Web mining technologies for customer and marketing surveys

Abstract

Purpose

The purpose of this paper is to illustrate the usefulness and results of applying web mining as extensions of data mining.

Design/methodology/approach

Web mining is performed using three selected software to databases related to customer survey, marketing campaign data, and web site usage. The three selected software are PolyAnalyst^® of Megaputer Intelligence, Inc., SPSS Clementine^®, and ClickTracks by Web Analytics.

Findings

This paper discusses and compares the web mining technologies used by the selected software as applied to text, web, and click stream data.

Research limitations/implications

The limitations include the availability of databases and software to perform the web mining. The implications include that this methodology can be extended to other databases.

Practical implications

The methodology used in this paper could be representative of that used for managers to manage their relationships with customers, their marketing campaigns, and their web site activities.

Originality/value

PolyAnalyst is applied to analyze text data of actual written hotel comments. SPSS Clementine is applied to customer web data collected in response to several different marketing campaigns, including age, gender, and income. ClickTracks is applied to click‐stream data for Bob's Fruit web site to generate click fraud report, search report with revenues, pay‐per‐click, and search keywords for all visitors.

Citation

Segall, R.S. and Zhang, Q. (2009), "Web mining technologies for customer and marketing surveys", Kybernetes, Vol. 38 No. 6, pp. 925-949. https://doi.org/10.1108/03684920910973162