Moving Beyond Recommendation Engines, does personalisation work or are we doomed!

 

This is driven by a thought - is there a flaw in personalisation?

Most TV service providers now recognise that there is a need to incorporate recommendation as part of their content discovery mix - according to TV Genius. Depending on the provider, this can be a matter of personalising the video-on-demand store, promoting premium TV channels, or driving viewers to video-on-demand services from within the traditional EPG. All of these solutions have appeal to different demographic groups, but recent research they have conducted shows that a much broader content discovery solution is required.  After all, not every user has the same exact content discovery needs; while some viewers know exactly what they want, others are simply browsing for something new to watch.

 So segmentation could look like ..... with each group having very different content discovery behaviours.

1. Socialites: Influenced by friends and family, channel surfing, and web and mobile

2. Progressives: Influenced by web and mobile content

3. Reactives: Influenced by channel surfing and on-air trailers

4. Traditionals: Influenced by newspapers, magazines, and on-air trailers

5.  TV addicts: Influenced by on-air trailers, the EPG, and web and mobile content  

So the question is does personalisation work or is it broken.....

In the book I looked at this problem and concluded that you needed two types of input/ feedback for personalisation/ recommendation to work.  Your own personal preferences (for improvement and refinement) and trends from a wider community (for colour, flavour and breath)

This is so much more eloquently put by Eli Pariser: Beware online "filter bubbles"   in his TED talk and read the comments at the end.

 However, I agree with the outcome - if we depend on the algorithm to much we are doomed.