LinqTV Suggest-IQ
Show every viewer the title they did not know they wanted
A large catalog is only valuable if people can find their way through it. Suggest-IQ is the AI personalization engine that learns from how your audience watches and turns that into recommendations which lift engagement and keep subscribers around.
See it on your catalogDiscovery is the product
The biggest streaming services do not win only on content; they win on knowing what to put in front of you next. A viewer who opens your app and immediately sees three things worth watching stays. A viewer who scrolls a generic grid and finds nothing closes the app, and eventually cancels.
Suggest-IQ brings that same discovery muscle to your service without a data-science hire. It plugs into the catalog and viewing data you already generate and starts personalizing the experience for each user.
What it changes
More watch time
When the next great title is one click away, sessions get longer and catalogs that felt empty suddenly feel deep.
Lower churn
Subscribers who keep finding things to watch keep paying. Personalized discovery is one of the strongest retention levers a streaming service has.
Better catalog ROI
Surface the long tail, not just the homepage hits, so the content you licensed actually gets seen and earns its keep.
How Suggest-IQ works
Signals in
Suggest-IQ learns from plays, completions, search, watch time, ratings and device context, building a picture of what each viewer and each title is really about.
Models rank
Recommendation models combine collaborative patterns (people like you also watched) with content similarity (titles like this one) to score what to show next.
Surfaces out
Results power continue-watching, "because you watched" rows, personalized homepages, search ranking and email re-engagement, across web, mobile and TV.
Make your catalog feel bottomless
Let us run Suggest-IQ against a sample of your catalog and viewing data so you can see the lift for yourself.
Request a demo