Monthly Archives: June 2010

Recommendation engine: books and beyond

Recommendation engines are the software applications that take customers’ shopping behavior and recommends them what other products they should consider buying. Recommendation engine plays two critical roles. First, it helps in personalizing customer experience on the web and in-turn makes online shopping a better experience. Second, it helps drive revenue for online stores by making sensible and relevant product suggestions to the customers., the online retail giant, has spearheaded the innovation in this space. Everything from search results to the home page to emails sent out to customers are personalized for every customer with relevant recommendations based on the customer’s shopping pattern.

Amazon recommendation engine does wonders for the online bookstore. It understands a customer’s reading pattern from their search and buying history and recommends the customer similar books. The engine takes into consideration the book genre, author, buying pattern of the customer, buying pattern of other customers who bought similar books and a bunch of other criteria to display relevant recommendations. Over the years, Amazon has been able to sell millions of additional books and tap into its long tail with the help of the recommendation engine.

Now let’s talk about the scenario beyond books. Over the years, Amazon has expanded its retail footprint by selling products in more than three dozen categories. It sells everything from home appliances to jewelry. As expected, Amazon has adopted the recommendation engine for its other product categories as well. In many cases like movies, video games and music the adoption was very straightforward from books. With the help of relevant recommendations, Amazon is able to provide customers with a richer shopping experience in these categories.

Though in some other cases like home appliances, cellphones and gardening products, there’s a critical difference which makes the recommendations shown to the customers irrelevant. In categories like these, the online mega-store does not take into consideration the fact that if the customer has already bought the product from them, they won’t buy it again for sometime. I experience this when I bought a vacuum cleaner from Amazon last week. Even after buying the vacuum cleaner, my homepage has recommendations of vacuum cleaner and I am receiving email newsletter with attractive offers on vacuum cleaners. This would have made a lot of sense if I bought a marketing book and received recommendations for other marketing books, but when translated to a vacuum cleaner, this becomes an annoying experience. How can it be made better? Maybe by considering broader area of home appliances or cleaning products for recommendations than the narrow category of vacuum cleaners.

In all, the recommendation engine is a great innovation to enhance online shopping experience. But when applied to newer territories, there are lots of opportunities to make them smarter and more efficient.