Executive Summary

Many consumers — from busy hobbyists who split their leisure time across Netflix, Steam, Kindle and podcasts to power users tracking hundreds of titles — struggle with fragmented watchlists, duplicate discovery efforts, and poor memory of what they intended to read/watch/play next. This problem affects a large, active cohort: we estimate a 500 million global opportunity (addressable market $12.0B at $24 ARPU/year), and while the market score (88/100) and revenue potential (76/100) look attractive, pain points are concentrated among avid media consumers who invest time in curation and discovery rather than casual users. A viable product would be a unified tracker that ingests consumption history across movies, TV, books and games, normalizes metadata into a single personal media graph, and surfaces cross-format recommendations and consolidated watch/read/play lists. Key features would include importers for existing trackers, a single timeline and wishlist, AI-driven embeddings to recommend cross-format transitions (e.g., books that match a show’s themes), and privacy-respecting profiles with optional social sharing and platform-agnostic export. This is an attractive moment because streaming fragmentation and the rise of platform-specific exclusives have increased the value of consolidation, and cross-media consumption is mainstream: more people now switch formats mid-journey, creating additional recommendation signal. Crucially, recent advances in LLMs and embedding models lower the technical barrier to deliver nuanced, personalized cross-format recommendations at scale, which supports the $12B addressable estimate and the stated ARPU. To stand out against medium competition (Trakt, Letterboxd, Goodreads, and a dozen niche apps), focus on one unified metadata model, high-quality import/export tooling, and demonstrable cross-format recommendation lift; monetize via a modest subscription (the market supports ~$24/year ARPU), affiliate purchases, and premium social features. Challenges are real: integration with closed platforms, metadata normalization, user acquisition costs, and limited defensibility without proprietary behavioral data, so early emphasis should be on building sticky core utility (accurate history + seamless imports) and transparent privacy to earn users before layering recommendations and social features.

Market Opportunity

Unified tracker for movies, TV, books and games targets a $12.0B = 500M potential users x $24 ARPU/year (global entertainment trackers and active media consumers) total addressable market with medium saturation and a year-over-year growth rate of 8-12% (consumer apps around media discovery & tracking).

Key trends driving demand: Streaming fragmentation -- more services pushes users to consolidate watchlists and discovery in one place.; Cross-media consumption -- users increasingly switch between books, games and screen media, creating value for cross-format discovery.; AI personalization -- LLMs and embeddings enable nuanced recommendations across different media types and personal histories.; Open data/APIs -- healthy public datasets (TMDB, IGDB, Trakt, Goodreads) speed integration and catalog completeness..

Key competitors include Letterboxd, Trakt.tv, Goodreads (owned by Amazon), HowLongToBeat / IGDB (adjacent for games), Notion (workaround).

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Unified tracker for movies, TV, books and games

Executive Summary

Market Validation

Market Opportunity

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