Problem Space
Tourists are struggling
We reviewed 10 academic papers on tourist decision-making models, and conducted interviews with 10 travelers, uncovering 3 key problems they commonly face.
Information Overload
Trust and Credibility
Uncertain Conditions
Uber Drivers and Tourist Riders
When riders travel to a new city, they often crave authentic local experiences, but they lack personal connections. On the flip side, drivers know and love their city. They want to share it, but don’t have a clear or comfortable way to do so. Both sides want to connect, but right now, there’s no smooth or reliable way to make that happen.
Tourist Riders
Have no personal connections with locals of the city they are visiting
Know and love their city, but have no clear way to share it
Unsure whether locals are willing or available to offer recommendations
Worry that their recommendations may be unsolicited
Interacting with locals can be unpredictable, awkward, and rarely documented
Struggle to fully convey their recommendations while driving
Uber Drivers
Research Question
Aside from Airbnb, no existing platforms truly rely on locals for insights. Uber is uniquely positioned to do so through its network of local drivers.
Research Question
Aside from Airbnb, no existing platforms truly rely on locals for insights. Uber is uniquely positioned to do so through its network of local drivers.
Research Question
Aside from Airbnb, no existing platforms truly rely on locals for insights. Uber is uniquely positioned to do so through its network of local drivers.
Research Question
Aside from Airbnb, no existing platforms truly rely on locals for insights. Uber is uniquely positioned to do so through its network of local drivers.
Market Analysis
Research Finding
Localness
aside from Airbnb, no existing platforms truly rely on locals for insights. Uber is uniquely positioned to do so through its network of local drivers.
Research Finding
Aside from Airbnb, no existing platforms truly rely on locals for insights. Uber is uniquely positioned to do so through its network of local drivers.
Survey
215
Participants
20+
Platforms
Distributed
21
Total
Questions
100%
Completion
Rate
Research Finding
Localness
95% want recs from locals; 82% of those request recs from Uber drivers
Experiencing the locals’ lifestyle/customs provides an immersive travel experience that improves users fulfilment while traveling
Design Implication
Design methods that encourage local drivers to share travel insights, and enable users to easily discover hidden gems
Research Finding
Curate
users prefer a few very personalized recs tailored to their trip purpose
Users are overwhelmed with too many platforms and options to choose from when planning. Showing users too many options is not helping them
Design Implication
Help users focus on fewer, high-quality options, and provide sources of recommendation
Task Observation
Who: 5 participants of different travel styles, selected based on the survey. Why: Focused, observable behaviors for between-group comparison. What: Participants were given a travel-planning task with unexpected situations. We observed their tools and decision-making processes
Research Finding
Consensus: users rely on a consensus of reviews, ratings, and comments as social proof, yet they are susceptible to detailed negative feedback contradicting the consensus
Users are concerned about the authenticity of a positive consensus, but a large number of reviews helps alleviate this concern. Detailed negative feedback feels more personal than the generalized tone of positive reviews, and may create doubt about the consensus.
Design Implication
Similar recommendations should be grouped to provide social proof
Uber drivers and their recommendations should be verified to ensure they are trustworthy and authentically local
Diary Study
Who: 6 participants who were on vacation at the time. Why: real unexpected travel situations over a longer period. What: Participants were given a daily diary template, and self-report their decision-making processes during unexpected situations
Research Finding
Spontaneous: users often enjoy spontaneous exploration, discovering places of interest along their planned travel routes.
Travelers often deviate from their scheduled itinerary and end up filling in the gaps with activities nearby. They are open to unanticipated adventures and detours, which add a sense of impulsivity that they enjoy.
Design Implication
Design systems that suggest real-time, context-aware recommendations along the user’s route to help fill unexpected schedule gaps
Combined strategies are needed here
Three Themes
The three tourist challenges were translated into three themes for ideation. Each team member generated 10 design concepts inspired by research findings, and all ideas were categorized under the three core themes as shown in the Venn diagram. While many ideas successfully covered two themes, none fully encompassed all three. We realized that addressing them all would require a combination of strategies. Following the brainstorming session, each team member selected five design ideas with the most potential and developed sketches to better understand how these ideas could fit within the context of the Uber app.
Information Overload
Personalized
Trust and Credibility
Trust
Uncertain Conditions
Quick
Initial Sketches
The ideas covered different stages of the user journey: some focused on collecting riders’ preferences before generating recommendations, others concentrated on the in-ride experience where recommendations are delivered, and some explored the post-ride stage where users access their saved recommendations. Several sketches also investigated how and when recommendations could be prompted from drivers.
Concept Testing - Round 1
We selected three concepts that were well-received by participants during concept testing round one. The first concept recommends points of interest (POIs) along the rider’s current route. The second reimagines POI selection through a dating app–style swiping interface. The third replaces traditional ratings and reviews with insights drawn from Uber’s unique trip data. While none of these concepts alone became the final product, each contributed critical elements to the overall solution.
Concept Testing - Round 2
Rider experience product flow: after gathering feedback from the first round of testing, we developed new sketches that began shaping end-to-end product flows. One flow focused specifically on the in-ride experience, mapping the full journey of a first-time user interacting with what would later become known as Uber Recs. This work marked the initial formation of the Uber Recs experience.
Driver experience product flow: we also developed a flow for the driver side, specifically within the driver app, exploring how local insights and recommendations could be prompted from drivers without adding significant burden. However, due to time constraints, the project scope was limited to focusing solely on the rider-side experience.
Final Concept
We translated the envisioned experience into concrete steps, procedures, and interface elements needed to support it. The flow diagram outlines the full user journey. This exercise helped identify the critical decision points, interface needs, and system triggers required to make the experience feel seamless and intuitive. With a clear understanding of both user flow and system behavior, we were ready to proceed to developing the high-fidelity prototype.
Current Ride-booking Page
Design Goal
Add Uber Recs into the flow.
Keep it simple and intuitive.
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Iteration 1.0
Iteration 1.1
Solution 1
Each ride option (UberX, Black, etc.) includes a dropdown menu that lets users choose from nearby drivers.
Iteration 2.0
Solution 2
Display available drivers directly under each ride option, without adding a Recs mode toggle.
Iteration 3.0
Solution 3
All existing ride options remain unchanged, and users can simply choose drivers from a separate section called Uber Recs.
Open Uber at airport rideshare pickup
Book a ride to hotel with Uber Recs
Wait for pickup and view driver profile
Save driver recommendations
Approaching en-route recommendations
Book a ride with saved recommendations
Product intro pop-up
Recs mode home screen
Localness
Unlike generic tour apps, Uber Recs curates authentic insights sourced directly from local drivers, offering a uniquely personal and trustworthy experience.
Curation
When riders first arrive in a new city, such as Atlanta, their initial interaction with Uber Recs is designed to feel welcoming and inspiring. We introduce a specialized homepage that captures the local atmosphere, helping set the tone for exploration and putting riders into a "trip mode" mindset. While the experience encourages riders to engage with new features, it does so with minimal effort required, aiming to make them feel special and valued.
Select a Uber Recs driver
Uber Recs brand campaign
Spontaneity
In Recs Mode, riders book rides as usual, with an added option to choose a driver who shares their interests, like food or art, for spontaneous, personalized recommendations. This lightweight step creates chances for meaningful local discoveries without disrupting the flow.
Greeting card from driver
Driver profile page
Curation
While waiting for the car to arrive, users receive a personalized greeting card introducing the driver. They also have the option to view the driver's detailed profile. This touchpoint is designed to help break the ice and facilitate more natural conversation once the ride begins.
Localness
In Recs Mode, the driver profile highlights the driver's local roots and lived experiences, which form the basis of their recommendations.
Driver’s picks
Driver insights
Curation
In addition to the current driver’s recommendations, users can also view suggestions from other drivers who share their travel preferences.
Consensus
Alongside the driver’s personal take on recommended POIs, the system shows how many other drivers have recommended the place and how many users have saved it. Similar reasons are grouped to reflect a broader consensus.
Preview at start of trip
Tipping page
Spontaneity
If driver recommendations are on or near the route, they appear on the map. As the ride progresses, riders get notified just before passing a suggested spot, encouraging spontaneous discovery. The map also shows the distance from the rider’s current location or hotel, making it easy to revisit later.
The tipping page reminds users of the driver's recommendations, encouraging tips and offering another opportunity to save any they missed during the ride.
Notification on lock screen
Saved recs on homepage
Book a ride to saved recs
Spontaneity
The following day, when considering where to explore next, riders can easily recall saved recommendations, such as the World of Coca-Cola suggested by their driver, Margaret. From the homepage, riders can quickly book a ride to the saved destination, reducing the need for extensive research or planning.
Localness
Users can also save drivers to explore their full list of recommendations. Discovering destinations through a trusted local adds a sense of authenticity and connection that goes beyond browsing generic reviews.
© 2014-2023 Yijiang Xu
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