A U.K.-based startup has made notable progress with a content recommendation engine that mines metadata and tracks usage patterns to help customers seek out and find content they might actually like.
Considering the almost bewildering array of linear and on-demand content now available to viewers, perhaps it's not surprising that the tool, developed by ThinkAnalytics Ltd., is gaining traction with pay-TV providers.
The company is trying to solve a freedom of choice paradox (apologies to Devo) faced by consumers -- they like having the breadth and depth of content but still need some help finding the content they might want to watch.
Recommendation engines are already popular among over-the-top (OTT) video providers such as Netflix Inc.. But ThinkAnalytics says its engine goes beyond the "light touch collaborative filtering" that some OTT players use by tapping into metadata and other information gathered not just from VoD usage and live TV channel surfing, but also by factoring in their preferences for non-video content such as books and games. The result of that work creates a "unique preference profile" of the customer, says Chairman Eddie Young.
And that process isn't limited to the set-top box. ThinkAnalytics says its technology can be built into guides driving navigation systems on tablets, smartphones, PCs and other connected devices that have become key to TV Everywhere strategies.
And the idea is gaining traction with pay-TV providers. The U.K.-based company claims that its technology currently is built into navigation systems that are in front of 70 million customers, and counts BSkyB Ltd., Virgin Media Inc., Telenet and Unitymedia GmbH (now part of Liberty Global Inc.) among its major customers.
It's also working with three unnamed service providers in North America, including two "very large cable companies" that are just about to deploy the technology, as well as a smaller IPTV operator, Young says.
It's maybe worth noting at this point that Comcast Corp.'s IP-capable X1 platform, which is set to launch soon in Boston, will sport a recommendation engine.
Why this matters
As cable continues to expand its content libraries and TV Everywhere efforts, the use of slick, cloud-based navigation systems probably aren't enough to help video customers discover content without going through a laborious process.
The use of recommendation engines will give pay-TV operators access to the sort of navigation tools that have helped to popularize OTT video services and should help to improve customer satisfaction levels.
And tying a recommendation engine to these new interfaces could help cable operators improve VoD sales levels well beyond what they've been able to generate from older, more limited menu-driven guides that require users to search for content on their own.
â€” Jeff Baumgartner, Site Editor, Light Reading Cable