Best Practice: Web-mining case study: An Internet radio website
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Keywords: personalisation, customer relationship management (CRM), e-business, e-commerce, Internet marketing (e-marketing), data mining
Best Practice Web-mining case study: An Internet radio website Jesus Mena and Raymond Pettit Received: 21 February 2001
It is of the essence of a good case study that it should include an evaluation of activity being studied. The following case is, however, so recent that it is premature to provide such an assessment. We thought the material interesting enough in its own right to print as it stands; the authors have promised to provide a second bite at the cherry in the shape of an evaluation when that can be done Ð perhaps in time for our next issue, or failing that the next but one.
Abstract Data mining is the key to customer knowledge, intimacy and pro®tability. Today, businesses are overwhelmed with data, prompting the thoughtful and consistent use of analytic techniques that can enable understanding and knowledge of the customer in ways that can maximise relationships and the opportunity for pro®t. This case study concerned an Internet radio station striving to become more intelligent about their visitors. The exploratory phase combined data-mining analytic techniques and appended third-party demographic and lifestyle information. Key segments of the visitor population could then be isolated by infusing marketing logic and rules that emerged from the results of the analysis. Visitors were identi®ed by heavy listeners; music preferences; and non-listeners. In the ®nal analysis, the data-mining process informed the radio station that traditional business principles apply to the Internet, and revealed the importance of de®ning clear business objectives, the critical need for quality data and data preparation, and that long-term survival is dependent on integrating data-driven results with business logic and experience.
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Jesus Mena Lumina Americas, EVP, WebMiner, 670 Broadway, Suite 2, New York, NY 10012, USA Tel: 1 212 813 6761 Fax: 1 212 253 9799
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Data mining is the key to customer knowledge, intimacy and pro®tability. For years marketers have been using databases to construct a picture of their customers and have turned to data-mining tools and associated techniques to extract the most valuable information possible to drive marketing decisions. Arti®cial intelligence (AI) technology (in the form of data mining) has been used to: Ð stop `churn' (or customer attrition) by cellular phone companies Ð manage ®nancial and risk portfolios by ®nancial services ®rms Ð detect fraud and set pricing by credit card companies
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Web-mining case study Ð lift response rates by mail cataloguers Ð analyse `shopping carts' (market basket analysis) by retailers. In today's hyper-competitive marketplace, the creative and strategic use of customer information has become critical to survival. And nowhere is more `data
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