While content variety may be a good starting point for success, as well as a huge sell point when it comes to acquisition, it’s the browsing experience that can get the touchdown when it comes to user retention. A good recommendation engine can make for an emotional response as it caters directly to the user’s needs, and whereas word of mouth was the standard and common practice, new business models have developed a more efficient and fail-proof way of getting the right content towards the right person.
So, the next time your clients get home and ask themselves “What will I watch this evening?”, you can be pretty sure that their favorite subscription service has already gathered enough data from previous viewings and other users in order to minimize their browsing effort. It may not get them the perfect movie or TV show, but it will at least give them the best possible choice according to what’s available at the time.
So, how does it work exactly?
Well, recommendation engines can go through various complex shapes and take different twists and turns into achieving their goal, but let’s make the rounds with 2 recommendation engines that can generally be applied.
This concerns the similarity of the movies or tv shows being recommended. If you like an item, the recommendation system will show you another with similar characteristics. It’s prone to be successful when the properties of each item are well defined.
Memory-Based Collaborative Filtering:
Taking at least two users with the same viewing habits you can have a pretty accurate idea that what user A saw, can be recommended to user B.
WeTek goes way beyond this and uses state of the art analytics that can, not only get users the right content at the right time, but also display the content you would like to see featured next to the recommendations. This way we can assure that the message comes across to the right target, making it appealing to each different audience.