Tipple is a location-based mobile app that provides users with on-the-spot, reliable happy hour and nighttime special information. For bars, it's a better way to increase their revenue stream by reaching out to a larger customer base with real-time menu deals information, which is otherwise only seen on chalkboards in limited capacity outside their establishments.
Time Frame: 3 weeks
Tools: Google, Google Forms, Google Sheets, Illustrator, Photoshop, Omnigraffle, Sketch, Invision
My Role: UX Designer, Lead UI Designer, Interaction Designer, UX Researcher, Project Manager
"A bunch of us were out one night and we weren't familiar with the bars in the area. It was just frustrating standing on the street looking for a good place for happy hours. There's not much out there for that" - Joshua B., Tipple CEO
That was the inspiration for the Tipple app. Everyone enjoys a good deal. Joshua realized there was a void for finding deals in the New York bar scene. My teammate, Sunjoo Lee and I, were brought on to review the current UX/UI design, provide suggestions and improve the on-boarding process for bar management. The company also wanted to incorporate a social media element to the app to increase the user downloads and encourage more bars to sign up.
With Tipple already in its beta stage, we conducted heuristics analysis on the app to determine best practices and potential improvements.
The major findings of our investigation:
1. Lack of uniformity on front end and the back end.
2. The process to fill information for bar management is tedious and confusing with many input fields and redundancies.
3. Multiple UI elements do not meet design standards.
We looked at similar competitive apps like Happy Hour Monster, Alcofy, and Drink Up and navigated each apps as users. Additionally, apps with similar business models like Groupon and Foursquare were included in the study.
We prepared and sent out ten survey questions to potential interviewees. We received thirty five responses and chose seventeen to interview. The interviewees varied in age and the frequency with which they went to bars. We also interviewed five bar management users with business located in different neighborhoods. The bars ranged from a local dive, an Irish pub, to a high end restaurant/bar.
"Me and a buddy went to this bar cause Yelp mentioned they had a happy hour but when we got there, the bartender told us they don't do that anymore. That was very annoying." - Justin K, Bar patron
From the interviews, we found that real-time information was important for people using reviews and deal apps like Yelp and Groupon. If the information is wrong even once, it is unlikely that the user will use that feature again.
Interviewing the bar management, we found them hesitant to use technology for self promotion. The restaurant/bar was the only one with an active social media presence, using their Instagram to promote upcoming events. Ease of use was key to them participating in Tipple.
While we interviewed the bar management on location, we were able to conduct some contextual inquiry as well.
• A group of friends hurriedly ordered multiple glasses of wine at seven dollars per glass, five minutes before Happy Hour ended.
• Regular customers come into the bar past the end of Happy Hour and still received the deals.
• At Beechers (a restaurant/bar), the bar was empty right before the start of Happy Hour. Within forty five minutes, the bar was filled.
• “Could you tell us the price for everything that is on the happy hour deal?”- a customer asking the bartender while looking at the specials chalkboard on the wall
An unexpected trend occurred when we began to look at the interview data. While all interviewees enjoy a good happy hour deal, there were more emphasis on variables like decor, ambience, location and music as motivation for frequenting a bar among the older group of interviewees.
Interviewees over the age of twenty seven were more selective about the bars they would go. The price was secondary. It was only the younger power users, patrons who frequent bars one to two times a week that were willing to go anywhere for a cheap drink.
The challenge for us would be having both groups of users staying engaged with the app.
Taking our synthesized data, we developed three personas that embody the needs of users: Stephanie is looking to find a low key bar for conversations with friends; Jake is looking for a bar close to work to network with coworkers over cheap drinks; Lucky Jack's is the owner of a bar that recently opened and is looking to bring in more customers.
Since up-to-date information was a big priority for users, the first feature we included was a timer counting down the end of happy hours on the bar profiles. Watching bar patrons' behaviors, we noticed a rush to get drinks orders in when Happy Hour was ending. We wanted a tongue-in-cheek way to play up that urgency.
Whether it was headcount or counting the register, every bar owner/manager has a system letting them know which days are the busiest. The second feature would make use of this knowledge. A crowd capacity meter would be implemented to let users know how packed a bar was on any given night. To enable bar management to input the information as quickly as possible, we created a check off system with designated categories for every night. Management users would only have to do it once. The meter would range from "empty" to "packed", which lets users know how crowded a bar is without having to walk in.
With the importance of ambience to users from our research, we created a filtering system for bar searches based on types of bar. Categories like dive, pub, sports were included. A second "vibe" filter was also included, allowing users to find the specific decor they want, whether it was a lounging, dancing, or just a head-bobbing atmosphere.
A smaller location-based feature was also implemented. In map view, purple location dots indicated which bars serves the user's happy hour favorite drink they inputted in their profile.
Before incorporating our features prioritization session, we created swim lanes within different user tasks to help us visualize the interaction of an user with Tipple.
Below are the first wireframes with the annotated notes from usability testing we conducted.