Voting Platform Ranker Debuts TV Recommendation Tool

In the US, consumer voting web platform Ranker has launched an app called Watchworthy, which uses a proprietary machine learning platform to deliver personalized TV recommendations.

Founded in 2009 by entrepreneur Clark Benson (pictured), Ranker's platform is used by crowds to vote on their favorite item in a list - such as the 'best athletes in history', 'worst movies of all time', and the 'best lip gloss'. The firm attracts more than 40 million monthly unique visitors and over one billion votes, and uses power Ranker Insights - a machine learning platform providing access to psychographic correlation data - to deliver personalized consumer recommendations ('if you like X, you'll also like Y, Z'), as well as audience insights.

The new app, Watchworthy, applies first-party correlation data amassed over a decade from the one billion votes on Ranker.com. According to the firm, in just 60 seconds of liking and disliking shows, Watchworthy discerns what type of shows the user is likely to love or not across all networks and streaming services; and then converts a phone or tablet into a smart, personalized remote, through which users can immediately start watching shows from their watch list directly on the device, or cast to a TV.

Recommendations are made across every streaming service on both old and new shows that match personal taste; with shows given a 'worthy' score based on the percentage likelihood that they are worthy of the user's time. According to Benson, 'with so much TV out there, it's only getting harder to pick new shows across all of the new streaming services popping up... Watchworthy is designed to relieve the paradox of choice by accurately recommending what is worthy of your time, where to find it, and how to watch it'.

Web site: www.ranker.com .