Tinder

With 20 billion matches to date, Tinder is the world’s most popular app for meeting new people. Think of us as your most dependable wingman—wherever you go, we’ll be there. If you’re here to meet new people, expand your social network, meet locals when you’re traveling, or just live in the now, you’ve come to the right place. We’re called “the world’s hottest app” for a reason: we spark more than 26 million matches per day. How many dating apps do that?

I redesigned the Tinder app for fun because I’ve met women online and I like to work on products I actually use. I have always had an interest in the idea of love and relationships. After my girlfriend broke up with me, it was difficult for me and I wasn’t doing something right. I had to find a real solution rather than listening and following advice from people who had problems in their own relationships. I searched for experts and read books from the top psychologists, relationship counselors, persuasion, and pick-up. 

It took me 2 months to finish this project. I spoke with users and I discovered that their main pain point was not being able to target a specific ethnicity and Tinder being too broad. For example, maybe one day the user was in the mood and looking for a German woman and the following day preferred a Brazilian woman. Similar to how on Yelp you can search for different foods—Chinese, Mexican, Thai, American, etc.

MY PROCESS

MY ROLE

I was responsible for every aspect of design— heuristic analysis, surveys, interviews, creating an affinity diagram, sketching concepts, and low/high fidelity prototypes.

RESEARCH

I went through and used the Tinder app and noted any observations I made. I included possible solutions for a more intuitive experience.

INTERVIEWS

From the interviews, the common pain point was not being able to filter preferences by ethnicity because users want control of matches for a given day.

Other pain points I discovered was that Tinder matches were of average quality, some users aren’t looking for “hook-ups” and want a preference “looking for a relationship,” fake profile accounts, men looking for women and being matched with men, users being matched with people that are far away, etc.

AFFINITY DIAGRAM

I organized and grouped all the pain points users had challenges with so I can better understand and empathize to find a solution. I grouped the pain points into 2 categories—functionality with the app and personal problems.

PERSONA

I created personas based on the research. I grouped each kind of person to be more targeted to cater to the user needs. Sean is grouped with people looking for a long-term relationship on Tinder.

PROBLEM

From my research, I learned user pain points included: Women having more options and guys feeling disposable (10,000 swipes, 1000 messages sent, 10 replies, 3 dates), low attention span, getting rid of people looking for “friendships,” people feel they don’t fit in with the definition of mainstream beauty, etc.

I noticed a trend from the data that the users wanted to filter by ethnicity so I decided to tackle that pain point. Users could spend hours swiping and swiping on a broad pool of matches not targeted to their preferences.

For example, with Yelp, instead of searching for something broad like “food” and getting results like American, Mexican, Asian, Brazilian, etc. A user can get more specific to their preference like Mexican food.

SOLUTION

I learned that users wanted to have a filter for ethnicity to have variety and narrow results, so I sketched out different variations and possible solutions to filter by ethnicity.

 

I have two solutions for creating a more specific and targeted system. Users can answer a questionnaire and have the algorithm narrow down matches. Or the option below, at the Tinder home screen there would be options for ethnicity preferences before swiping potential matches.

THINGS I LEARNED

I tested out the design with my friends and they found it easy to use and liked the filter feature. If I had access, I would be curious to know what challenges Tinder is currently facing.

Common problem users were having was matching with spam accounts. I wasn’t sure how to solve that problem, but I spoke to my friend and he had an interesting idea of utilizing face recognition where new users would have to verify their account by cross-checking their driver’s license and scanning their face. But I’m not sure how users would feel about sharing personal information like their driver’s license.


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