Applications of recommender systems in target selection categories of interest to customers. The ssumptions used in this paper. The likely problem in such a simple approach methodology for target sclcction is is that not all potential buyers may solicit deliberated on in the third section. Th promotional mails for new product scction following that is devoted to introductions in a category. Here,a expcrimental evaluation of the systen structured methodology is presented to and a discussion of its implications. The identify the prospects that are more paper concludes with a summary of the likely d to campaign, especially for new product introductions within a category of an online retail store PRELIMINARIES A typical recommender system, which This section describes the definitions, is aimed at generating recommendations notations al sumptions used in this at product category level, profiles paper. The notations used are made customers and identifies a set of likely distinct by making the in bold and products(categories of product) that are italics throughout this paper of interest to the. These systems also P A set of products (categories of generate Top-N products(categories of products) in the database is denoted as product)as recommendation in a ranked P=(P, P,.. Pn;, where n is the tot order. Apart from providing number of product categories in the Cs re recommender systems can also provide cn 1n sl ch a way that there are only rich insights in identifying prospects that Stock Keeping Units(SKUS) or brand are likely to purchase a new product names of products below this level. For e there is a Here. the use of such a novel products available in the databasc as methodology is investigated for this shown in Figure 1. In Figure l, at level specific class of target selection problem 1(root), there is the personal care and in c-cotmmeice. grooming category. At level 2, there is The primary contributions of this the dental care and hair care product paper are as follows: first, a novel egory. At level 3, each of the product methodology for target selection in categories in level 2 has sct of other internet business using recommender product categorics. Bclow this level systems is suggested. The methodology there are varicties of products uses basic concepts of collaborative (SKUs/brand names of products). So, the filtering and data miningfor total number of products in level 3( effectively selecting the target customers. this example) is taken as the total Secondly, the methodology is number of products in the database. experimentally evaluated on a real-life Tgtp The target product is tI data retailer in India. and its benefits customers need to be sclected and demonstrated. The suggested system can denoted as TgtP(TgtPE P erve as a useful tool for e-commerce CustomerDB. Customer database managers in devising effective denoted as Customer DB. consists of the promotional strategies The organisation of the rest of this products in P. More specifically, the is as follows: the following section database has data of the for <Ck, P> describes the definitions, notations and for each customer Ck in C. The Pi,s il a Henry Stewart Publications 0967-3237(2004) Vol 13, 1, 61-69 Journal of Targeting, Measurement and Analysis for Marketing 63 Reproduced with permission of the copyright owner. Further reproduction prohibited without permissionReproduced with permission of the copyright owner. Further reproduction prohibited without permission