Taste

Overview

Taste is an entertainment discovery platform that connects users with movies and TV shows across streaming services through personalized recommendations. Rather than aggregating ratings from the general public, Taste generates recommendations by identifying users with similar taste profiles and surfacing their favorite content. The platform is designed to be gender-neutral and free from commercial bias, distinguishing it from traditional review aggregators.

Key Features

• Taste Profile Calculation - Users rate movies and TV shows to build a personalized taste profile that grows with each interaction and rating.
• Like-Minded Recommendations - Recommendations are generated from users with similar taste profiles rather than crowd-sourced ratings.
• Streaming Service Integration - Users can add their streaming subscriptions to discover available content across multiple platforms.
• Watchlist Management - Users can build and manage personalized watchlists of content they want to watch.
• Gender-Neutral Reviews - Peer reviews are decentralized and designed to remove gender bias and commercial influence.
• Free Content Discovery - Users can discover and watch free movies and shows available through integrated streaming services.
• Partner Matching - Users can connect with partners or friends to find content to watch together based on shared taste.
• Attribute-Based Browsing - Content can be browsed and filtered by genres, attributes, and streaming service availability.

Pricing

Platforms & Requirements

Taste is available as a web application at taste.io and as native mobile apps for iOS and Android. The platform is powered by The Movie Database (TMDb) and JustWatch for content data and streaming availability information.

Integrations & Ecosystem

• The Movie Database (TMDb)
• JustWatch
• Multiple streaming services
• Partner/friend connection features

Alternatives

Reputation

Taste is perceived as a community-driven alternative to traditional review aggregators, with emphasis on removing commercial bias and gender bias from recommendations. The platform has successfully raised $1.1M through community crowdfunding, indicating user confidence in the model. The approach of matching users with similar taste profiles rather than relying on aggregate scores appeals to users seeking personalized discovery, though the platform remains smaller than established competitors like IMDb and Rotten Tomatoes.