Uber
Product Feature
UX Research
Timeline
2 Weeks
Role
Product Designer
Tools
Figma
Goal
The goal is to help Uber riders quickly navigate the airport without relying on airport staff or sign architecture. Additionally, the aim is to increase Gross Bookings for Uber rides originating and ending in airports. This will be achieved by increasing Monthly Active Platform Consumers (MAPCs) through capturing a higher percentage of the airport commuter market.
Airports: Opportunity Assessment
Airports represent a significant growth area for Uber, offering a steady stream of travelers who need reliable transportation to and from these major transit hubs. Despite the promising potential, Uber faces intense competition in this market. The following points highlight the key aspects of Uber's involvement in the airport transportation sector:
Uber generates a significant percentage of Gross Bookings from trips in large metropolitan areas and trips to and from airports.
In 2018, Uber generated 15% of Ride-sharing Gross Bookings from trips that either started or were completed at an airport.
Uber experiences great competition in the airport market from other ride-sharing companies, traditional taxis, and car renting services.
[Key metrics referenced from S-1 filing]
Problems
Traveling through airports can be a challenging experience for many flyers due to various uncertainties and logistical hurdles. Common problems that travelers face when commuting to and navigating through airports include:
Flyers commuting to airports have a hard time figuring out which terminal and boarding gate their flight is taking off from.
Flyers often don’t know how early to arrive at the airport and how long the security process is going to take that particular day.
Grabbing a quick bite from an airport restaurant which is a long walk from their boarding gate might cost them their flight if they are in a time crunch.
After landing at their destination, flyers don’t know the status of their baggage or where to collect it from.
Why we should solve this?
Following Uber’s vision to ignite opportunity by setting the world in motion, solving flyers’ pain points, and making sure their journey from Point A to Point B is as effortless as possible will help us build trust.
Airport rides are costlier compared to regular rides because of the often high regulatory cost associated with operating business within an airport premise.
Airport riders might feel cheated by paying higher than usual fares for their commute. Personalized features for this particular user segment might incentivize them to justify this premium.
Hypothesis: Helping to simplify consumers’ airport experience might incentivize riders to chose Uber over other competitors and increase Gross Bookings from trips originating or ending in airports
Ranking Ideas
Idea 1 would require us to make a prediction model that will require high engineering effort. Business impact might be low because of competitors like Gmail who already provide this service the moment you receive a flight confirmation email.
For Idea 2 and 3 we can prompt the rider to check in with their flight number in the Uber app when they are heading towards an airport. This will require moderate engineering effort. Riders might be more incentivized to use this feature because they are already on the Uber app looking out for information like ETA, cost of trip.
For Idea 4, while researching about this I found out that Uber is already testing this idea in the Toronto airport and I want to brainstorm new solutions
Feature Proposal
Go-To-Market Pilot Program
Phase 1 (3 months): Begin by releasing the feature in five key cities: Toronto, Denver, Mumbai, Paris, and Dubai. These cities represent diverse airport markets across three continents, allowing us to gather comprehensive and varied data points. This phase is crucial for understanding the unique challenges and opportunities in different regions and collecting initial feedback from a broad user base.
Phase 2 (3-5 months): After analyzing the data and feedback from Phase 1, expand the release to 50 additional cities. This phase aims to validate the findings from the initial launch and gather more extensive data. By increasing the number of markets, we can ensure the feature's robustness and scalability, identifying any regional-specific issues and making necessary adjustments before a wider rollout.
Phase 3: With the insights and data collected from the previous phases, proceed to a global release. This final phase will involve launching the feature in all remaining markets, leveraging the learnings and optimizations from the pilot and expansion stages to ensure a smooth and successful global implementation.
Measuring Success
Qualitative: Implement a feedback form that prompts flyers to rate the accuracy of their flight details and leave comments after they have collected their baggage. This will provide valuable insights into user satisfaction and areas needing improvement.
Quantitative: Measure the net change in Gross Bookings for rides originating from airports. Since our feature adds value primarily for riders already en route to the airport, the number of rides ending at airports might remain unchanged. Focus on understanding how the feature impacts the volume of rides starting from airports.
Feature Discovery to Check-in Ratio: Track the percentage of users who discover the check-in feature and actually use it. This metric helps determine whether the check-in process is intuitive and easy to use or if it requires significant effort, potentially deterring users.
Check-in to Ride Call Ratio: Analyze the percentage of riders who, after checking in, proceed to call an Uber once they reach their destination. This is the most important metric based on our hypothesis, as it directly correlates the feature's effectiveness with increased ride bookings from airports.