One of the things that seems to be sorely lacking from just about every osC, or osC derivative is support for Collaborative Filtering. Collaborative filtering is the dynamic suggestion of products based on the customers browsing preferences compared against other customers that have similar interests.
For example, osCommerce offers the ability for registered users to provide a rating and a review of products, and displays these ratings and reviews to help you, as a new customer, get an idea of how other people enjoyed the product. Taken this concept a bit further, I’ve seen some osCommerce stores offer an average rating from all of the customers that have rated the product, so that you can quickly get an idea of what the average customers thinks. However, your interests might not be the same as the average customer’s interests. Therefore their rating might not be as relevant.
A very good example of this is at www.netflix.com. NetFlix is an online DVD renter. Netflix takes the ratigns that you provide, and gives you recommendations based on the kinds of movies that you like, and based on movies that other people liked that also like the kind movies that you like.
Sound complicated? Get used to it. In 5 years, I suspect that every major online retailer out there is going to utilize this type of powerful targeted marketing. If you only like to watch ‘Sci-Fi’ movies, doesn’t it makes sense that when you visit my site, I display suggestions for movies that are in that genre?
With this kind of enhanced suggestion marketing available, merchants can instantly boost their conversion ratios. And with pay per click, and other web advertising methods becoming more and more expensive, I’d want to try to be as specific as possible with the products I display, rather than randomly throwing up any product that strikes my fancy.
Obviously, using a customers ratings, and comparing those against categories, manufacturers, and other peoples ratings with similar interests are one way to by able to provide collaborative filtering. I’m sure there are others. I’d like to come up with a few of my own algorithms, and try to package them into one of the osC projects I’m working on. I’ll let you know how it goes. If you have any ideas, or experience working with collaborative filtering, let me know.
