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on like-minded users. The algorithm aggregates the items consumed by most similar users,
eliminates those items that the target user has already purchased or rated, and recommends
the remaining items to that user.
E-Commerce has an edge over the Brick-and-mortar stores where in THE LONG TAIL
phenomena comes into picture. Retail stores have limited work space which makes them to sell
the commodities in descending order of their popularity, whereas in online stores there is no
such issue. The seller can sell as many products he wants.
Because users of an on-line store would wish to view all of the items available in that store,
there is a need to recommend selected items to individual users. This means that
recommenders must be designed to recommend items both from the head as well as the long
tail.
In order for any organization to successfully implement a recommender strategy, the following
best practices apply:
1. Recommendation is aimed at improving the customer dialogue. The heart of recommendation
lies in gaining insights into your customer. Customers typically require an open, trusted
relationship before they will share such insights with you.
2. Keep the big picture in mind, but start small: A successful recommendation strategy will
probably feature a combination of different recommender types, but implementing them all at
once is not advisable.
Recommendations in short works for the seller as mouth publicity and for the buyer as a friend's
advice!