Dynamically Tie the Right Offer to the Right Customer in Telecommunications Industry
This work addresses the challenge of effective marketing campaigns for telecommunications businesses, but it appears incremental as it builds on existing methods like genetic algorithms and decision trees.
The study tackled the problem of linking customer segmentation with campaign targeting in telecommunications by proposing a conceptual model that integrates these processes, resulting in more meaningful segmentation outcomes for marketers.
For a successful business, engaging in an effective campaign is a key task for marketers. Most previous studies used various mathematical models to segment customers without considering the correlation between customer segmentation and a campaign. This work presents a conceptual model by studying the significant campaign-dependent variables of customer targeting in customer segmentation context. In this way, the processes of customer segmentation and targeting thus can be linked and solved together. The outcomes of customer segmentation of this study could be more meaningful and relevant for marketers. This investigation applies a customer life time value (LTV) model to assess the fitness between targeted customer groups and marketing strategies. To integrate customer segmentation and customer targeting, this work uses the genetic algorithm (GA) to determine the optimized marketing strategy. Later, we suggest using C&RT (Classification and Regression Tree) in SPSS PASW Modeler as the replacement to Genetic Algorithm technique to accomplish these results. We also suggest using LOSSYCOUNTING and Counting Bloom Filter to dynamically design the right and up-to-date offer to the right customer.