How ReelRecs finds movies and shows you’ll love

The streaming world, personalized to you

A thriller you love on Netflix can tell us something about the drama you might love on Apple TV. Your taste travels across services. Your recommendations should too.

ReelRecs licenses PeerLogix’s full historical viewing collection for model training: more than one billion viewing observations recorded over more than ten years. That history includes viewing of titles across Netflix, Disney+, Apple TV, HBO Max, Paramount+, Peacock and other major streaming services, across countries and markets.

The benefit is a wider starting point for finding your next favorite. Viewing patterns help our engine learn which titles connect, including films and shows on different services. Your own ratings tell it which of those connections fit you.

These figures describe PeerLogix’s accumulated viewing collection. Its methodology explains the household observations and title coverage. The ReelRecs customer page documents the licensed relationship.

Why a few ratings can get you started

You bring your taste. The engine already has a broad history of what people watch.

Start by rating six familiar movies or shows in ReelRecs. Those reactions give the recommendation system a first picture of your preferences. It can apply what it has learned from viewing patterns and title information without waiting for you to build years of watch history inside the app.

A new ReelRecs account therefore starts with an established recommendation foundation behind it. As you rate more titles, your profile gains detail. A comedy you loved, a thriller you disliked and a drama you found average help it distinguish your taste from someone who simply watches the same genres.

You do not need to connect your Netflix account or hand over the passwords to your streaming services. Rate familiar titles, choose your services and open Discover → Recs for you.

What each kind of information contributes

Information	What it helps ReelRecs do	What you get
PeerLogix viewing history	What it helps ReelRecs doLearn relationships between titles from viewing patterns across services and markets	What you getA broad foundation for discovery, including connections outside one catalog
Your ratings and comparisons	What it helps ReelRecs doIdentify your favorites, disappointments and relative preferences	What you getRecommendations shaped around what you enjoy
Information about each movie or show	What it helps ReelRecs doConnect story, people and other title characteristics	What you getA reason you can recognize behind a personal pick
Current provider listings	What it helps ReelRecs doShow viewing options for the title and your country	What you getA route from a recommendation to where you can watch

Someone watching a film is different from someone loving it. That is why ReelRecs combines viewing patterns with your explicit likes and dislikes. The historical data supplies connections; your opinions help make those connections personal.

A recommendation beyond the obvious sequel

In a captured ReelRecs example, an established profile received Killers of the Flower Moon with a personal Rec Score of 8.0. Its explanation connected the film with two different favorites: GoodFellas, rated 7.8, and Forrest Gump, rated 10.

Martin Scorsese supplies a connection to GoodFellas. Writer Eric Roth supplies one to Forrest Gump. The recommendation brings those parts of the viewer’s taste together in a different story. It is a useful illustration of why a profile containing several kinds of films can be more revealing than a single genre label.

See the recommendation and the ratings behind it. The example shows an actual recommendation and a shorter presentation of its explanation; it does not reconstruct every calculation inside the model.

Does that turn into useful recommendations?

Our recommendation evaluation put a viewer’s favorite ahead of a disliked title 94% of the time, versus 50% for the placebo comparison. In a separate evaluation, the top 20 picks recovered about 27 times as many favorites as ranking by ReelRecs’s crowd scores. The results and methods explain both measures.

The everyday payoff is easier to describe: interesting suggestions that feel like they belong to you.

App Store reviewer Yummyohan described rating Hereditary, Caveat and I Am Legend as loved. They reported that the recommendations matched their horror taste and brought up several films they would consider watching. Their public review gives a concrete account of familiar favorites becoming new possibilities.

Another reviewer, Maggeih, described being a picky viewer and already saving many promising movies and shows after a short time with the app. Those are the outcomes ReelRecs is built around: recognize what appeals, keep the next good choice ready and spend less of your evening searching.

Find your next watch across your services

Select your streaming services in Discover → Recs for you → Platform → Apply. The filter is free to use and includes paid streaming services. Your suggestions narrow to subscription listings on the services you select.

Open a title for its Rec Score, explanation, trailer and Where to Watch. Watch through the provider using its usual subscription or rental offer. Save another promising suggestion in Bookmarks for tomorrow. When you are choosing with someone else, Watch+ combines the ratings of joined members and shows who wants to watch.

You can make ReelRecs your first stop before opening a streaming app. It answers both parts of the evening: what fits your taste and where to find it.

Questions about the viewing data

Is ReelRecs learning only from its own users?

ReelRecs uses its viewers’ ratings together with a much older licensed viewing foundation. PeerLogix’s historical collection spans more than a decade, more than a billion observations and more than 70 million households observed over time. The recommendation engine can use those learned connections from your first rated profile.

What is the relationship with the named streaming services?

Netflix, Disney+, Apple TV, HBO Max, Paramount+ and Peacock are examples of services represented in PeerLogix’s viewing coverage. PeerLogix supplies the licensed data to ReelRecs through its own observation technology. The service names describe that coverage, rather than endorsements or direct data partnerships with ReelRecs.

Does ReelRecs have access to the full collection?

ReelRecs’s license includes the entire PeerLogix historical viewing collection for model training. The billion-plus figure describes that source collection. Training prepares and selects useful signals from the data to build the recommendation model.

Does a large viewing history mean everyone gets the same picks?

Your ratings are what make the recommendations yours. Two people can love some of the same films and disagree on others. ReelRecs uses their individual preferences to predict personal fit, while Friend and World Scores remain separate perspectives.

What do I have to do first?

Get ReelRecs free on iPhone or Android and rate six titles you know. Open your personal picks, select your services and find something you look forward to watching.