WebMining for Profitability provides a central reference to the components, issues, techniques and technologies for aggregating, enhancing, mining, and leveraging web data for personalization and profitability. This is the only book that provides guidance for categorizing the dozens of personalization products and services in the market or assessing their effectiveness. The book has a companion website that will be continuously updated. The site will enable readers to chat, mail sections to colleagues, and register for a newsletter on new profitability products, services, upgrades, announcements, and profitability case studies.
This is a powerful manual for e-businesses on how to achieve profitability by leveraging web analytic tools, techniques, services, and strategies.
Sprache
Verlagsort
Verlagsgruppe
Elsevier Science & Technology
Zielgruppe
Illustrationen
Approx. 100 illustrations; Illustrations
Maße
Höhe: 235 mm
Breite: 178 mm
Gewicht
ISBN-13
978-1-55558-265-4 (9781555582654)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Jes?s Mena is a data mining consultant and a former artificial intelligence specialist for the Internal Revenue Service (IRS) in the U.S. He has over 15 years experience in the field and is author of the best-selling Data Mining Your Website and WebMining for Profit. His articles have been widely published in key publications in the information technology, Internet, marketing, and artificial intelligence fields. He can be contacted at mail@jesusmena.com.
Autor*in
CEO of ProMiner, Inc., Alameda, CA, USA
Marketing Technology; Web Data Components; Offline Demographics; Log Analyzers and Packet Sniffers; Collaborative Filtering Software; Data Mining Suites; Webhouses; Ad Networks; E-mail Management Systems; E-commerce Suites; Electronic Customer Relationship Management Systems (eCRMs); Application Service Providers (ASPs); Personalization, Profitability and Privacy; A Personalization Case Study
