Rudelle Blogging

Recommendation engines which generate real-time personalized recommendations are based on very complex mathematical algorithms. To source such a system, several options are possible ranging from complete in-house development to fully packaged commercial solutions like Criteo.

What are the different types of approaches?
In general, we distinguish two major types of approaches:
- « Content » approaches, based on the analysis of intrinsic product characteristics,
- « Collaborative » approaches, based on the relative user profiles.

To be efficient, content approaches need a complete preliminary configuration of products. Unfortunately, this is barely possible in an open environment. Moreover, results are in general very disappointing in terms of predictive accuracy. For these reasons, content approaches are losing ground on the internet.

On the other hand, collaborative approaches involve two major constraints:
- algorithms which are much more complex than content approaches,
- very high computing resources.
Consequently, very few collaborative methods are capable of managing big volumes of data with acceptable response times.
Conclusion : before rushing on a cheap solution, make sure you won't get stuck in the middle of your ramp up. Otherwise, you are better off doing nothing!