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| Author: | Boone, D. S. Roehm, M. |
| Title: | Evaluating the Appropriateness of Market Segmentation Solutions Using Artificial Neural Networks and the Membership Clustering Criterion |
| Journal: | Marketing Letters
2002 : VOL. 13:4, p. 317-334 |
| Index terms: | MARKET SEGMENTATION NEURAL NETWORKS STATISTICS |
| Language: | eng |
| Abstract: | The "appropriateness" of a given segmentation solution is a key consideration in all marketing segmentation studies. By appropriate, it is meant that not only has the optimal segmentation solution been identified, but also that the proper number of segments to market to has been correctly specified. This research focuses on the second, and more fundamental, issue of determining the appropriate number of segments in a marketplace. If the appropriate number of segments is over-specified, marketers may over-segment the market and treat audience segments separately that could effectively be treated inclusively. Conversely, if the appropriate number of segments is under-specified, marketers may under- segment the market and fail to identify distinct, viable segments that should be marketed to separately. |
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