More than 1 billion users rely on review sites like Yelp and IMDB to get recommendations, generating over a billion dollars in advertising revenue every year. Oddly, these platforms do not offer a truly personalized experience. Why should two people with drastically different tastes see the same ratings and reviews?
Taste uses predictive algorithms to deliver personalized reviews across products and services. By rating what you like and dislike, the app generates a personal "Match%" for every item. Not only will you save time finding what to watch (and eventually what to read and where to go), building a taste profile is also surprisingly addictive.
The Match% is computed from the ratings of people who are the most similar to you in taste. This peer-to-peer method will allow us to service a wide range of categories with the same user experience and algorithm. It also means we will be able to suggest what book you will enjoy based on the music you love and the restaurants you frequent—it's helping you get recommendations from like-minded people all around the world.
- 300,000 registered users.
Already one of the top search results on Google and both app stores.
- Upcoming categories include music, books, podcasts, games, apps, food & drink, travel, events, anime & comics, fashion, gadgets, articles, and even recipes.
- Personalized results that come from humans, not a machine.
App lets you compare tastes with friends to find what to watch together or a restaurant you will all love.
By consolidating reviews across categories and making them personalized, you would only need a single Taste profile across the web. Our long-term vision is to replace all rating and review platforms with one app and turn "Match%" into the new standard for product discovery.