writes interesting news articles and blogs that track the latest developments in the tech industry.  When he is not writing, you can find him rooted to his seat playing video games, watching movies, or supporting his favorite football team. Since his childhood, he has always loved to travel and explore new places. Traveling is a major part of his life due to a myriad of reasons such as experiencing new cultures, food, and traditions. His other hobbies include playing football, cooking, and running.  You can find him on LinkedIn here .

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10 CRM studies you need to read before you select your next CRM

Take a look at these CRM case studies before deciding which is the best software for your needs

British Airways

Wells fargo.

1.  Uber

3. British Airways

4. Wells Fargo

6. McDonald's

8. Unilever

9. Activision

10. Amazon  

In a crowded market, discerning what the best CRM software is to meet your needs is difficult. Reviews, statistics, and user feedback are all useful, of course, but sometimes reading evidence of how a brand has employed a CRM tool as part of a specific project is what is really needed to convince businesses that a particular piece of software is a good fit.

The need for a trustworthy CRM case study is made even more pressing given the sheer number of solutions on the market - many with their own strengths and weaknesses, as well as target audiences. For example, would a list of the best CRM for startups be relevant for your company? Or would the best recruitment CRM be more suitable? There are also the best insurance CRMs , the best CRMs for real estate , the best sales CRM , and more to consider. 

One of the best ways of answering, “ What is CRM software? ” is to look at the tools already on the market and then, if you want to see how they have been employed effectively by brands in the past, examining some high-profile CRM case studies should be next on your agenda. Below, we outline 10 CRM studies that will demonstrate the full potential of this powerful solution and how it’s been used across a wide range of industries.

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The 10 CRM studies you need to read 

Today, Uber is known the world over for having disrupted mobility completely, garnering a valuation that dwarfs that of more established players in the automotive space - despite owning zero vehicle assets itself. However, despite its future-first ethos, Uber still depends on CRM software to ensure it is able to harness the huge quantities of data at its disposal. 

Uber uses Salesforce CRM software to extract data from individuals who engage with its brand on social media, ensuring that interactions are monitored, complaints are responded to, and all feedback can be put towards the creation of a better customer experience. By piecing all relevant data within a holistic dashboard, Uber can tailor offers, recommendations, and promotions based on previous customer interactions.

Uber has always understood that the real value lies in customer data - not simply providing a transportation service. That’s why it makes more sense to think of it as a technology company; not a taxi firm. With that in mind, finding a suitable CRM platform has long been critical to Uber’s success. This has allowed the company to monitor customer behavior and riding habits - even as it experiences rapid growth. 

Another of the great disruptors of the 21st-centrury economy, Airbnb couldn’t have achieved its huge success without relying on a suitable CRM solution. The scale of the Airbnb platform is mind-boggling. The platform boasts more than 100 million guests globally, has listings in 65,000 cities and 191 countries, and is used by an estimated one in every four leisure travellers. 

This scale means that Airbnb is privy to huge quantities of data and faces a seriously large number of queries every day. To manage this, Airbnb decided to make use of the Zendesk CRM , which offered the scalability, reliability, and uptime needed to facilitate growth as the number of hosts and guests using the platform continued to rise rapidly. 

Airbnb’s Global Customer Experience team uses Zendesk to provide real-time support to customers across multiple channels, with every contact recorded within Zendesk Support. Zebdesk also empowers Airbnb to gain a grip of customer data by providing a 360-degree view of each customer. This means support can be personalized and a better customer experience can be delivered.  

The travel industry has bounced back remarkably well after being decimated by the pandemic. Brands have had to reconsider how their revenues are driven, however, with global airline capacity taking several years to return to pre-COVID levels. One of the ways that brands have attracted tourists back in the air is with value-add services like the British Airways Executive Club. 

Utilizing the Teradata CRM, the British Airways Executive Club is a loyalty scheme that allows individuals to earn points by purchasing flights, hotel stays, or car rentals through British Airways or its partners. Customers can also save their preferences so repeat bookings are smoother, ensuring a seamless customer experience. They also have the opportunity to work their way up the membership ranks, achieving blue, bronze, silver, gold, or Premier membership.

The British Airways Executive Club demonstrates how CRM solutions can be used to strengthen customer loyalty. The platform allows the airline to keep track of customer preferences so it can offer targeted deals based on their membership level and past bookings. 

One of the largest banks in the US, Wells Fargo manages sensitive information for approximately 70 million individuals. But even with its considerable scale, Wells Fargo must continue to uphold the highest standards of customer service - particularly given the competitive nature of its industry. As well as other established financial institutions, organizations like Wells Fargo have also seen their market share come under threat from new fintech start-ups.

In light of the increasingly competitive financial sector, Wells Fargo employs a CRM solution to ensure its many different departments run smoothly and customer communication is seamlessly enabled. This means empowering social media connectivity and collating customer contact across multiple channels. 

Wells Fargo has revealed that its use of a CRM has enabled it to greatly increase efficiency so greater focus can be placed on high-value work because certain manual tasks can be streamlined or even automated. This has led to the creation of more optimized platforms, allowing the bank to save time and energy and ensuring customers receive better service.

Once the world’s number one smartphone manufacturer, Nokia’s brand still carries some considerable heft - even if the likes of Apple , Samsung , and Google have taken its smartphone crown. Nokia’s use of the Salesforce CRM has played a major role in ensuring that the company continues to generate significant revenues in a fast-changing market.

One of the major challenges facing Nokia before it began using the Salesforce CRM was how to manage the diversity and scale of its products and markets across different geographies and languages. Salesforce allows Nokia to more easily organize its data - no matter how spread out it is.

Salesforce allows Nokia to select and segment data into specific target groups for more effective lead generation. It has also led to the creation of the Nokia Intelligent Care Assistant, which integrates directly with the Salesforce Service Cloud. This collaboration provides a holistic subscriber view, which enables truly omnichannel customer service, including proactive support. Although Nokia’s brand may not carry the same weight as it once did, without the company’s employment of the Salesforce CRM, it may no longer be around at all.

The fast-food giant McDonald’s has become one of the most recognizable brands in the world - but their success is down to more than just flipping burgers. McDonald’s has a long-running partnership with CRM platform Astute Solutions, which provides the restaurant chain with detailed insights on customer satisfaction levels and other forms of feedback. Providing a breakdown by region or individual restaurant, Astute enables McDonald’s to quickly identify potential customer issues so they can be remediated swiftly. 

With McDonald’s serving an estimated 60 million people every day, managing the huge amount of data at its disposal is key to providing a quality service. As such, the company’s CRM provides real-time access to customer information, integrates data from across a network consisting of thousands of restaurants, and provides accurate reports for managers.

Despite McDonald’s global standing, the fast-food space is a crowded one and the restaurant chain is always looking to open new sites and launch new products. In order to gain visibility into what customers want and how best to capture potential new customers, data is key. For an organization of McDonald’s size, managing this data has only been made possible through its use of a CRM. 

The automotive space has undergone massive change in recent years and further evolution is predicted for the not-too-distant future. Even though BMW may have been around since the early 1900s, it knows that no firm is immune from disruption - even those that have existed for over a century. 

With most vehicles now incorporating an increasing number of software solutions, they represent an effective way for firms to harvest, collate, and analyze data. BMW uses a CRM to realize the benefits that can be unlocked through this data, by capturing data from multiple sources including - whether that includes dealerships, web pages, call centers , SMS, or through direct marketing .

In addition, CRM software has played an essential role in the company’s loyalty scheme, “The Owner’s Circle.” This lets BMW owners of old or new cars register their vehicles online and monitor their car’s financing and maintenance. All this helps to strengthen the post-purchase relationship between the vehicle owner and BMW, allowing them to check the status of their new car order, view the maintenance history of a used car, or get reminders about upcoming service milestones. It’s about maintaining engagement after a transaction has been completed.

One of the world’s largest producers of consumer goods, Unilever manufactures a host of items that are commonly purchased by households across the world, including Dove. Persil, Domestos, and many more. Given the sheer number of goods Unilever produces, it understandably handles a huge amount of customer data. Using SAP’s CRM, Unilever was able to improve its call center capabilities and increase the productivity of its consumer-facing teams.

Unilever has also employed CRM tools to capture real-time information from customer surveys across and run targeted campaigns to capture customer data. The company’s use of the technology has allowed for faster response times to consumer queries and more efficient maintenance of customer databases.

Unilever represents a great example of how CRM tools can provide clarity and unity to a company that has grown far beyond its domestic market and offers products that spread across multiple categories and industries. The analytics functionality, in particular, allows Unilever to better understand consumer challenges allowing the company to apply its innovations and digitalization efforts to the launch of new products.

Video game maker Activision is responsible for some of the most popular series in the world, including the likes of Call of Duty , Crash Bandicoot, Guitar Hero, and many others. But where Activision’s only real concern was ensuring sales figures were high enough, now the company’s aim is to build long-lasting customer relationships. For that, a CRM is key.

Making use of the Salesforce CRM, Activision was able to completely overhaul its customer service offering. Before employing the CRM, almost half of all customers experiencing an issue spoke to an Activision rep over the telephone, but today 82% use an online self-service portal, with 10% opting for social channels. This has had a major impact in terms of cost reduction and customer satisfaction levels.

Because of the way that the Salesforce CRM can scour social networks for relevant posts, Activision has been able to get much closer to the gaming community. As such, it has become easier to understand their likes, dislikes, needs, and issues. Challenges have been resolved faster and insights have been put towards the creation of the next blockbuster game

Amazon may be one of the biggest companies in the world but it still requires third-party help in the form of a CRM solution. The e-commerce juggernaut not only provides an online retail site but also offers a popular cloud computing service in the form of Amazon Web Services, which has been using Salesforce CRM since 2006.

Elsewhere, Amazon has crafted its own bespoke CRM strategy to ensure it offers native integration with other Amazon software. The technology giant uses its CRM to share personalized offers and promotions with customers, collect data en masse and store it, and provide recommendations based on an individual’s purchase history. 

In the years since its founding, Amazon has seen plenty of companies come and go, but still, it remains top of the tree. Over the years, the company has understood that what sets it apart is not the products it offers, but the data that it has access to. And the best way of managing this is through a CRM.

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Barclay has been writing about technology for a decade, starting out as a freelancer with ITProPortal covering everything from London’s start-up scene to comparisons of the best cloud storage services.  After that, he spent some time as the managing editor of an online outlet focusing on cloud computing, furthering his interest in virtualization, Big Data, and the Internet of Things. 

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Uber’s Strategy for Global Success

How can Uber adapt its business model to compete in unique global markets?

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As Uber entered unique regional markets around the world – from New York to Shanghai, it has adapted its business model to comply with regulations and compete locally. As the transportation landscape evolves, how can Uber adapt its business model to stay competitive in the long term?

Harvard Business School assistant professor Alexander MacKay describes Uber’s global market strategy and responses by regulators and local competitors in his case, “ Uber: Competing Globally .”

HBR Presents is a network of podcasts curated by HBR editors, bringing you the best business ideas from the leading minds in management. The views and opinions expressed are solely those of the authors and do not necessarily reflect the official policy or position of Harvard Business Review or its affiliates.

BRIAN KENNY: The theory of disruptive innovation was first coined by Harvard Business School professor Clayton Christensen in his 1997 book, The Innovator’s Dilemma . The theory explains the phenomenon by which an innovation transforms an existing market or sector by introducing simplicity, convenience, and affordability where complication and high cost are the status quo. Think Netflix disrupting the video rental space. Over the years, the term has been applied liberally and not always correctly to other examples, but every so often, an idea comes along that really fits the bill. Enter Uber, the ridesharing behemoth that turned the car service industry on its head. In a few short years after launching in 2010, Uber became the largest car service in the world, as measured in ride count. Last year, Uber drove 6.2 billion riders. Today’s case takes us to London in 2019, where Uber is facing the latest in a long list of challenges from regulators threatening their ability to continue operating in that important market. In this episode of Cold Call , we welcome Alexander MacKay to discuss the case entitled, “Uber: Competing Globally.” I’m your host, Brian Kenny, and you’re listening to Cold Call on the HBR Presents network.

Alexander MacKay is in the strategy unit at Harvard Business School. His research focuses on matters of competition, including pricing, demand, and market structure. Alex, thanks for joining us on Cold Call today.

ALEX MACKAY: Thank you, Brian. Very happy to be here.

BRIAN KENNY: The idea of Uber seems so simple, but it was revolutionary in so many ways. And Uber has been in the headlines many times for both good and bad reasons in its decade of existence. So we’re going to touch on a lot of those things today. So thanks for sharing the case with us.

ALEX MACKAY: Brian, I’m very happy to. It’s a little funny, we’ve actually started to see the first few students who have never hailed a traditional taxi in our classrooms. So I think increasingly, the contrast between the two is going to be pretty difficult for people to fully understand.

BRIAN KENNY: Let me ask you to start by telling us what your cold call would be when you set up the class here.

ALEX MACKAY: The case starts off with the current legal battle going on in London. And so the first question I just ask to start the classroom is: What’s the end game for Uber in London? What do they look like 10 years from now? In the midst of this ongoing legal battle, there has been back and forth, some give and take from both sides, Transportation for London, and also on the Uber side as well. And there’s actually a recent court case that has allowed Uber to have a little more time to operate. They bought about 18 more months of time, but this has been also brought with additional, stricter scrutiny, and 18 months from now, they’re going to be at it again trying to figure out exactly what rules Uber’s allowed to operate under.

BRIAN KENNY: It seems like 18 months in the lifetime of Uber is like a decade. Everything seems to happen so quickly for this company. That’s a long period of time. What made you decide to write this case? How does it relate to the work that you’re doing in your research?

ALEX MACKAY: A big focus of my research is on competition policy, particularly the realms of antitrust and regulation. And here we have a company, Uber, whose relationship with regulation has been really essential to its strategy from day one. And I think appreciating the effects of regulation and how its impact Uber’s performance in different markets, is really critical for understanding strategy and global strategy broadly.

BRIAN KENNY:  Let’s just talk a little bit about Uber. I think people are familiar with it, but they may not be familiar with just how large they are in this space. And the space that they’ve sort of created has also blown up and expanded in many ways. So how big is Uber? Like what’s the landscape of ridesharing look like and where does Uber sit in that landscape?

ALEX MACKAY: Uber globally is the biggest ridesharing company. In 2018, they had over $10 billion in revenue for both ridesharing and their Uber Eats platform. And you mentioned in the introduction, that they had over 6 billion rides in 2019. That’s greater than 15 million rides every day that’s happening on their platform. So really, just an enormous company.

BRIAN KENNY: So they started back in 2010. It’s been kind of an amazing decade of growth for them. How do you explain that kind of rapid expansion?

ALEX MACKAY: They were financed early on with some angel investors. I think Kalanick’s background really helped there to get some early funding. But one of the critical things that allowed them to expand early into many markets that helped their growth was they’re a relatively asset light company. On the ground, they certainly need sales teams, they need translation work to move into different markets, but because the main asset they were providing in these different markets was software, and drivers were bringing their own cars and riders were bringing their own phones, the key pieces of hardware that you need to operate this market, they really didn’t have to invest a ton of capital. In fact, when they launched in Paris, they launched as sort of a prototype, just to show, “Hey, we can do this in Paris without too much difficulty,” as their first international market. So being able to really scale it across different markets really allowed them to grow. I think by 2015, their market cap was $60 billion, five years after founding, which is just an incredible rate of growth.

BRIAN KENNY: So they’re the biggest car service in the world, but they don’t own any cars. Like what business are they really in, I guess is the question?

ALEX MACKAY: They’re certainly in the business of matching riders to drivers. They’ve been able to do this in a way that doesn’t require them to own cars, just through the use of technology. And so what they’re doing, and this is I think pretty well understood, is that they’re using existing capital, people who have cars that may be going unused, personal cars, and Uber is able to use that and deploy that to give riding services to different customers. Whereas in the traditional taxi model, you could have taxis that you didn’t necessarily own, but you leased them or you rented them, but they had the express purpose of being driven for taxi services. And so it wasn’t using idle capital. You kind of had to create additional capital in order to provide the services.

BRIAN KENNY: So you mentioned Travis Kalanick a little bit earlier, but he was one of the co-founders of the company, and the case goes a little bit into his philosophy of what expansion into new markets should look like. Can you talk a little bit about that?

ALEX MACKAY: Certainly. Yeah. And I think it might even be helpful to talk a bit about his background, which I think provides a little more context before Uber. He dropped out of UCLA to work on his first company, Scour, and that was a peer-to-peer file sharing service, a lot like Napster, and actually predated Napster. And where he was operating was sort of an evolving legal gray area. Eventually, Scour got sued for $250 billion by a collection of entertainment companies and had to file for bankruptcy.

BRIAN KENNY: Wow.

ALEX MACKAY: He followed that up with his next venture, Red Swoosh, and that was software aimed at allowing users to share network bandwidth. So again, it was a little bit ahead of its time, making use of recent advances in technology. Early on though, they got in trouble with the IRS. They weren’t withholding taxes, and there were some other issues with his co-founder, and there was sort of a bad breakup between the two. Despite this, he persevered and ended up selling the company for $23 million in 2007. And after that, his next big thing was Uber. So one thing I just want to point out is that at all three of these companies, he was looking to do something that leveraged new technology to change the world. And by nature, sometimes businesses like that operate in a legal gray area and you have very difficult decisions to make. Some other decisions you have to make are clearly unethical and there’s really no reason to make some of those decisions, like with the taxes and with some other things that came out later on at Uber, but certainly one of the things that any founder who’s looking to change the world with a big new technology company has to deal with, is that often, the legal framework and the regulatory framework around what you’re trying to do isn’t well established.

BRIAN KENNY: Obviously drama seems to follow Travis where he goes. And his expansion strategy was pretty aggressive. It was almost like a warlike mentality in terms of going into a new market. And you could sort of sum it up as saying ask forgiveness. Is that fair?

ALEX MACKAY: Yeah. Yeah. Ask for forgiveness, not permission. I think they were really focused on winning. I think that was sort of their ultimate goal. We describe in the case there’s this policy of principle confrontation, to ignore existing regulations until you receive pushback. And then when you do receive pushback, either from local regulators or existing sort of taxicab drivers, mobilize a response to sort of confront that. During their beta launch in 2010, they received a cease-and-desist letter from the city of San Francisco. And they essentially just ignored this letter. They rebranded, they used to be UberCab, and they just took “Cab” out of their name, so now they’re Uber. And you can see their perspective in their press release in response to this. They say, “UberCab is a first to market cutting edge transportation technology, and it must be recognized that the regulations from both city and state regulatory bodies have not been written with these innovations in mind. As such, we are happy to help educate the regulatory bodies on this new generation of technology and work closely with both agencies to ensure compliance.”

BRIAN KENNY: It’s a little arrogant.

ALEX MACKAY: Yeah, so you can see right there, they’re saying, what we’re operating in is sort of this new technology-based realm and the regulators don’t really understand what’s going on. And so instead of complying with the existing regulations, we’re going to try to push regulations to fit what we’re trying to do.

BRIAN KENNY: The case is pretty epic in terms of it sort of cuts a sweeping arc across the world, looking at the challenges that they faced with each market they entered, and none more interesting I think the New York City, which is obviously an enormous market. Can you talk a little bit about some of the challenges they faced going into New York with the cab industry being as prevalent as it was and is?

ALEX MACKAY: Yeah, absolutely. I mean, I think it’s pretty well known for people who are familiar with New York that there were restrictions on the number of medallions which allowed taxis to operate. So there was a limited number of taxis that could drive around New York City. This restriction had really driven up the value of these medallions to the taxi owners. And if you had the experience of taking taxis in New York City prior to the advent of Uber, what you’d find is that there were some areas where the service was very, very good. Downtown, Midtown Manhattan, you could almost always find a taxi, but there are other parts of the city where it was very difficult at times to find a cab. And when you got in a cab, you weren’t sure that you were always going to be given a fair ride. And so Uber coming in and providing this technology that allowed you to pick up a ride from anywhere and sort of track the route as you’re going on really disrupted this market. Consumers love them. They had a thousand apps signups before they even launched. Kalanick mentioned this in terms of their launch strategy, we have to go here because the consumers really want us here. But immediately, they started getting pushback from the taxicab owners who were threatened by this new mode of transportation. They argued that they should be under the same regulations that the taxis were. And there were a lot of local government officials that were sort of mobilized against Uber as well. De Blasio, the Mayor of New York, wrote opinion articles against Uber, claiming that they were contributing to congestion. There was a lot of concern that maybe they had some safety issues, and the taxi drivers and the owners brought a lawsuit against Uber for evading these regulations. And then later on, and this was the case in many local governments, de Blasio introduced a bill to put additional restrictions on Uber that would make them look a lot more like a traditional taxi operating model, with limited number of licenses and strict requirements for reporting.

BRIAN KENNY: And this is the same scenario that’s going to play out almost with every city that they go into because there is such an established infrastructure for the taxi industry in those places. They have lobbyists. They’re tied into the political networks. In some instances, it was revealed that they’ve been connected with organized crime. So not for the faint of heart, right, trying to expand into some of the biggest cities in the United States.

ALEX MACKAY: Absolutely. Absolutely. And what’s sort of fascinating about the United States is it’s actually a place where a company can engage in this battle over regulation on the ground. And de Blasio writes his opinion article and pushes forward this bill. Uber responds by taking out an ad campaign, over $3 million, opposing these regulations and calling out de Blasio. So again, we sort of have this fascinating example of Uber mobilizing their own lobbyists, their lawyers, but also public advertising to sort of convince the residents of New York City that de Blasio and the regulators that are trying to come down on them are in the wrong.

BRIAN KENNY: Yeah. And at the end of the day, it’s consumers that they’re really making this appeal to, because I guess my question is, are these regulations stifling innovation? And if they are, who pays the ultimate price for that, Uber or the consumer?

ALEX MACKAY: Consumers definitely loved Uber. And I don’t think any of the regulators were trying to stifle innovation. I don’t think they would say that. I think their biggest concern, their primary concern was safety, and a secondary and related concern here was losing regulatory oversight over the transportation sector. So this is a public service that had been fairly tightly regulated for a long time, and there was some concern that what happens when this just becomes almost a free market sector. At the same time, these regulators have the lobbyists from the taxicab industry and other interested parties in their ear trying to convince them that Uber really is like a taxi company and should be regulated, and really emphasizing the safety concerns and other concerns to try to get stricter regulations put on Uber. And part of that may be valid. I think you certainly should be concerned about safety and there are real concerns there, but part of it is simply the strategic game that rivals are going to play between each other. And the taxicab industry sees Uber as a threat. It’s in their best interest to lobby the regulators to come down on Uber.

BRIAN KENNY: And what’s amazing to me is that while all this is playing out, they’re not turning their tails and running. They’re continuing to push forward and expand into other parts of the world. So can you talk a little bit about what it was like trying to go into countries in Latin America, countries in Asia, where the regulations and the regulatory infrastructure is quite different than it is in the US?

ALEX MACKAY: In the case, we have anecdotes, vignettes, one for each continent. And their experience in each continent was actually pretty different. Even within a continent, you’re going to have very different regulatory frameworks for each country. So we sort of pick a few and focus on a few, just to highlight how the experience is very different in different countries. And one thing that’s sort of interesting, in Latin America, we focus on Bogota in Colombia, and what’s sort of interesting there is they launched secretly and they were pretty early on considered to be illegal, but they continue to operate despite the official policy of being illegal in Colombia. And they were able to do that in a way that you may not be able to do it so easily in the United States, just because of the different layers of enforcement and policy considerations that are present in Colombia and not necessarily in the United States. Now, when I talk about the current state of Uber in different countries, this is continually evolving. So they temporarily suspended their operations early in 2020 in Columbia. Now they’re back. This is a continual back and forth game that they’re playing with the regulators in different markets.

BRIAN KENNY: And in a place like Colombia, are they not worried about violence and the potential for violence against their drivers?

ALEX MACKAY: Absolutely. So this is true sort of around the world. I think in certain countries, violence becomes a little bit more of a concern. And what they found in Colombia is they did have more incidents where taxi drivers decided to take things into their own hands and threaten Uber drivers and Uber riders, sometimes with weapons. Another decision Uber had to make that was related to that was whether or not to allow riders to pay in cash. Because in the United States, they’d exclusively used credit cards, but in Latin America and some other countries like India, consumers tended to prefer to use cash to pay, and allowing that sort of opened up this additional risk that Uber didn’t really have a great system in place to protect them from. Because when you go to cash, you’re not able to track every rider quite as easily, and there’s just a bigger chance for fraud or for robbery and that sort of thing popping up.

BRIAN KENNY: Going into Asia was also quite a challenge for them. Can you talk a little bit about some of the challenges they faced, particularly in China?

ALEX MACKAY: They had very different experiences in each country in Asia. China was a unique case that is very fascinating, because when Uber launched there, there were already existing technology-based, you might call them, rideshare companies, that were fairly prominent, Didi and Kuaidi, And these companies later merged to be one company, DiDi, which is huge. It’s on par with Uber in terms of its global presence as a ridesharing company. When Uber launched there, they didn’t fully anticipate all the changes they would have to make to going into a very different environment. In China, besides having established competitors, Google Maps didn’t work, and they sort of relied on that mapping software to do their location services. So they had to completely redo their location services. They also, again, relied on credit cards for payments, and in China, consumers increasingly used apps to do their payments. And this became a little bit of a challenge because the main app that Chinese customers used, they used WeChat and Alipay primarily, they were actually owned by parent companies of the rival ridesharing company. So Uber had to essentially negotiate with its rivals in order to have consumers pay for their ridesharing services. And so here are a few sort of localization issues that you could argue Uber didn’t fully anticipate when they launched. The other thing about competing in China that’s sort of interesting is that Chinese policy regarding competition is very different from policy in the United States and much of Europe. For the most part, there’s not the traditional antitrust view of protecting the consumers first and foremost. That certainly comes into play, but the Chinese government has other objectives, including promoting domestic firms. And so if you think about launching into a company where there’s a large established domestic rival that certainly increases the difficulty of success, because when push comes to shove, the government is likely to come down on the side of your rival, which is the domestic company, and not the foreign entrant.

BRIAN KENNY: Yeah, which is understandable, I guess, to some extent. This sounds exhausting, to be sort of fighting skirmishes on all these fronts in all these different places in the world. How does that affect the morale or tear at the fabric maybe of the culture at a company like Uber, where they’re trying to manage this on a global scale and running into challenges every step of the way?

ALEX MACKAY: It certainly has an effect. I think Uber did a very good job at recruiting teams of people who really wanted to win. And so, if that’s the consistent message you’re sending to your teams, then these challenges may be actually considered somewhat exciting. And so I think by bringing in that sort of person, I think they actually fueled this desire to win in these markets and really kept the momentum going. One of the downsides of this of course is that if you exclusively focus on winning and getting around the existing regulations, there does become this challenge of what’s ethical and what’s not ethical? And in certain business areas, there actually often is a little bit of a gray line. I mean, you can see this outside of ridesharing. It’s a much broader thing to think about, but regulation of pharmaceuticals, regulation of use of new technologies such as drones, often the technology outpaces the regulation by a little bit and there’s this lag in trying to figure out what actually is the right thing to do. I think it’s a fair question whether or not you can disentangle this sort of principle of confrontation that’s so pervasive throughout the company culture when it comes to regulation from this principle confrontation of other ethical issues that are not necessarily business driven, and whether or not it’s easy to maintain that separation. And I think that’s a fair question, certainly worthy for debate. But what I think is important is you can set up a company where you are abiding by ethical issues that are very clear, but you’re still going to face challenges on the legal side when you’re developing a new business in an area with new technology.

BRIAN KENNY: That’s a great insight. I mean, I found myself asking myself as I got through the case, I can’t tell if Uber is the victim or the aggressor in all of this. And I guess the answer is they’re a little bit of both.

ALEX MACKAY: Yeah. I think it’s fair to characterize them as an aggressor, and I think you sort of need to be if you want to succeed and if you want to change the world in a new technology area. In some sense, they’re a victim in that we’re all the victim as consumers and as firms of regulations that are sometimes difficult to adapt in real time to changing market conditions. And there’s a good reason why they are sticky over time, but sometimes that can be very costly. Going back to something we talked about earlier, I think there are hardly any consumers that wanted Uber kicked out of New York City. I think everyone realized this was just so much superior to any other option they had, that they were really willing to fight to keep Uber around in the limited ways they could.

BRIAN KENNY: So let’s go back to the central issue in the case then, which is, how important is it to them, in terms of their global strategy, to have a presence in a place like London? They’re still not profitable by the way, we should point that out, that despite the fact that they are the largest in the space, they haven’t turned the corner to profitability yet. I would imagine London’s kind of important.

ALEX MACKAY: Absolutely. London is a key international city, and a presence there is important for Uber’s overall brand. So many people travel through London, and it’s a real benefit for anyone who travels to be able to use the same service at any city you stop in. At the same time, they’re facing these increasing regulatory pressures from London, and so it’s a real question whether or not, 10 years from now, they look substantially different from the established taxi industry that’s there. And you can kind of see this battle playing out across different markets. As another example, in Ghana. When they entered there, they actually entered with a framework for understanding. They helped build the regulations for ridesharing services in Ghana when they entered. But over time, that evolved to additional restrictions as the existing taxi companies pushed back on them. So I think a key lesson here in all of this is that the regulations that you see at any given point in time aren’t absolutely fixed, for anyone starting a technology-based company, there will be regulations that do get created that affect your business. Stepping outside of transportation, we can see that going on now with the big tech firms and sort of the antitrust investigations they’re are under. And the policymakers in the US and Europe are really trying to evolve the set of regulations to reflect the different businesses that Apple, Facebook, Microsoft, Google are involved in.

BRIAN KENNY: One thing we haven’t touched on, and it’s not touched on in the case obviously because it just sort of started fairly recently, is the pandemic and the implications of the pandemic for the rideshare industry as fewer people find themselves in need of going anywhere. Have you given any thought to that and whether that’s going to have any effect on the regulations?

ALEX MACKAY: It certainly could. Uber is in a somewhat fortunate position, at least if you judge by their market capitalization, with respect to the pandemic. Initially their stocks took a pretty big hit, but rebounded pretty quickly, and part of this is because the primary part of their business is the transportation through Uber X, but they do also offer the delivery services through Uber Eats, and that business has really picked up during this pandemic. There’s certainly a mix of views about the future, but I think most people do believe that at some point we’ll get back to business as usual, at least for Uber services, when we come up with a vaccine. I think most people anticipate that they’ll be resuming use of Uber once it becomes safe to do so. And I think, to be frank, a lot of people already have resumed using Uber, especially people who don’t have cars or who see it as a valuable alternative or a safer alternative to public transit.

BRIAN KENNY: Yeah, that’s a really good point. And the Uber Eats thing is interesting as another example of how it’s important for businesses to re-imagine the business that they’re in because that, in many ways, may be helping them through a really tough patch here. This has been a really interesting conversation, Alex, I want to ask you one final question, which is, as the students are packing up to leave class, what’s the one thing you want them to take away from the case?

ALEX MACKAY: So I would hope the students take away the importance of regulation in business strategy. And I think the case of Uber really highlights that. And if you look at the conversation around Uber I’d say for the first 10 years of their existence, it was essentially around the superiority of their technology and not so much how they handled regulation. If you think back to the cease-and-desist letter that San Francisco issued in 2010, if Uber had simply stopped operations then, we wouldn’t have the ridesharing world that we have today. So their strategy of principle confrontation with respect to regulation was really essential for their future growth. Again, this does raise important ethical considerations as you’re operating in a legal gray area, but it’s certainly an essential part of strategy.

BRIAN KENNY: Alex, thanks so much for joining us on Cold Call today. It’s been great talking to you.

ALEX MACKAY: Thank you so much, Brian.

BRIAN KENNY: If you enjoy Cold Call, you might like other podcasts on the HBR Presents Network. Whether you’re looking for advice on navigating your career, you want the latest thinking in business and management, or you just want to hear what’s on the minds of Harvard Business School professors, the HBR Presents Network has a podcast for you. Find them on Apple podcasts or wherever you listen. I’m your host, Brian Kenny, and you’ve been listening to Cold Call , an official podcast of Harvard Business School on the HBR Presents Network.

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How Uber Transports Their CRM Data from Point A to Point B with RampID

• Jun 28, 2018
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Uber’s all about getting their users from point A to point B. So what gets Uber’s data from their CRM database into the digital space? Why, LiveRamp of course! Tesäen Chavis, DMP manager at Uber, uses RampID to connect Uber’s data from their CRM to pseudonymous channels so they can test user segments and find out if they’re targeting based on the right attributes.

“RampID has been able to help us tie these identities together and effectively manage our campaigns in a way that we’re saving dollars as they run,” said Tesäen. Watch the video or read the transcript below.

Don’t feel like watching the video? Read the full transcript here:

My name is Tesäen Chavis. I am the DMP Manager at Uber. Uber is a leading technology app. We provide a service that enables people to get rides. We’re a mode of transportation that takes a person from point A to point B.

I manage our tokenized data through our DMP. In short, I collect all of Uber’s data. We unify that data into a single ID, in this case it’s AAMID [Adobe Audience Manager ID], and then we activate that across all of our media campaigns.

We utilize LiveRamp as our CRM encryption. When it comes to Uber’s CRM data, we are able to segment users into specific life-cycle stages. LiveRamp is able to segment and anonymize those life- cycle stages so we can apply the same logic to our media campaigns.

Via LiveRamp we’re able to take directly identifiable personal data and tie that to several IDs, whether that be device IDs or cookie IDs. Then we can tie those identities together. Why do we want to do that? We need to have an understanding of who these people are across all of their devices so we can effectively target them and manage things like frequency capping. We can suppress them if we are over targeting them. LiveRamp has been able to help us tie these identities together and effectively manage our campaigns in a way that we’re saving dollars as they run.

Our LiveRamp account team is pretty incredible. They’re able to answer any questions that we have, whether it pertains to identity resolution , or personalization , or even building out our own version of a CDIM graph. They’re able to understand our business challenges, and they appropriately apply solutions to those challenges in a meaningful way. It’s not just an upsell, it’s, “this is why you need to consider this, and this is where it will get you a year or two from now.”

As we test user segments to figure out if we have viable attributes to go after different audiences, we’ve been utilizing LiveRamp to make that connection from CRM to pseudonymous channels. We gain these insights via the performance metrics that [tell us whether] this test group is converting or there’s some sort of incrementally in terms of whether or not they’re taking additional trips. From there, we can pretty much scale up that effort into a full-fledged campaign.

Once we actually gain those insights, whether it’s demographic-based or behavioral-based, we’re able to utilize LiveRamp’s Data Marketplace in order to gain second-party segments or third-party data in order to expand our reach. That’s pretty integral to how we approach these campaigns as well.

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The magic behind Uber’s data-driven success

Uber, the ride-hailing giant, is a household name worldwide. We all recognize it as the platform that connects riders with drivers for hassle-free transportation. But what most people don’t realize is that behind the scenes, Uber is not just a transportation service; it’s a data and analytics powerhouse. Every day, millions of riders use the Uber app, unwittingly contributing to a complex web of data-driven decisions. This blog takes you on a journey into the world of Uber’s analytics and the critical role that Presto, the open source SQL query engine, plays in driving their success.

Uber’s DNA as an analytics company

At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B. With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price. But the simplicity ends there. Every transaction, every cent matters. A ten-cent difference in each transaction translates to a staggering $657 million annually. Uber’s prowess as a transportation, logistics and analytics company hinges on their ability to leverage data effectively.

The pursuit of hyperscale analytics

The scale of Uber’s analytical endeavor requires careful selection of data platforms with high regard for limitless analytical processing. Consider the magnitude of Uber’s footprint. 1 The company operates in more than 10,000 cities with more than 18 million trips per day. To maintain analytical superiority, Uber keeps 256 petabytes of data in store and processes 35 petabytes of data every day. They support 12,000 monthly active users of analytics running more than 500,000 queries every single day.

To power this mammoth analytical undertaking, Uber chose the open source Presto distributed query engine. Teams at Facebook developed Presto to handle high numbers of concurrent queries on petabytes of data and designed it to scale up to exabytes of data. Presto was able to achieve this level of scalability by completely separating analytical compute from data storage. This allowed them to focus on SQL-based query optimization to the nth degree.

What is Presto?

Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes. It excels in scalability and supports a wide range of analytical use cases. Presto’s cost-based query optimizer, dynamic filtering and extensibility through user-defined functions make it a versatile tool in Uber’s analytics arsenal. To achieve maximum scalability and support a broad range of analytical use cases, Presto separates analytical processing from data storage. When a query is constructed, it passes through a cost-based optimizer, then data is accessed through connectors, cached for performance and analyzed across a series of servers in a cluster. Because of its distributed nature, Presto scales for petabytes and exabytes of data.

The evolution of Presto at Uber

Beginning of a data analytics journey.

Uber began their analytical journey with a traditional analytical database platform at the core of their analytics. However, as their business grew, so did the amount of data they needed to process and the number of insight-driven decisions they needed to make. The cost and constraints of traditional analytics soon reached their limit, forcing Uber to look elsewhere for a solution.

Uber understood that digital superiority required the capture of all their transactional data, not just a sampling. They stood up a file-based data lake alongside their analytical database. While this side-by-side strategy enabled data capture, they quickly discovered that the data lake worked well for long-running queries, but it was not fast enough to support the near-real time engagement necessary to maintain a competitive advantage.

To address their performance needs, Uber chose Presto because of its ability, as a distributed platform, to scale in linear fashion and because of its commitment to ANSI-SQL, the lingua franca of analytical processing. They set up a couple of clusters and began processing queries at a much faster speed than anything they had experienced with Apache Hive, a distributed data warehouse system, on their data lake.

Continued high growth

As the use of Presto continued to grow, Uber joined the Presto Foundation, the neutral governing body behind the Presto open source project, as a founding member alongside Facebook. Their initial contributions were based on their need for growth and scalability. Uber focused on contributing to several key areas within Presto:

Automation: To support growing usage, the Uber team went to work on automating cluster management to make it simple to keep up and running. Automation enabled Uber to grow to their current state with more than 256 petabytes of data, 3,000 nodes and 12 clusters. They also put process automation in place to quickly set up and take down clusters.

Workload Management: Because different kinds of queries have different requirements, Uber made sure that traffic is well-isolated. This enables them to batch queries based on speed or accuracy. They have even created subcategories for a more granular approach to workload management.

Because much of the work done on their data lake is exploratory in nature, many users want to execute untested queries on petabytes of data. Large, untested workloads run the risk of hogging all the resources. In some cases, the queries run out of memory and do not complete.

To address this challenge, Uber created and maintains sample versions of datasets. If they know a certain user is doing exploratory work, they simply route them to the sampled datasets. This way, the queries run much faster. There may be inaccuracy because of sampling, but it allows users to discover new viewpoints within the data. If the exploratory work needs to move on to testing and production, they can plan appropriately.

Security: Uber adapted Presto to take users’ credentials and pass them down to the storage layer, specifying the precise data to which each user has access permissions. As Uber has done with many of its additions to Presto, they contributed their security upgrades back to the open source Presto project.

The technical value of Presto at Uber

Analyzing complex data types with presto.

As a digital native company, Uber continues to expand its use cases for Presto. For traditional analytics, they are bringing data discipline to their use of Presto. They ingest data in snapshots from operational systems. It lands as raw data in HDFS. Next, they build model data sets out of the snapshots, cleanse and deduplicate the data, and prepare it for analysis as Parquet files.

For more complex data types, Uber uses Presto’s complex SQL features and functions, especially when dealing with nested or repeated data, time-series data or data types like maps, arrays, structs and JSON. Presto also applies dynamic filtering that can significantly improve the performance of queries with selective joins by avoiding reading data that would be filtered by join conditions. For example, a parquet file can store data as BLOBS within a column. Uber users can run a Presto query that extracts a JSON file and filters out the data specified by the query. The caveat is that doing this defeats the purpose of the columnar state of a JSON file. It is a quick way to do the analysis, but it does sacrifice some performance.

Extending the analytical capabilities and use cases of Presto

To extend the analytical capabilities of Presto, Uber uses many out-of-the-box functions provided with the open source software. Presto provides a long list of functions, operators, and expressions as part of its open source offering, including standard functions, maps, arrays, mathematical, and statistical functions. In addition, Presto also makes it easy for Uber to define their own functions. For example, tied closely to their digital business, Uber has created their own geospatial functions.

Uber chose Presto for the flexibility it provides with compute separated from data storage. As a result, they continue to expand their use cases to include ETL, data science , data exploration, online analytical processing (OLAP), data lake analytics and federated queries.

Pushing the real-time boundaries of Presto

Uber also upgraded Presto to support real-time queries and to run a single query across data in motion and data at rest. To support very low latency use cases, Uber runs Presto as a microservice on their infrastructure platform and moves transaction data from Kafka into Apache Pinot, a real-time distributed OLAP data store, used to deliver scalable, real-time analytics.

According to the Apache Pinot website, “Pinot is a distributed and scalable OLAP (Online Analytical Processing) datastore, which is designed to answer OLAP queries with low latency. It can ingest data from offline batch data sources (such as Hadoop and flat files) as well as online data sources (such as Kafka). Pinot is designed to scale horizontally, so that it can handle large amounts of data. It also provides features like indexing and caching.”

This combination supports a high volume of low-latency queries. For example, Uber has created a dashboard called Restaurant Manager in which restaurant owners can look at orders in real time as they are coming into their restaurants. Uber has made the Presto query engine connect to real-time databases.

To summarize, here are some of the key differentiators of Presto that have helped Uber:

Speed and Scalability: Presto’s ability to handle massive amounts of data and process queries at lightning speed has accelerated Uber’s analytics capabilities. This speed is essential in a fast-paced industry where real-time decision-making is paramount.

Self-Service Analytics: Presto has democratized data access at Uber, allowing data scientists, analysts and business users to run their queries without relying heavily on engineering teams. This self-service analytics approach has improved agility and decision-making across the organization.

Data Exploration and Innovation: The flexibility of Presto has encouraged data exploration and experimentation at Uber. Data professionals can easily test hypotheses and gain insights from large and diverse datasets, leading to continuous innovation and service improvement.

Operational Efficiency: Presto has played a crucial role in optimizing Uber’s operations. From route optimization to driver allocation, the ability to analyze data quickly and accurately has led to cost savings and improved user experiences.

Federated Data Access: Presto’s support for federated queries has simplified data access across Uber’s various data sources, making it easier to harness insights from multiple data stores, whether on-premises or in the cloud.

Real-Time Analytics: Uber’s integration of Presto with real-time data stores like Apache Pinot has enabled the company to provide real-time analytics to users, enhancing their ability to monitor and respond to changing conditions rapidly.

Community Contribution: Uber’s active participation in the Presto open source community has not only benefited their own use cases but has also contributed to the broader development of Presto as a powerful analytical tool for organizations worldwide.

The power of Presto in Uber’s data-driven journey

Today, Uber relies on Presto to power some impressive metrics. From their latest Presto presentation in August 2023, here’s what they shared:

Uber’s success as a data-driven company is no accident. It’s the result of a deliberate strategy to leverage cutting-edge technologies like Presto to unlock the insights hidden in vast volumes of data. Presto has become an integral part of Uber’s data ecosystem, enabling the company to process petabytes of data, support diverse analytical use cases, and make informed decisions at an unprecedented scale.

Getting started with Presto

If you’re new to Presto and want to check it out, we recommend this Getting Started page where you can try it out.

Alternatively, if you’re ready to get started with Presto in production you can check out IBM watsonx.data , a Presto-based open data lakehouse. Watsonx.data is a fit-for-purpose data store, built on an open lakehouse architecture, supported by querying, governance and open data formats to access and share data.

1 Uber. EMA Technical Case Study, sponsored by Ahana. Enterprise Management Associates (EMA). 2023.

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Strategies Driving Uber’s Successful Journey: A Case Study

by PanGrow | Nov 6, 2023

Uber, the global leader in ride-hailing, is a universally recognized brand. We all know it as the platform that seamlessly links passengers with drivers for convenient transportation. However, what often escapes notice is that beneath the surface, Uber is more than just a transportation facilitator; it’s a formidable force in data and analytics. On a daily basis, countless riders engage with the Uber app, unwittingly feeding into a sophisticated network of data-powered insights and choices.

Uber stands as a dominant force in the transportation and delivery industry, boasting operations in over 72 countries and catering to more than 110 million active monthly users.

The remarkable triumph of Uber has spurred numerous entrepreneurs to venture into the realm of ride-hailing and delivery services. Let us get familiarized with Uber’s marketing strategies through this guide.

Revenue Model & Pricing Strategy

Uber makes money in a few different ways. Its a commission based system, where it takes a percentage of the total fare. There are various elements of its revenue model.

First, they take a part of the money you pay for your ride. This is called a commission, and it’s usually about 20-30% of the total cost. Sometimes, when a lot of people need rides, Uber might charge a bit more. This is called surge pricing. It helps encourage more drivers to be available when it’s really busy, and Uber makes extra money from it.

They also have other fees, like a booking fee or an airport fee. These are extra charges for specific situations. Some people pay a subscription fee for a service called Uber Pass. It gives them discounts on rides and other perks, and Uber makes money from these subscriptions.

Uber does more than just rides. They also deliver food (Uber Eats) and help ship goods (Uber Freight). They make money from fees they charge restaurants, riders, and other partners for these services. Businesses can pay Uber to advertise on their app, which brings in more money.

So, in short, Uber mainly makes money by taking a piece of the fare from each ride. They also have other ways of earning, like subscriptions, fees, and advertising. They’ve expanded into different services to bring in even more money.

Navigating Marketing Strategies

Uber, a trailblazer in the ride-sharing industry, owes much of its success to a well-crafted marketing strategy.

Customer at the Center Stage

A cornerstone of Uber’s strategy is its unwavering focus on the user. The company places a premium on delivering a seamless, hassle-free experience. This commitment is evident in their user-friendly mobile app and straightforward booking process. By prioritizing customer satisfaction, Uber has built a loyal and trusting customer base.

Dynamic Pricing Feature

Another standout tactic is Uber’s dynamic pricing, known as surge pricing. This strategy, allows Uber to adjust fares based on demand and supply. While it can be a topic of debate, surge pricing effectively balances ride availability during peak times, ensuring a reliable service.

Referral Program: A Win For All

Uber’s referral program is a brilliant move in customer acquisition. By encouraging existing users to refer friends and family, the company taps into the power of word-of-mouth marketing. This not only brings in new customers but also fosters a sense of community and trust among users. Incentives like discounts on future rides create a win-win situation, driving platform growth.

Data-Driven Approach

Data is a powerful ally for Uber. The company leverages analytics to gain insights into customer behavior and preferences. This data-driven approach informs decisions on pricing, routes, and service expansion, keeping Uber attuned to evolving customer needs.

Enhancing Experience

In addition to customer-focused strategies, Uber places significant emphasis on driver satisfaction. Recognizing drivers as integral to the service, Uber implements initiatives to enhance their experience. Offering flexible earning opportunities, access to support, and performance incentives are among the ways Uber keeps its driver base motivated and engaged.

Multichannel Marketing

Uber’s marketing efforts span various channels. The company invests heavily in digital marketing, utilizing social media, email campaigns, and targeted ads to engage with users. This multi-channel approach ensures Uber maintains a strong online presence and remains top-of-mind.

In summary, Uber’s success hinges on its dedication to user satisfaction, data-informed decision-making, and a comprehensive approach to the ride-sharing ecosystem. By focusing on user experience, implementing dynamic pricing, leveraging referral programs, and using data analytics, Uber has established itself as a dominant force in global transportation.

Additionally, the company’s attention to driver satisfaction and robust digital marketing efforts further contribute to its triumph.

Brand Building & Customer Loyalty

A key element of Uber’s success lies in its strategic use of social media platforms like Instagram, Facebook, and YouTube to connect with a diverse user base, including passengers, drivers, food enthusiasts, and partners. This concerted effort is central to building a strong brand identity and fostering lasting customer loyalty.

Through engaging content on platforms like YouTube, Uber shares driver stories, customer feedback, road safety tips, and updates on initiatives. This content not only informs and educates but also reinforces the brand’s commitment to safety, innovation, and community.

Uber excels at customer service on social media, promptly addressing feedback, suggestions, and concerns. With a dedicated customer service account, the company builds trust and reliability among its users.

Campaigns like the #WhyIRide initiative in 2016, encouraging users to share their motivations for choosing Uber on social media, have been highly successful in generating organic word-of-mouth marketing and user-generated content. This has significantly increased brand awareness and customer engagement.

Uber also strategically partners with influential figures, celebrities, and organizations that align with its values. Notable collaborations, like pledging to create one million job opportunities for women as drivers in partnership with UN Women in 2015, underscore the brand’s commitment to inclusivity and empowerment, garnering widespread recognition and praise.

Challenges and Future Prospects

Uber serves as a pivotal platform connecting drivers and passengers across cities globally. The company’s forward trajectory appears promising, owing to its astute consideration of critical factors such as regulatory dynamics, fierce competition in the transportation and delivery sector, ongoing innovation in products and services, and unwavering commitment to customer satisfaction.

This success has piqued the interest of entrepreneurs, leading to an uptick in the development of Uber-like clone apps for taxis and delivery services, potentially expanding to incorporate various modes of transportation like bikes, motorbikes, trains, scooters, buses, and even futuristic prospects like flying taxis. However, adherence to local laws and regulations is paramount in implementing Uber’s marketing strategies, as stringent rules governing safety, labor, and taxation may influence the company’s profitability and growth.

In the face of its accomplishments, Uber grapples with a set of formidable challenges that could impact its operations, financial performance, and overall prosperity. Foremost among these are regulatory hurdles. Many cities and countries contend that Uber’s business model clashes with existing legal frameworks, resulting in bans and limitations on its operations in certain locales.

Legal entanglements also pose a significant obstacle. Disputes with drivers seeking reclassification as employees rather than independent contractors, along with allegations of inadequate safety measures against harassment and assault, have landed Uber in the courtroom.

Furthermore, Uber contends with fierce competition in a cutthroat industry, contending with rivals like Lyft and Didi Chuxing, some of whom boast strong affiliations with local authorities and transportation entities.

Safety constitutes a paramount concern for Uber, encompassing both rider and driver well-being. The company has faced scrutiny for perceived inadequacies in safeguarding its stakeholders, prompting substantial policy adjustments to address these anxieties.

Finally, despite its lofty valuation, Uber’s profitability remains elusive. Pressured by investors to demonstrate sustainable financial viability, the company has undertaken substantial modifications to its business model and cost structure in a bid to achieve profitability. Balancing these challenges against its well-established strengths, Uber’s trajectory in the transportation and delivery sector will hinge on its ability to navigate these hurdles and capitalize on its innovative and customer-centric approach.

Lessons Learnt

Uber employs a distinctive marketing approach to cultivate a loyal user community. By offering complimentary rides, discounted fares, and referral perks, the company effectively lures in customers. The exceptional quality of the ride experience fosters a desire for repeated use, ultimately creating a habitual and revenue-generating pattern for the company.

To ingrain this novel mode of transportation in the public consciousness, Uber has made substantial investments in marketing efforts, generously providing free rides on a global scale. Moreover, the company leverages its competitive pricing structure as a significant selling point, further solidifying its appeal.

If you are interested in knowing more about digital marketing services that can help your business substantially, contact us at [email protected] or visit our website today!

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12 Successful CRM Implementation Case Studies to Learn From

CRM implementation can seem like a monumental task to complete. From knowing which CRM to choose, to understanding how to fit it in with the rest of your sales stack , there’s a lot involved from pricing to convincing decision-makers to making sure it works well from the start.

If you’re looking for CRM implementation case studies to give you ideas and confidence to get started, then look no further.

12 CRM Case Studies

Want to get this done right (the first time)? Learn from the CRM case studies of companies that implemented a new CRM successfully to improve the customer experience, drive customer engagement , and increase revenue.

1. How Customer.io Uses Automated Handoffs to Enable Smarter Sales

Company: Customer.io

Customer.io is an established martech provider that needed a CRM to work better with both an inbound and outbound sales process. Plus, they needed it to fit well with their current tool stack and give them automated workflows.

This case study interview with Alex Patton, Director of Marketing and operations at Customer.io, digs deeper into the technical setup the company uses with its CRM platform and how that process maximizes the team’s time and productivity.

2. 6 Tips for Assessing Your CRM + Optimizing Workflow—from a Revenue Coach

Company/Organization: High Kick Sales

Kyle Stremme’s consulting firm, High Kick Sales, enables sales teams to create an optimized process and tech stack. This case study explores the insights Kyle gained from helping B2B and B2C companies develop their CRM systems and processes, plus details on how he helps managers analyze their current CRM and decide on a better system.

3. Implementing Customer Relationship Management (CRM) in Hotel Industry from an Organizational Culture Perspective

Company: Anonymous UK hotel chain

This study, done by the International Journal of Contemporary Hospitality Management, examined a hotel chain in the UK as it implemented a new CRM, noting what worked and what didn't about its implementation process.

They administered a questionnaire to 346 hotel chain managers and found that organizational culture readiness was one of the most determining factors in the success of a CRM implementation.

4. Choosing and Implementing a CRM for Small Business

Company: Bean Ninjas

Bean Ninjas is an accounting firm for eCommerce businesses. Their tech stack was dissonant and unconnected, and their ‘CRM’ (actually a project management tool) didn’t even have email built-in. The lack of functionality was impacting their business.

Their self-written case study goes through choosing the right CRM, implementing the system into a more optimized sales workflow , technical integrations, and the end results.

5. How AAXIS Digital is Saving an Estimated $250,000 by Switching from Salesforce to the HubSpot CRM Platform

Company: AAXIS

This CRM implementation case study focuses on how an enterprise company migrated from one extensive CRM to another, saving them lots of money on a system they weren’t using to the full.

The case study explores how they chose their new CRM and their accomplishments with it, including increasing marketing automation and better aligning sales and marketing. For specific Salesforce resources, check out our list of CRM implementation resources .

6. Replacing HubSpot with Close: Scaling Trufan in a CRM Reps Love

Company: Trufan

Trufan (now Surf for Brands) is a fast-growing SaaS startup with a tech-savvy target market. So, they needed a CRM that could move quickly alongside their team, helping them build well-constructed automation that could scale as they grew.

This CRM implementation case study shows how a wrong decision slowed their progress and how a new solution helped them scale faster.

7. A Successful CRM Implementation Project in a Service Company

Company: Anonymous service company from Slovenia

This academic case study by Piskar Franka and Armand Faganel examines the process a service company in Slovenia followed alongside CRM consultants to implement a new solution.

They concluded that a proper CRM implementation can improve customer relationships , achieve greater information sharing between employees, and lead to better strategic decisions. This is mostly interesting for historical purposes, as it gives some insight into the complexity involved in implementing a CRM into a larger company in 2007.

8. Hownd Cut CRM Costs by 80 percent in 2 Weeks—While Saving SMBs During COVID

Company: Hownd

Hownd works with brick-and-mortar businesses to get more foot traffic, and their mission since the start of the pandemic is to help SMBs get back on their feet and recover. They needed a CRM that would help them cut their costs to help others and help them move quickly to fill the needs of their customers.

This case study/COVID success story shows how Hownd found the right CRM for their business, cut costs, streamlined their process, and continues to help SMBs survive through hard times.

9. The Ultimate Team Effort: How the Close Sales Team Joins Forces to Build More Solid Deals

Company: Close

This unique case study is the story of our CRM software company and how we’ve implemented our CRM tool into our sales stack. It digs into the nitty-gritty of technical setups and integrations, API, and how it all works together for a smooth, profitable process.

10. Switching to HubSpot Adds up for Casio

Company: Casio

This enterprise CRM implementation case study shows how consumer electronics company Casio switched from a custom-built CRM to one that was more inclusive for their marketing and sales teams. It shows how they updated their inbound marketing process and increased their new customer sales by 26 percent.

11. The Unique Sales Process ResQ Club Uses to Power It's Mission to Zero Food Waste

Company: ResQ Club

ResQ Club, a Finnish company on a mission to make zero food waste a reality, needed a CRM solution that would help them track customers and partners and scale quickly.

This case study shows how they used Close to build their own custom processes with Custom Fields , email sequences that are personalized to different European cities, and Smart Views that keep sales reps focused on the right deals.

12. Strategic Issues in Customer Relationship Management (CRM) Implementation

Company: Anonymous UK manufacturing company

This paper from 2003 by Christopher Bull from the Department of Business Information Technology at Manchester Metropolitan University Business School discusses the effects of a strategic customer relationship management process and how it affected this manufacturing company.

The results of this study highlighted that CRM implementations frequently failed. It also referenced a study of 202 CRM projects, which concluded that only 30.7 percent of organizations said the CRM implementation improved how they sell to and service customers.

Testimonials that Highlight the Benefits of CRM Implementation

What kind of benefits should you expect once you’ve implemented a new CRM ? It depends on your company and current pain points. If you are considering switching to a new CRM or implementing one for the first time, here’s what real CRM users say:

1. Nick Parker, Founder at FTOCloud

“With Close, we're able to keep track of hundreds of deals and clients over multiple months while simultaneously unifying our team's communication.”

2. Tim Griffin, Founder & CEO at Cloosiv

“ We didn’t start getting traction until we started using Close. I don’t know if the company would still be here if we hadn’t implemented it.”

Read the whole story here.

3. Maryl Johnston, CEO at Bean Ninjas

“The real benefit of Close is less about sales admin time and more about closing more deals. Because Close makes it very easy to stay in touch with customers and allows Sales to manage their pipeline without needing a sales admin, we can now go into Close and see all the leads in a broad view.”

‎4. Aimee Creighton, Sales Administrator at Bean Ninjas

“ The biggest win for me is the cut-down in labor time of setting up leads in our task management system (not designed for lead management) and ensuring all fields are filled out. It significantly reduced the time-intensive manual process of documenting leads. I feel like Close has completely cut that down, and everything is right there from the dashboard. I think it’s been worth the investment.”

5. Monika Tudja, Business Development Manager at Now Technologies

“ I can't imagine my work-life without Close - I've been using it at my previous company and I 'demanded' implementing it on my first day at the current one. I'm useless without Close. Seriously thinking about getting an account for my personal life.”

6. Sara Archer, Director of Sales and Marketing

“ Since we've started using Close, we've QUADRUPLED our average revenue per user.”

Read how they did it here.

7. Sarah Haselkorn, Head of Sales at MakeSpace

“ You guys [at Close] have been a HUGE part of our growth so far, and with your support I have so much confidence that our sales team is set up to scale.”

8. Duncan Burns, VeggiDome

“I am able to stay on top of my outreach, correspondence, and follow-up seamlessly AND relax enough to do a better job, knowing that I'm not missing a beat!”

9. Michael Grady, Lazarus

“ This is a CRM that is all about focus with no bloat which is exactly what inside sales needs.”

10. Aubrey Lim, ThreeTrees

“My first time using a CRM. 8 months in and it's frictionless to use. My favorite features: being able to pull up colleagues' emails to a particular lead, bulk-uploading contacts, email templates.”

‎11. Timothy Corey, Director of Sales at Commonwealth Joe

“Close allows us to see where we should spend our time and effort. We can look at our sales for the same quarter last year and know what worked well and what didn’t -- this allows me to know where to put my energy, on what companies, and in what markets.”

Ready to Write Your Own CRM Implementation Success Story?

The right CRM helps you easily access customer information, track contacts, qualify leads, improve conversion rates, and more. If you're ready to implement a CRM, we can help.

For a successful CRM implementation , you need a clear plan to follow. That’s why we’ve given you the right resources to make a better decision. Get our CRM implementation guide here:

ACCESS OUR CRM IMPLEMENTATION GUIDE →

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Uber in 2024: From Industry Disruption to Creating Value For All Stakeholders

Dara Khosrowshahi became the CEO of Uber in August 2017, following internal turbulence and serious headwinds related to the company’s governance and reputation. Five short years later, Uber was clearly back on course, building on the success of its technology platform to reach 150 million monthly active platform users—and a market cap of $125 billion by the end of 2023.

This case study traces the remarkable transformation of Uber from its early innovation as a ride-hailing pioneer in a handful of cities, to the global expansion of Uber mobility services that required close attention to local operational and regulatory practices, to solving the complex technical challenges to drive Uber’s food delivery services forward. Interviews with Uber leadership reveals the strategic approach to work on the engineering, data science, product management, and product design challenges involved in building and maintaining a customer-friendly app and create an optimized user experience—and scale this on a global basis while factoring in local conditions and practices.

Key to this success was a culture reboot within Uber, and a renewed focus on collaboration and value creation for all stakeholders. The company that had found its initial footing by disrupting and transforming the taxi industry, more than a decade earlier, now faced a future where artificial intelligence and autonomous vehicles would likely disrupt the mobility sector once again—but Uber was preparing intensively for what the future might bring.

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Falling in love is addictive. Those of us who have ever fallen in love find it hard to explain how it happened and why. It is undoubtedly one of the best feelings there is, and yet it is difficult to explain rationally. Many of us spend a large part of our lives looking for love,...

How Uber delivers an excellent customer experience

Falling in love is addictive.

Those of us who have ever fallen in love find it hard to explain how it happened and why.

It is undoubtedly one of the best feelings there is, and yet it is difficult to explain rationally.

Many of us spend a large part of our lives looking for love, falling in love, trying our best to stay in love and to be close to the people we love.

We love not only people; we love cars, some love places, others love food or films. People can love a multitude of things.

But wait, why are we talking about love in an article dedicated to the customer experience?

Quite simply because the best customer experiences are very similar to love. They are extremely tough to design, but when you get it right, you can make your customers love you for life . And the reason why it is so challenging to create an exceptional customer experience is very simple.

Experiences are all about human interactions. There are scientific explanations, but above all, it’s about emotions.

And as we can see in Maslow’s triangle, emotional needs transcend physical needs.

Customer experience has become so important in recent times that several firms of analysts regularly publish indices. The Forrester’s US Customer Experience Index covers a significant proportion of industries such as airlines, hotels, insurance, etc.

But what happens if you’re not a service company, but rather an organization like AirBnB, Uber or WhatsApp? Who does the customer talk to when WhatsApp doesn’t work or when the Uber App is not responding?

How does Uber deliver an excellent customer experience?

Welcome to the world of product experience – a subset of customer experience, highly appreciated by design specialists, and of immense importance to organizations that cannot afford (or do not want) to spend a lot on marketing or customer service.

Product experience is what the consumer remembers about the product through the various stages of interaction with it (purchase, first use, current use, abandonment, etc.).

From the experience point of view, the three dimensions within which a product must perform are:

• the functional,
• the sensual,
• and the emotional.

These aspects are independent of the economic dimensions of the product such as the cost, price or efficiency of production (which are equally important attributes).

1 — Functional experience

The question that any product must answer is: what is the basic functional human need the product is intended to meet?

Is it a need for transport, for accommodation, for knowledge or something else?

We often speak of the functional value created by the product.

2 — Sensual experience

Nobody loves unattractive cars irrespective of the speed they can achieve. Beauty is a matter of taste, but things must be pleasant to see and hear.

Some even believe that a smell can evoke an experience (aromatherapy in hotels, spas or restaurants is a good example). As a matter of fact, people rarely judge a book by its cover.

So make sure you tell a great story that solves a big problem, but be sure that it is beautiful and appeals to the senses.

3 — Emotional experience

What emotional response does your product evoke in its user?

A sense of power, well-being, belonging, attachment, aversion, pleasure or pride?

Taking into account the wide variety of customers you want to reach in a B2C universe, there is no single formula.

You must invest time in studying your customers’ reactions within the environment in which they are likely to use your product.

Providing a Memorable Customer Experience

This is the cherry on the cake, the Holy Grail, the proof that your product experience is effective.

Does your product create a memorable or unforgettable customer experience based on the three dimensions above ?

To answer this question, create a questionnaire made up of ratings designed to assess the three dimensions of your product (functional, sensual and emotional experience) in real terms and determine the memorability of your product experience.

This type of questionnaire will provide you with an excellent means of quantitative measurement of the product experience, allowing you to estimate how successful it is likely to be with your target market.

So, while mapping the customer experience can be a good way to anticipate the contact points and the reactions of your consumers to your services throughout the product life cycle, a product experience measurement system can help you to improve the experience and therefore the attractiveness of your product to your customers by quantifying the different aspects of the experience.

In a nutshell, an exceptional product experience can evoke genuine loyalty in your customers.

Why does Uber deliver the best product experience?

To demonstrate why Uber provides a remarkable product (and customer) experience, I suggest we simply compare the experience offered by a traditional taxi service and that provided by Uber.

Like the booksellers or the travel agencies that went before them, the taxi industry hasn’t succeeded in breaking new ground in its approach to customers.

Instead of investing in improvements that could have removed some of the irritations that their customers experience, they have almost always chosen not to evolve and to stay as they were .

Meanwhile, Uber has arrived…

The start-up has invested heavily in the sticking points of the customer experience so as to disrupt the taxi market.

Fundamental principles of great Customer Experience

Here are the principles they apply and some concrete examples, always in comparison with the traditional taxi services:

1 — Remove the irritations

No more need to stand waving on the pavement, no more long waits, lower charges and clearer pricing, and an end to grumpy drivers.

Customers expect, more than ever before, simple and quick processes . If you don’t take account of this, you will quickly be replaced.

2 — Offer transparency

Your Uber driver is called Julien. He is driving a C-Class Mercedes and will arrive in 2 minutes.

The technology to keep customers informed in real time exists and should be made use of whenever possible.

Whether it is tracking a UPS shipment or the number of steps required to make an online purchase, knowing when and why an order will be on time or late (or any other relevant information available about a product or service) allows you to meet the expectations of your customers more effectively .

3 — Use customer feedback as though it were currency

How would you evaluate your experience with your Uber driver? Why?

Give customers and employees alike the chance to be heard and make good use of the feedback.

In the case of Uber, feedback is a fundamental element in the experience which ensures that the best (customers and employees) get the best service .

4 — Establish strong relationships with people

Thank you for the journey, see you again soon!

Customers are human beings, and the companies that serve them are made up of human beings too. Making things simple and transparent doesn’t mean sacrificing the human factor.

In fact, technology makes it much easier to put the emphasis on encouraging human contact. How do you ensure that this is VIP contact? This is where feedback becomes vital !

And you, what do you do to make sure your customers love you and feel loved? Which companies inspire you the most?

15+ questions to ask your customers about their needs and expectations

Qualify customer expectations before, during and after the purchase, or for a new cycle !

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A CRM (customer relationship management) is, at its core, a database of customer data. CRM systems are increasingly sophisticated, and allow you to organise this data to provide a myriad of customer service, marketing, and sales solutions. A CRM system means you can run your business operations from one place.  Businesses of all sizes can benefit from a CRM as well as businesses in any industry. Some providers offer niche systems that fit into one industry, while others are flexible and can be customised to suit various business sizes and industries. 

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CRM is typically charged on a per user, per month basis. This fee can be anywhere from as low as £10 per user, per month, to as high as £240 per user, per month.

Most CRM systems are cloud-based which means that your business’ data (files, contacts, documents, the lot) is stored ‘in the cloud’, hosted on servers operated by the CRM provider, rather than on your own premises.

There’s a couple of benefits to this, including both security and convenience – who wants to have a load of expensive equipment taking up valuable office space? The main advantage of cloud-based CRM, though, is that it facilitates remote working.

With cloud-based CRM , information updates in real-time – enabling collaboration across time zones, and bringing together teams situated thousands of kilometres apart. Plus, there’s no expensive hardware to maintain or install – cloud-based CRM is accessible entirely from your web browser.

Yes. CRM software can be used by businesses of any size even if you’re just got started. Starting with a CRM system from the get-go means you can be sure that data, information and important documents are all stored safely and in one place. You don’t need to carry out any data migration or worry about losing information amongst stacks of files and paperwork. Instead, your CRM system will have all the necessary info stored plus be equipped with tons of tools and solutions to make your business much more streamlined and efficient. 

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UBER CRM case study Customer retention metrics in SQL

Background : I want to find the retention of a customer cohort on a weekly-rolling basis, so that they can take necessary intervention if a rider has not taken a ride for 28 days.

Link : Problem in detail

Below are list of metrics I'm trying to achieve in a single query

Definitions of Columns in the Output Query (Single Query):

date: the date in respect to which the below metric will be computed.

city_id: the id of the city

dau: Count of distinct riders who have completed min one trip on that date.

wau: Count of distinct riders who have completed min one trip in the last 7 days with respect to the date in column ‘date’

new_rider: count of distinct riders who have taken their first trip in the last 7 days with respect to the date in column ‘date’

previous_mau: count of distinct riders who have taken min one trip between the last 56 to last 29 days with respect to the date in column ‘date’

mau_28: Count of distinct riders who have completed min one trip in the last 28 days with respect to the date in column ‘date’

retained: intersection of distinct riders in the previous_mau and mau_28 phase

resurrect: count of distinct riders who were inactive in the previous_mau phase but were active in the mau_28 phase.

churn: count of riders who were active in the previous_mau phase but inactive in the mau_28 phase.

Active : If a rider has completed at least one trip in the respective period Inactive : If a rider has not taken a single trip in the respective period

Below is what I have tried:

Query to insert values

Below is what I got/Acheived so far: (Credit goes to LukStorms )

How to achieve all the results of the above queries in a single query? And how to write a query to answer 7,8,9,10 questions above in a single query output?

also, they are few special considerations for mapping rider to a particular city

A rider may take a trip from multiple cities, which might lead to counting the riders active or inactive in multiple cities. Hence to solve this problem a rider needs to be mapped to one city only. A rider should be mapped to a city from which they have taken the maximum trips considering only their recent 20 trips. 2. For all calculations related to a city it is important to consider the city mapped to a rider instead of the city where the trip occurred. 3. Our database system does not have a standard mode function so the rider city mapping needs to be derived.

• 1 Can you show the expected results for the given sample data. –  Dale K Commented Nov 28, 2019 at 19:46
• Hi Dale K, I have hyperlinked the detailed document of what I’m trying to achieve by this query –  PieSquare Commented Dec 1, 2019 at 19:23
• 1 SO questions need to be stand-alone and not depend on external resources. –  Dale K Commented Dec 1, 2019 at 19:25

2 Answers 2

Here is how I would do it ->

MS SQL Server 2017 Schema Setup :

• I missed the requirements to roll up the results by city and date, instead of date and that bit was added. Also the dau was added. I didn't have time to unwind and properly test but I think the results are sound. –  Ross Bush Commented Dec 3, 2019 at 19:50

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Uber Case Study: from Startup to Global Mission

by Bharat Arora · Updated on October 9, 2023

TABEL OF CONTENTS

• Introduction

From Humble Beginnings to Global Domination

• The Disruptive Wave: Challenges for Traditional Industries

Business model

Understanding the business, sharing economy business model, uber vs. regular taxi: how passengers meet drivers, introduction for uber case study:.

In 2009 a revolutionary idea was born on the streets of San Francisco.

An idea that will redefine urban mobility and challenge the non-functionality of traditional transportation.

This was the beginning of Uber, a startup that would soon become a popular name across the world.

But how did a simple app achieve such huge success in a relatively short period of time?

And what were the subsequent effects of its unique approach on established industries?

Let’s dive in deeper about the Uber Case Study.    

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When Travis Kalanick and Garrett Camp first started with Uber, it was out of a personal need: finding a reliable ride in the city.

Little did they know, this seed of an idea would sprout into a tech giant, now valued at billions.

In its early days, Uber was a luxury service, offering rides in high-end vehicles. But as the company grew, it adapted, monetized, and expanded its services while meeting the needs of a broader audience. UberX, UberPOOL and Uber EATS are just a few examples of how the company continues to innovate to meet the diverse needs of its users.

Unique business ideas: Challenges for Traditional Industries

As Uber began to gain success, it wasn’t just the transportation industry that felt losing customers due to the competition.

Traditional business models across various sectors were suddenly under trouble, being compared to this new, agile approach that Uber represented.

The company didn’t just offer rides; it offered convenience, efficiency, and a user-centric experience, all come in a mobile app that is available on the Google Play Store and Apple Store .

But innovation comes with its unique challenges. Taxi unions, regulators, and even some users were skeptical and, at times, openly hostile to the changes Uber brought.

Cities like London, Paris, and New York saw massive protests, with taxi drivers voicing their concerns about this new player in the market

However, what truly sets Uber apart was its ability to leverage technology and data, continuously refining its services based on customer feedback and behavior.

What is Uber’s business model?   Is it sustainable?

Uber operates under a platform-based business model, often referred to as the “sharing economy” or “peer-to-peer” model.

Here’s a breakdown:

• Platform-based model: Uber acts as an intermediary between drivers (service providers) and passengers (customers). who doesn’t own a vehicle; instead, it partners with drivers who use their own cars.
• Flexible pricing: Uber uses an algorithmic pricing model in which fares can change based on real-time supply and demand. This  often happens during peak hours or during unfavorable weather conditions, known as “surge price.”
• Cashless transactions: Payment is made through the app using a credit card and debit card, making the process seamless for  drivers and passengers.
• Feedback and Rating system: After each trip, drivers and riders will rate each other. This ensures a level of quality control and trust within the platform.
• Diverse services: Uber has diversified its services over the years.From luxury rides (Uber Black) to economical options (UberX) to carpooling (UberPOOL), it meets a variety of customer needs. In addition, it also expanded into other areas such as food delivery using UberEats.
• Global presence: Uber operates in many cities and countries around the world, adapting to local regulations and market conditions.

Is it sustainable? 

The sustainability of Uber’s business model has been a topic of debate for many reasons:

• Regulatory challenges: Uber has faced regulatory hurdles in many cities and countries. Traditional taxi services have protested against Uber, leading to bans or restrictions in certain areas.
• Financial concerns: As of my last update in January 2022, Uber has yet to achieve consistent profitability. Although revenue is significant, the company still spends heavily on promotions, driver incentives and expansion efforts.
• Reputation management: Uber has faced criticism and negative publicity on many fronts, from safety concerns to corporate culture issues. Addressing these concerns is critical for its long-term sustainability.
• Competition: In many markets, local competitors (such as Ola in India, Didi in China, and Lyft in the United States) are challenging Uber. These competitors often have a better understanding of local market and can offer stiff competition.
• Relationship with the driver: Classifying Uber drivers as independent contractors rather than employees has been controversial. Drivers’ desire for better pay and benefits has led to legal battles in some areas.
• Diversification: On the positive side, Uber’s diversification into areas such as food delivery (UberEats) and freight (Uber Freight) could provide additional revenue streams and enhance the company’s sustainability.

A unique Business model with sharing economic approach – The term “unique” in the business context refers to innovations that significantly change industries and markets, often displacing long-standing, market-leading companies, products, and alliances.

Uber’s business model proves this definition. Instead of following a traditional asset ownership model  (like a taxi or fleet), Uber relies on a “sharing economy” approach.

• Sharing economy:  At its core, the sharing economy is a social-economic system built around  sharing resources. This is usually a platform that makes it easy for you to borrow or rent assets owned by others.  In Uber’s case, that means connecting drivers willing to share their personal vehicles with passengers looking for a ride.
• Asset-Light model: One of the main advantages of this approach is that Uber does not incur the costs and liabilities associated with owning a fleet of vehicles. Instead, it focuses on maintaining and improving the platform that connects drivers and riders.
• Win-win scenario:  Drivers have the opportunity to work on their terms and earn money using the asset they already own (their car), while riders benefit from convenient and more affordable transportation option.

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A click from the nearest available car

The easy to use and immediate services of Uber are unbelievable in comparison with the traditional taxi industry

With the Uber app:

• Instant access: Users can hail a ride with just a few taps on their smartphone. The application interface displays the number of available vehicles in real time, helping users know the distance of the nearest driver.
• Transparent prices:  Before confirming a ride, users get an estimated fare, ensuring there are no surprises at the end of the trip.
• Real-time tracking:  Once a ride is booked, users can track the driver’s progress to their location and get an estimated time of arrival.
• Cashless transactions: The entire payment process is managed in the app, eliminating the need for cash and making the end of the ride smooth and hassle-free.

Serves All Age Groups and backgrounds

Uber’s appearance is not limited to a specific demographic. Its user-friendly design and diverse services offering target a wide range of audiences:

• For young and tech-savvy people: The convenience of booking a ride via a smartphone app attracts the younger generation,who are used to digital solutions based on their needs.
• For the elder: Even for those who aren’t tech-savvy, Uber makes an effort to make its platform accessible. Features like the ability to book a ride for someone else or the ability to hail a ride without an app in certain areas are aimed at older users.
• Diverse Service Range:  Whether it’s a luxury car service (Uber Black), a economical ride (UberX), or a carpooling option (UberPOOL), there’s something for everyone, regardless of  budget or preference. what they like.
• Wide range of services: Uber has also taken steps to ensure its service is inclusive. Features like Uber WAV (wheelchair accessible vehicle) and efforts to provide services to undeserved areas demonstrate their commitment to meeting all walks of life and needs.

Provides Financial and Economic Value

The sharing economy’s primary allure lies in its ability to unlock significant financial and economic value:

• Optimized Resource Utilization : Traditional business models often involve underutilized assets. For instance, a car might sit idle in a driveway for hours or a room might remain vacant in a house. The sharing economy taps into this dormant value, allowing individuals to monetize these underused assets by renting or sharing them.
• Cost Savings for Consumers : By bypassing traditional middlemen and infrastructure costs, services in the sharing economy often provide more competitive pricing. For example, staying in an Airbnb can be cheaper than a hotel, and using platforms like Task Rabbit can offer affordable services compared to established businesses.
• Economic Stimulus : The sharing economy injects money into local economies. Hosts, drivers, or service providers earn directly from their assets or skills, often supplementing their primary income sources.

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Attracts Investors

The potential and rapid growth of the sharing economy have not gone unnoticed by the investment community:

• High Valuations : Companies operating within the sharing economy, like Airbnb, Uber, and We Work, have achieved multi-billion dollar valuations in relatively short time frames.
• Venture Capital Influx : The innovative nature and scalability of sharing economy platforms have attracted significant venture capital. Investors see the potential for high returns, especially if these platforms can achieve dominant positions in their respective markets.
• Future Potential : As technology continues to evolve and more sectors become ripe for disruption, investors anticipate that the sharing economy model will permeate even more industries, offering further investment opportunities.

Fast Growing Industry

The sharing economy’s growth trajectory has been nothing short of meteoric:

• Rapid Adoption : The convenience, cost-effectiveness, and user-centric design of sharing economy platforms have led to swift adoption rates among consumers. Many people now prefer to hail a ride on Uber or rent a vacation home on Airbnb rather than use traditional services.
• Global Expansion : While the sharing economy began primarily in Western countries, its reach has quickly expanded globally. Markets in Asia, Africa, and South America are experiencing surges in sharing economy platforms tailored to local needs.
• Diverse Sectors : Initially, the sharing economy was most prominent in sectors like transportation and accommodation. However, its principles are now being applied to diverse areas, including finance (peer-to-peer lending), fashion (clothing rentals), and even agriculture (equipment sharing).

Uber’s Financial Value and Revenue:

• 2014: Uber reported a net revenue of $400 million.
• 2015: Uber’s net revenue surged significantly, reaching approximately $2 billion.
• 2016: The company’s growth trajectory continued with a net revenue of around $6.5 billion.
• 2017: Uber’s net revenue reached $7.5 billion, marking a steady increase.
• 2018: The revenue figures for this year stood at approximately $11.3 billion.
• 2019: Uber reported a net revenue of around $14.1 billion.
• 2020: Despite the challenges posed by the COVID-19 pandemic, Uber managed a net revenue of about $11.1 billion.
• 2021: The company’s net revenue rebounded to approximately $15 billion.
• 2022: As of the latest data, Uber’s net revenue is projected to be around $16.5 billion.

Uber Driver Earnings:

• 2014: Drivers could earn up to $20 per hour.
• 2015-2016: The earnings for drivers remained relatively stable, with many reporting earnings in the range of $18 to $25 per hour, depending on the city and demand.
• 2017: Some reports suggested that driver earnings slightly decreased to an average of $17 to $23 per hour.
• 2018: With more drivers joining the platform and increased competition, the average hourly earnings hovered around $16 to $22.
• 2019: Driver earnings saw a slight uptick, with many earning between $17 to $24 per hour.
• 2020: The pandemic impacted driver earnings due to reduced demand, with many drivers reporting earnings of $15 to $20 per hour.
• 2021: As the demand for ride share services began to recover, driver earnings ranged from $18 to $25 per hour.
• 2022: The latest data suggests that drivers can earn anywhere from $19 to $26 per hour, depending on factors like location, time of day, and promotions.

It’s essential to note that these figures are approximate averages and can vary based on several factors, including location, demand, promotions, and individual driver performance.

Attracts Investors:Since its founding,Uber has attracted investors and significant attention from the venture capital community.

Its innovative approach to transportation and  rapid growth have made it a top candidate for investment.

• Valuation:Uber’s value has skyrocketed over the years. In 2015, it was valued by investors at a staggering $51 billion, making it one of the most valuable startups in the world at the time.
• High-Profile Investments:Several leading companies soon realized Uber’s potential and decided to invest.These include:

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Menlo Ventures:An early-stage venture capital firm that has backed several successful technology companies.

Google Ventures (GV): AlphabetInc’s venture capital arm.  (Google’s parent company) has invested in Uber, strengthening its position in the technology industry.

Fidelity:A multinational financial services company saw the potential benefits of Uber’s growth.

BlackRock:Another major global investment management firm has backed Uber.

Fast-Growing Industry:Uber’s impact on the transportation industry is undeniable. Its growth metrics reflect the success and  demand for its services.

Daily Trips: According to the latest data, Uber makes an average of 25 million trips per day. This number shows the  scale of the company’s operations and the level of trust users have in the company’s services.

Total Trips:Since its founding in 2010, Uber has facilitated  42 billion trips worldwide. This number not only highlights the company’s growth but also its global reach and acceptance.

It’s important to note that while these numbers provide insight into Uber’s growth and investor interest, the company’s journey has been filled with challenges, controversies, and competition.

However, its ability to attract investors and its rapid growth in the industry have highlighted its importance in the sharing economy and the transportation sector more generally.

  Type of services from uber

Uber black:.

• Description: Uber Black is the company’s original luxury service. It offers riders  a more premium experience than standard services.

Vehicle Type: High-end black luxury sedans often come from brands such as Mercedes-Benz, BMW or Audi.

Registration & Insurance: All Uber Black vehicles are commercially registered and insured, ensuring a higher level of safety and professionalism.

Driver Requirements: Uber Black drivers typically have professional driving experience and are expected to provide a higher level of service.    

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• Description:The Uber SUV is similar to the Uber Black but offers a larger vehicle for those who need more space.

Vehicle Type: High-end black luxury SUVs like Cadillac Escalades or Lincoln Navigators.

Registration & Insurance: Like Uber Black, all vehicles are commercially registered and insured.

Capacity: Designed to accommodate larger groups or passengers with more luggage.

• Description: UberX is Uber’s  most popular and standard service, providing affordable rides for everyday use.

Vehicle Type:Typical everyday cars, which can range from a Toyota Prius to a Honda Accord. Model year requirements varies by city, but  generally it’s a 2000  or newer model (in some cities, 2005 or newer).

Driver Requirements Drivers must have a clean driving record and pass a background check.

Vehicle Requirements: Specific car brands and models are accepted, and vehicles must be in good condition.

• Description: Uber XL is designed for larger groups, offering vehicles with more seating capacity than UberX.

Vehicle Type: Larger vehicles like minivans or SUVs.

Capacity: Can comfortably fit 6 passengers or more.

Pricing: While it’s priced higher than UberX due to the larger vehicle size, it’s still more affordable than the luxury options.    

Uber Select:

• Description: Uber Select is a mid-tier luxury service, offering high-end cars without the premium price of Uber Black.

Vehicle Type: Luxury sedans and SUVs, but not as high-end as Uber Black or SUV.

Availability: Only available in select cities.

Pricing: Positioned between UberX and Uber Black in terms of pricing.

• Description: Uber Pool is a carpooling service, allowing passengers to share rides with others heading in the same direction.

Shared Rides: Passengers share the vehicle with others, making stops along the way to pick up and drop off.

Pricing: It’s cheaper than UberX since the cost is split among multiple passengers.

Availability: Only available in select cities and often in high-demand areas.

It’s important to note that the availability and specifics of these services can vary based on the region and local regulations. Always refer to Uber’s official website or app for the most up-to-date information for a specific location.

• Digital Convenience:  With Uber, the entire process is digitized. Customers use the Uber app to request a ride. Once the ride is confirmed, they can track the driver’s location in real time and know the estimated arrival time.
• Feedback system:  After the ride, customers can rate the driver, providing a feedback loop that helps ensure service quality.

Regular Taxi:

• Traditional Hailing:  Traditionally, customers hail a taxi on the street by waving or hailing an available taxi.
• Book in advance by phone:  They can also contact the taxi company in advance, who will then send the driver to the designated location. This method often requires waiting and lacks Uber’s real-time tracking feature.

Driver Options

Flexibility: Drivers use their own car, eliminating the need for a dedicated taxi license in many areas. This has democratized access to the ride-sharing economy, allowing more people to make money without large initial investments.

Regular Taxi: License: Traditional taxi drivers often require a specific taxi license to operate. It can be theirs, or they can rent one.

Dispatch service:  Many taxi drivers pay a monthly fee to a dispatch service, which provides them with booking services.  Some drivers also rent both the car and the license, which increases their overall costs.

Financially Interested Parties

Simplify stakeholders:  The main stakeholders are Uber itself (which receives a commission on each trip), the drivers, and the investors who funded Uber’s operations and growth.

Complex ecosystem: The traditional taxi model has involves many stakeholders, including  licensing agencies that manage and issue taxi licenses,  taxi companies that might own and operate fleets, individual drivers, and taxi license holders who might lease their licenses to other drivers.

The impact of the Uber model on the typical taxi industry and its key partners.

• Passengers benefit from greater reliability and convenience: With Uber, passengers have witnessed a paradigm shift in the way they hail and use transportation services. The Uber app offers real-time tracking, estimated arrival times, and transparent pricing. Passengers no longer have to stand on street corners waiting for a taxi to pass.  Instead, you’re just a few clicks away from a reliable ride, often with shorter wait times than traditional taxis.
• Drivers have higher income by Moving to Uber: Many drivers have reported higher incomes after leaving traditional taxi services for Uber. The flexibility to choose their own schedule, coupled with flexible pricing during periods of high demand, allows them to maximize their revenue.  Additionally, paying directly through the app eliminates the risk of unpaid tickets.
• Taxi companies are losing revenue:  Traditional taxi companies have faced a significant decline in revenue  due to the rise of ride-sharing platforms such as Uber. The convenience and often lower prices offered by Uber have caused many drivers to  switch, leaving taxi companies with fewer customers and reduced revenue.
• Loss of license validity: In many cities, taxi licenses (often called “medallions”) were once very valuable, sometimes costing hundreds of thousands of dollars. However, with the advent of Uber and other ride-sharing platforms,  demand for these licenses has decreased, causing their value to drop significantly.
• Licensing agency loses sales revenue due to reduced license value: As the value of taxi licenses declines, licensing authorities face a decline in revenue from selling and renewing these licenses. With fewer individuals and businesses interested in purchasing taxi licenses, these authorities have seen  their revenue sources streams.

Management: How does Uber manage Two sides of its market?

Two-way market:

Uber operates in a two-sided market, connecting drivers (supply side) and riders (demand side).

Managing this balance is crucial. Too many drivers and not enough riders can lead to driver dissatisfaction, while too many riders and not enough drivers can lead to long wait times and unhappy customers. Uber uses surge pricing  to manage this balance, raising prices at times of high demand to attract more drivers and vice versa.

Two groups of agents  interact through a “platform”, where one group’s benefit from joining the platform depends on the size of the other group joining the platform.  -Armstrong M. Regulatory approach

What do you think about Uber’s soft approach to regulation?

Uber’s business model has unique characteristics that make it difficult to classify the company into a specific industry.

Technology is at the heart of the network,delivering an unprecedented breakthrough model.

Uber has faced  criticism and backlash from taxi corporations, but has received praise and support from  customers.

By exploiting their position as a disruptive innovator, they have placed themselves in a position to influence the public.

In 2014, Uber hired David Plouffe to lead the company’s communications and public policy department.

Regulatory approach:

What’s the verdict on Uber’s cowardly approach?

Uber’s entry into the transportation market is nothing short of a revolution. But  innovation often comes with controversy, especially when it challenges established standards and regulations.

• Unique Business model:  Uber’s business model has blurred the lines between traditional taxi services and technology platforms. By positioning itself as a technology company that connects riders with drivers rather than a transportation service provider, Uber is operating in a regulatory gray area.  This has made it difficult for regulators to classify and manage companies within existing frameworks.
• Disruption at Its Core:At the heart of Uber’s model is technology.  By leveraging smartphones, GPS, and data analytics, Uber has introduced an unprecedented disruptive model to the transportation industry. This technological approach not only brings convenience to users but also poses significant challenges to traditional taxi services and regulators.
• Mixture of reactions: Although Uber has faced  criticism and backlash from taxi groups and some regulators, it has been praised by  users. The convenience, transparency, and generally lower costs associated with this platform have made it a favorite among runners.  This response dichotomy highlights the tension between innovation and regulation.
•  Exploiting the position of disruptive innovators:  Uber’s strategy isn’t just about providing rides. By positioning itself as a disruptive innovator, the company has achieved significant public influence. This influence often helps shape public opinion and, in some cases, even management decisions.
• Recruitment strategy in 2024: In an effort to strengthen its position and navigate the complex regulatory landscape, Uber hired David Plouffe in 2014 to lead the company’s public policy and communications department. Plouffe, with his political acumen,is seen as a strategic addition to Uber’s team, helping the company interact more effectively with regulators and stakeholders.

Safety Concerns and Challenges:

• Incidents related to False documents:  One of the biggest concerns that has emerged over the years has been incidents involving Uber drivers using false documents. There have been cases of drivers successfully passing Uber’s background checks using false or borrowed documents. Such incidents not only raise questions about the platform’s verification process but also pose potential risks for riders.
• Uber’s proactive response to security concerns: Uber quickly recognized its security concerns and took a number of steps to address them. The company has continuously developed its background check procedures, cooperated with law enforcement, and invested in driver safety training.  Uber’s commitment to safety is evident through its efforts to improve safety procedures and respond to feedback from passengers and drivers.
• Advanced security features: Uber has introduced several safety features to keep rider and drivers safe:
• Real-time identity check:  Periodic prompts driver to take a real-time selfie before accepting a ride, ensuring that the driver is using the app that is appropriate for the account holder.
• Driver profile:  Riders can view detailed profiles of their drivers, including ratings, compliments and number of trips taken.  This transparency allows riders to know more about the person driving them.
• Two-factor authentication:  To prevent unauthorized access, Uber has implemented two-factor authentication for its drivers. This additional layer of security ensures that only registered drivers can access the app.

The future of Ride sharing

The world of transportation is changing rapidly, and ride-sharing services, led by Uber, at the forefront of this transformation.

Traditional transportation methods are being challenged as consumers seek more convenient alternatives.

In 2019, the mobility market saw significant advancements, including record electric vehicle sales  records and regulations promoting shared mobility.

Global automakers have faced challenges such as stricter emissions regulations and trade tensions. Uber’s journey offers a insights into the future of ride-sharing.

Adapting to regulations, technology and consumer preferences will be essential.  By 2030, there is a huge opportunity for ride-sharing platforms, with highly connected vehicles worth between $450 billion and $750 billion.

Uber’s journey resembles disruptions in other industries, such as digital streaming vs. cable TV and online marketplaces vs brick-and-mortar stores.

Survival depends on the ability to adapt.

Uber identified gaps in the taxi model, used technology to fill them, and expanded rapidly.

This success demonstrates the power of innovation.

In short, the future of ride-sharing services led by Uber looks promising. As technology evolves and consumer preferences change, flexibility and adaptability will be critical.

Traditional industries may view these changes as threats or opportunities; the choice is theirs.    

Uber’s journey is a testament to innovation and adaptability in today’s rapidly evolving digital world.

Despite legal battles & internal problems, Uber has thrived, expanding to 737 cities in 84 countries, and providing more than 5 billion rides.

This shows his resilience. In the era of digital transformation, businesses must innovate to avoid obsolescence.

Uber has leveraged technology to disrupt the taxi industry, focusing on user-friendly applications and customer convenience.

However, achieving profitability remains a challenging. This emphasizes the need for adaptability.

In short, Uber’s journey highlights the importance of resilience, innovation, and adaptability.

At Protocloud Technologies , we provide website and mobile application development services.

We can help entrepreneurs and small business owners create a ride-sharing app like Uber, allowing them to successfully navigate a growing market.

Global Ride-sharing Trends

Passenger experience with uber, peer-to-peer business model, ride-sharing app development, ride-sharing future trends, ride-sharing revolution, sharing economy, two-sided market strategy, uber business model, uber financial growth, uber vs traditional taxi, uber's global impact, uber's regulatory challenges, bharat arora.

I'm Bharat Arora, the CEO and Co-founder of Protocloud Technologies, an IT Consulting Company. I have a strong interest in the latest trends and technologies emerging across various domains. As an entrepreneur in the IT sector, it's my responsibility to equip my audience with insights into the latest market trends.

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Uber Case Study: How the Ridesharing Giant Keeps Its Brand Strong

26 Nov 2019

Michael Signal

Table of Contents

How do average people fundamentally reshape a global multi-billion-dollar industry?

In Uber’s case, the answer is “by driving the same cars they already have.”

In this Uber case study, we will find out how they ascended to the heights of success and navigated through difficult waters along the way. We’ll see how they’ve built a sustainable brand that continues to succeed in a challenging industry.

Uber was one of the first companies to embrace and define “the sharing economy” concept. In so doing, it empowered consumers and entrepreneurial individuals to take control of for-hire transportation.

It is, in short, one of the most iconic technology companies in modern history.

That success didn’t happen overnight or without a lot of strategic planning and effort.

Uber is not a mere beneficiary of good luck or positive economic forces beyond their control. They are a perfect example of how a brand can be disruptive, transformative, and even sustainable.

Innovation in the Driver’s Seat

Innovation was the driver behind Uber’s initial success. This was evident in its unique premise: hail a ride from anywhere using a smartphone.

It is easy to forget that only a few short years ago, this wasn’t possible. At best, one might call a ride in from a local taxi or shuttle company, wait in the taxi line at the airport, or hail a cab on the side of the street.

Uber’s entry into the opaque world of ride-for-hire also allowed it to define innovation as its primary driver early on. The company would, its management said,  define itself as a technology company  and not as some kind of new taxi enterprise.

Again, a few years ago, this was unthinkable. Uber was a completely new product in a world where people had to wave down a ride from the side of the street. Uber’s product put the power of transportation into the hands of riders through their smartphone.

Embracing Disruption

As the company grew and ran into regulatory barriers erected to support the traditional for-hire transportation industry, such as taxis and limousines, it decided to embrace the controversial role of industry disruptor.

How, though, could Uber win against the myriad taxi regulations in major cities, which prevented them from doing things like picking up and dropping off at airports?

As Shark Tank investor Kevin Harrington pointed out in Forbes, the answer was in mobilizing customers to their cause. Uber was able to identify that many of its customers weren’t happy with the existing state of affairs in the transportation industry.

These customers wanted something better and became Uber’s core base. They then became advocates for the company in various forums as it fought against old regulations. Uber was smart to  identify and cultivate these customers  early on.

By making customer convenience and service a priority, Uber took the role of “disruptor” and turned it into a part of the company’s image and brand. They joined a broader  socioeconomic movement  towards changing old industries in ways that benefited consumers.

Uber, of course, also had to create a framework of lobbyists and other professional policy advocates. They began spending millions of dollars in places like  New York City . These fights continue because regulated taxis haven’t given up trying to keep Uber from invading their turf.

By and large, however, Uber has won – and in the process, made the innovation of changing an old industry part and parcel of what it represents to consumers.

Navigating Tough Waters

No Uber case study would be complete, or accurate, without documenting Uber’s challenges over the past couple of years.

In February 2017, former Uber employee Susan Fowler, an engineer, made a blog post heard round the world. On her blog, she described a toxic culture at the company where sexual harassment was rampant and managers cannibalized each other.

Her post received so much attention that Uber decided to respond by having the law firm Perkins Coie  do an investigation  into her allegations.

The CEO and co-founder of Uber, Travis Kalanick, began facing scrutiny over Uber’s company culture.

The company recognized a crucial if simple truth: to maintain a sustainable brand long-term, Uber had to be honest about what it stood for. Was it a cutting-edge, progressive company, as it attempted to posture itself? The brand teetered on the brink of outright hypocrisy, if not total disaster.

If it was the brand that Kalanick had long said that it was, then he had to go. Kalanick, along with Uber’s management, recognized this. There were numerous other personnel casualties of Uber’s very public self-reflection.

The most noteworthy demise, however, was the toxic culture threatening the long-term viability of the company. Out of the ashes of its former self, Uber decided to undergo a massive effort to restore its image and set itself up for the future.

Rebranding for the Future

Uber took what could have been its defeat and turned it into an opportunity. The new CEO made a point of  listening to employees  and driving that principle deep into the heart of a new corporate culture.

Some Uber executives even go the extra mile to participate as normal Uber drivers and experience what Uber’s drivers experience. The importance of getting one’s hands dirty is a part of the refreshed culture. Executives now attempt to bridge the gaps between drivers and the employees at the very top.

It also embarked on a major rebranding intended on capturing an accessible, progressive style that reflected the best of the company and communicated credibly with consumers. Uber recognized that  design was crucial  to the customer experience.

This included not only practical matters, such as the kind of typeface used, but also larger questions such as the tone of voice applied to its marketing and communication efforts.

Uber is not done with its rebranding effort, which included a  massive initial public offering  (IPO) in May of 2019. Uber’s entry into the stock market has been fraught with challenges. The company continues to lose money and investor confidence dwindles. The stock has had problems due to doubts about Uber’s profitability, among other concerns.

However, the Uber brand continues to be strong and recognizable – an asset that is almost certain to continue.

Lessons of the Uber Case Study 

Uber is, in one sense, a wholly unique company whose success would seem hard to emulate.

After all, not everyone is in a position to create a new company that disrupts an entire industry and takes on regulators the world over en route to a multi-billion-dollar IPO.

On the other hand, many of the lessons that Uber provides apply to other companies and startups .

Uber’s determination to focus on technology and innovation points to the importance of defining a clear brand strategy and messaging focus.

Their ability to embrace the role of disruptor offers hope to entrepreneurs tackling business norms and stale industry attitudes.

Hope can also be found in the company’s ability to weather challenges to its very existence. Uber took what could have been a disastrous 2017 and parlayed it into fresh opportunities for the company that concluded with an IPO.

The final lesson of this Uber case study, then, appears to be determination: determination to  strategize and plan  with clarity and focus, determination to stick with it through thick and thin, and determination to right the ship when things get difficult.

Are You the Next Uber?

Uber’s determination has proven, in many respects, to be the core value upon which its brand is most closely associated. It is this determination which also proves the greatest lesson for others in this Uber case study.

Do you have a great idea for a mobile or web app and want to emulate the success of Uber? We have experience helping some of the most credible and innovative firms in Australia and would love to partner with you to create more success.

Reach out  to learn more!

Michael is the creative brains of the company and he leads the UX and UI team at EB Pearls. He has experience of over 20 years in interaction design and have designed digital products for Fortune 50 companies all over the world.

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“We’re very happy with the results of EB Pearls’ work. Since its launch, the app has had over 7,000 downloads, with around 6,000 users completing the signup process in the first 6 weeks. ”

— Founder at Intro Dating

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How Simpleview CRM + Act-On saves Hawaiʻi Visitors & Convention Bureau 4,000+ hours each year

Aside from enriching Hawaiʻi and its people and attracting visitors who will leave the destination better than when they arrived, Hawaiʻi Visitors & Convention Bureau (HVCB)’s promise is to support its members by providing unique, strategic benefits to help them achieve their goals. 

However, with an impressive 1,300 members (100 new members annually) and hundreds of new contacts for existing members each year, HVCB faced a challenge in onboarding, engaging, and retaining so many accounts without dedicating its staff’s valuable time. 

Using Simpleview CRM and Act-On , HVCB built automated workflows that empower members to maximize their memberships — and help staff reclaim their limited time.

Act-On is a fantastic tool. It helps us free up our staff’s time using automated programs, it is easy to set up a new member program to increase member engagement, and success is measurable.

Since launching automated campaigns, HVCB has reported:

An open rate of 55.1%, with an open rate of 25.7% on resends 

78% of respondents said the welcome series was “very helpful”

Zero opt-outs

Saved 4,000 hours a year with automation

Increased membership by about 100 in 2024

Where they started:

In 2023 they had 210 contacts in the program with 1,680 emails sent

Where they are now:

In 2024 they have 520 contacts that have gone through the program with 4,883 emails sent

Download the case study to learn more.

Michael Fiez

Michael is a former DMO pro who can strategize, synthesize, and stitch stories together. He strives to deliver value and connect destinations with the tools and resources they need.