Posted by Danielle Goodman
Regardless of category, a vital app transcends basic functionality and user experience. It boils down to what makes an app something that a user doesn’t want to — or can’t — live without everyday. In our previous Designing for Place posts, we define what it means to be a vital app, while also providing a formula that you can measure your app’s usage to understand if what features you consider to be vital in your app aligns with what your users are actually doing.
Now, we’ll take these findings and apply them to a lifestyle app like Yelp. We’ll walk through some next-generation ideas we have for the app, using data like location and context to help deploy appticipation. As a result, Yelp will be able to better personify their users, serve the right experience to the right user at the right time, and increase overall app engagement.
The Yelp app has a fluid user experience. The functionality they care most about is served as 3 options in the center menu icon: Check In, Review, and Take a Photo / Video. On the current home screen, Yelp offers a “Nearby” mode that gives users a list of categories that it thinks you might be interested in. Users also can select a Monacle feature to more accurately understand where they are, what’s nearby, and how to get there.
The current home screen gives a list of categories that it thinks you may be interested in. Yelp also knows what time it is, and makes the relevant closeby suggestions - such as good places to go for lunch if you open the app around 12:00pm.
In this sense, Yelp has already taken the step towards integrating location into their user experience. Today, this location-based search serves users categorized recommendations based on their current location.
What we propose is taking their location functionality a step further with context. For example, what if Yelp was able to anticipate not only what their users needed at what time, but serve up recommendations based on what they know about the user’s behavior and intent?
Yelp isn’t a Skyhook customer, but we can’t help ourselves when it comes to imagining what the next generation of the app looks like with appticipation. By conducting our recommended usage analysis of their data, it would be possible to uncover how and when users are accessing which of their app’s functionalities.
Would you like to be part of the designing for place series? Contact us today to get started on an app usage analysis.
Using appticipation, Yelp could already know that a user is a “Coffee Lover” based on their location history and reviews. If Yelp added an “Appticipate me!” or similarly worded button to their screens, the app could serve up recommendations based on the type of information it has gathered and that it associates with a users’ persona. Yelp could automatically populate places it thinks their users might like based on this persona behavior, time of day, and positive / negative reviews on Yelp when the app opens.
Knowing location history and the persona of a user is also helpful when it comes to recommendations and reviews. Segmenting users by the kinds of food they review and the restaurants that they visit frequently would be extremely helpful. This would tell users who are looking at their reviews how reliable they are in a particular kind of cuisine. For example, a user with a very discerning sushi palette is looking for a good sushi spot. That user reads reviews about a place that made amazing sushi, got a 4 stars in aggregate and had very positive reviews and stories from most reviewers. So the user goes there with confidence.
But what happens when it turns out that this place does not live up to the users expectations and the sushi, in spite of the descriptions by the people who reviewed the restaurant was in fact terrible. It turns out that the people who gave the reviews were not at all qualified to review sushi. In fact, all of their other reviews were for hamburgers, burritos and other fast food. This was the fast food lover’s sushi joint.
Knowing that the user is a fast-food lover gives you more insight into the type of food the reviewer loves and how similar their tastes are to yours.
If Yelp worked with stores and restaurants to deploy a location-based venue mode, they could offer in-store incentives to encourage purchases when they walk into the store or restaurant. For example, a chain of restaurants could have each of their locations geofenced so that when users walk by or into the restaurant, Yelp offers them 10% off appetizers if they write a review within 2 hours. This encourages users to engage with the app, provides reviews for the restaurant, and encourages menu purchases in exchange for participation.
By having these other prompts, you can add context to your app and anticipate your user’s next move and help to make their lives easier and your app more vital.