The Perfect uberPOOL: A Case Study on Trade-Offs

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Product Impact and Business Outcomes

The research team launched the Express POOL product on November 6th 2017 in San Francisco California and Boston Massachusetts. The rollout of the Express POOL product was spearheaded by Uber’s Shared Rides product team in San Francisco and augmented by local operations specialists. A minority of riders in these markets initially qualified to take Express POOL, but after checking the metrics to validate that the product was delivering against expectations it was rolled out to all riders. The product validation was based on the assumption that Uber could improve the uberPOOL experience for riders, drivers, and the company.

The team used trip cancellation rate as one of the many key performance indicators to determine the success of the Express POOL product launch. Trip cancellation rate is defined as the percent of trip requests made by the rider or driver that was cancelled before the driver arrived at the pickup location to start the trip. The metric is experiential, with clear associations between a lower rate and a better rider experience. Other important metrics studied at the product launch include Express POOL opt-in shared-rides rate, driver efficiency & earnings, rider inconvenience, rider earnings, support ticket rate, and more.

Figure 12 shows the Express POOL cancellation rate from the launch of the product in early November 2017 through mid-March 2018. The plot shows that in the period immediately after the launch both riders and drivers had relatively high cancellation rates, but the rates came down significantly as they adjusted to the new experience. A high cancellation rate is expected for new product launches, but is typically following by a decrease as people come up a learning curve of varying steepness. Even though the changes made to the Express POOL product request flow were substantial the team began to see a decline in cancellation rate two-weeks after launching.

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Figure 12. Express POOL Cancellation Rate

The improved rider experience, supported by a falling cancellation rate, may be due to a variety of factors. High cancellation rates may be a symptom of curious riders exploring the new product in their app, and then make a trip request purely to investigate the new experience. These cancelled trip requests naturally decay over time as the novelty factor on the product begins to wear off post-launch. Riders may also gain a better understanding of the mechanisms of Express POOL and decide not to cancel due to uncertainty when waiting for a driver match, apprehension about walking to the pickup-location, safety concerns, or another issue. In sum there are many factors that might drive the falling cancellation rate, but overall it is indicative of good product-market fit and having improved the existing uber POOL experience.

The new product was also able to drive value to Uber’s bottomline. In the first month after launch riders that requested an Express POOL only waited for 40-seconds longer on average than riders taking the original POOL option. This 40-second delay was intentional, as Uber made riders wait on the trip request screen to get batched with other riders on their trip. In return for this delay, the match rate for the Express POOL product was 3.6% higher relative to the existing POOL product. Match rate is defined as the total trip requests that were matched divided by the total number of outstanding trip requests; it is a leading indicator of business performance and product experience. The improved experience associated with an increased match rate translated to riders taking 4.6% incremental shared rides trips 1-month after launch.

The success of the November 2017 launch of Express POOL in San Francisco and Boston lead to the product being rolled out in many other domestic and international markets. In late February 2018 Uber launched Express POOL in Los Angeles, San Diego, Denver, Philadelphia, Washington DC, and Miami. These markets experience similar positive effects from Express POOL that were observed in the original launch markets, and by expanding in these cities a few months after the original launch the team was able to synthesize learnings from San Francisco and Boston to better execute on the rollout strategy in these second wave locales. The third wave of domestic cities to get the new product was Chicago, Seattle, Atlanta, Las Vegas, and the New Jersey area in mid-May 2018. Finally, Express POOL went international with the launch of Paris, Sydney and Melbourne in August 2018. Attractive expansion markets exists across the globe and Uber hopes to bring the Express POOL product to all existing shared rides markets.

CONCLUSION

In conclusion, the research efforts to create the perfect POOL required close collaboration between the Uber user research and data science teams to understand rider preferences and the trade-offs they make when evaluating their transportation options. The ability to integrate both research methods enabled the team to provide compelling data to business leaders that was ultimately the single biggest input in developing the next iteration of uberPOOL. The resulting success of Express POOL provides a good example of how cross-pollination between disparate research methods can lead to positive business outcomes.

AUTHORS

Jenny Lo is a User Research manager at Uber. Jenny specializes in the study of quantitative research methods and information technology in developing countries (ICTD). She received her Masters of Information Management and Systems from the School of Information at University of California, Berkeley and Bachelors from Wesleyan University. Email: jlo@uber.com

Steve Morseman is a Data Scientist at Uber. His research focuses on rider acquisition, engagement, and product development. Steve received his Masters in Political Science from the University of California, Los Angeles and his Bachelors from the State University of New York at New Paltz. Email: morseman@uber.com

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