IEEE BYTE VOLUME-3 ISSUE-1 | Page 16

    6      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!