TL;DR
Built a community of over 10K daily active users by introducing a mobile app that recommends restaurants based on social activity.
Role
The Trip Ventures team tasked me to design a mobile experience for an app that enabled customers to discover trending restaurants around the world. I was brought on as a UX researcher and designer to design the experience.
Social activity is a stronger affinity indicator than customer reviews.
Historically, the main paradigm for finding restaurants has been based through "review-centric" apps, like Yelp, Facebook or Google.
The Trip Ventures team believed there’s an opportunity to disrupt the category by providing a discovery experience that recommends restaurants based on their social activity (aka number of posts from location) rather than their amount of customer reviews.
I interviewed people between the ages of 18-45 in the area of Miami to better understand the current solution landscape and their needs.
The current market for restaurant discovery apps is failing to meet the needs of young customers seeking trendy culinary experiences.
By providing an app that offers personalized, social-driven recommendations, we have the opportunity to carve an audience of young “foodies” we can monetize.
How might we empower young "foodies" to effortlessly discover new trendy restaurants and hidden spots?
We alined on a strategy of developing an MVP for the Miami market to validate the opportunity and stress-test UX concepts before a wider release. Based on the research findings, we aligned on the following solution principles:
For the MVP, I explored a few UX concepts to address the main job: find a new restaurant to visit later.
Before starting with development, I created clickable prototypes and conducted user tests with 12 participants to understand which UX concept resonated most and identify potential friction points.
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Grid
Feed
Carousel
Ultimately, the “Carousel” concept resonated the most with users. 100% of participants completed the primary task and 10/12 choose the concept as their preferred option. InMost importantly,
I observed this UI pattern encouraged users to consider the recommended restaurants more carefully and had the added benefit of more real estate to leverage for restaurant information and photos.
From there, I crafted a lo-fi wireframe to map key workflows for the MVP:
With some directional validation, we moved forward with the launch of a closed beta. We targeted food enthusiasts and restaurant owners in Miami to keep our feedback loop tight and start building rapport with the community. While the overall response was very favorable, several key areas for improvement were identified:
I designed and iterated on few elements of the experience to address these pain points before expanding to other major markets:
Despite positive feedback, some users struggling to discover the swipe gesture to browse recommendations. To address this, I introduced in-app guides to explain explained key features or gestures when users open tabs for the first time.
Users indicated filtering by cuisine was a must-have. After further investigation, I found their struggle was the app recommendations did not match their particular needs. For instance, they would never go to the same spot for a romantic dinner versus eating with their family.
To streamline search, I introduced controls to filter by cuisine and ambiance to help users to find suitable options.
Some users requested a map-based interface, but upon investigation, I discovered their pain point was the inability to control their search range. Depending on the restaurant quality, people are willing to travel further. To address this, I introduce distance-based filters to enable users to adjust their search on their willingness to walk or drive.
At our core, our app is the “anti-yelp”. Overtime, I noticed the post sentiment started becoming more negative. Ultimately, the ability to attach text to a post encouraged the behavior we were trying to replace.
I re-designed the publishing workflow to only allow the sharing of photos to encourage positive posts. In the end, the number of photos shared remain steady and sentiment improved with the introduction of the new experience.
I introduced social proof indicators to help users understand why restaurants are being recommended and generate more trust. This includes displaying the number of visitors and affinity labels such as trending, new, local favorite, hidden gems and Michelin-rated to highlight exceptional restaurants.
Sign up experience to collect minimum details and permissions to personalize experience.
This included favorite cuisines, camera roll and location permissions. With these permissions, the app analyzes the camera roll, matching photos to restaurants to create a “taste” profile based on visited restaurants.
As the user continues visiting restaurants, our recommendation algorithm improves.
Carousel experience to enable users to quickly swipe between restaurant recommendations.
The UI design focused on delivering instant value to the user by providing personalized recommendations limited to the user’s current location.
The experience displays only one recommendation at a time and limits recommendations to only 10 restaurants.
This approach favors quality vs quantity and encourages users to carefully consider each restaurant recommendation.
Conversational interface to control their restaurant recommendations.
Once users have swiped across their default recommendations, they’re shown a guided workflow to enable them to filter restaurants based on cuisine, distance and timing.
Similarly to how a friend would ask “what you’re in the mood for”, the conversational experience asks a set of basic questions to streamline the filtering process if none of the recommendations meet their needs.
Social feed experience to enable users to view photos of the dining experiences of their friends and the broader community.
The core of the experience was the feed and profiles, which allowed users to discover experiences beyond their immediate location and follow other influential “foodies” in the community.
The goal of the experience was to open the app for “casual” browsing (aka reactivation) and encourage sharing of their own experiences (aka engagement).
Publishing experience to enable users to share their dining experiences.
The experienced leverages our photo-matching engine to enable users to browse photos more efficiently by grouping them by restaurants.
To encourage positive vibes, I streamlined the publishing experience to only allow sharing of photos and tagging posts with keywords.
Notification experience to proactively encourage users to share photos from their dining experiences.
The experience leveraged our photo-matching engine to notify users whenever they’ve taken a photo of a new restaurant and they’ve not shared yet.
This allowed us to increase the number of posts in our graph and improve retention by resurrecting users who’ve not shared in a while.
The MVP was designed, built and launched in around 3 months. As a result, we:
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