CASE STUDY - PERSONAL
Starlit
Starlit is an entertainment app dealing with facial recognition technology. It allows users to face swap with stars from their favorite movies. Users are able to share their clips with friends through the app via messaging or other social media.
User Research, UI/UX Design
Many apps are trying to get in the face swap market but few are using it well and even less are making a profit off of it. Most of these apps are merely copying and pasting a face onto another, which is fun but is poor in quality.
Being a new app, I needed to understand competitors and the target market for this product. To do this I found as many similar apps I could and did a competitor analysis. In doing this, I was able to find a few things to focus on in order to stand above the competition.
Poor Quality Face Swap
Simplify The Process
Needs To Make Money
01.
Using machine learning technology for face swap.
02.
Eliminating steps in order to upload and share content.
03.
Have ads at the end of each clip saying the sponsors name.
Matt needs to choose a film and character then he needs to enable the facial recognition feature.
Rachel needs to record herself and then send her clip to her friends.
A walk-through of the app is the first thing the users will see. These pages will have GIFS to help users understand the process of choosing a scene and character, as well as using facial recognition.
The explore page will also act as the home page. Users can browse through different categories of scenes. Once users choose a scene, they will choose a character they want to swap with.
The app uses machine learning technology for facial recognition, which will provide a seamless face swap between user and the chosen character. The users need to look at the screen and rotate their head. The lines around the circle will turn green once they are done.
When the user is happy with the recording, they can share their video to social media or save the video to their phone.
