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Recommendation Engine Revenue Chugging Along

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Recommendation Engine Revenue Chugging Along

A s the amount of content and number of video services available grows, both OTT and traditional pay TV video providers recognize that offering content suggestions and personalizing the experience increases the value of the service in the eyes of the customer. Otherwise, viewers are less likely to turn on a service when they have to search for something to watch on their own. When a service is not used, the viewer drops their subscription or stops using the service. To provide recommendations, providers are turning to third-party recommendation engines rather than developing their own.

Revenue for the video recommendations engine market almost doubled from $33 million in 2014 to $68 million in 2015, mainly due to pay TV providers adding a recommendation feature to their video offerings. In 2016, we forecast revenue will grow to $95 million as there are many pay TV providers who have yet to work with a third-party recommendation engine vendor, especially in emerging markets such as Asia and Latin America.

Western Europe remained the largest generator of recommendation engine revenue in 2015, with North America second. Many providers in both regions have adopted third-party recommendation engines to stave off competition and churn, with the penetration of subscribers higher in Western Europe than in North America. The higher ARPU in those regions generates more revenue that can be used to offer features like recommendation engines.

Vendors are competing with internally developed engines. Those using internal systems, like Netflix Inc. and Inc., are not factored into our vendor revenue forecast.

Changes in the market over the last year show the evolution of the recommendation engine market. Vendors are acquiring new customers, as there is agreement that having a recommendation engine is very important to video providers' businesses. Netflix has claimed that its recommendation engine saves $1 billion per year because it reduces churn. Vendors continue to improve their algorithms with spatial/temporal filtering, which takes into account viewer habits on various devices as well as at certain times of the day.

Video recommendation engine vendors range from small startups like Spideo to vendors like TiVo Inc., Ericsson AB and Adobe Systems Inc., which each have large businesses outside of recommendation engines. Some of the smaller vendors are expanding their product portfolios as well. Jinni targeted ads for the entertainment industry. ThinkAnalytics launched the ThinkBigData analytics platform.

Currently there is overlap among customers. For example, one vendor's engine may be adopted in the TVE service and then a different engine adopted for the VOD service to the set-top box. In some cases, the same vendor is able to expand its relationship with the customer by bridging to other services. As silos are broken down, we expect MVPDs will move away from multiple vendors to one recommendation engine vendor.

For further insight into recommendation engine vendors, their customers and revenues by region, see the full article and supplemental data here.