I am trying to identify a ML technique to score products based on the number of times the product was "viewed", "clicked" and knowing the "cost per click" for each product. Given the product ID and category ID, how can I proceed to score each product?
I am sure I have to coarse classify them (some have no clicks, but views, some have both, some have none)? Since there are 1000s of products... Any tip?
I guess the technique is also used in e-commerce to design recommender systems, like based on popularity of a product. Any one can shed some light?
*Edit: Though the suggestions here are interesting, still I couldn't figure out best way to do this.