Optimization Model For Mobile Marketing Strategy Based On Customer Segmentation

With the rapid increase of mobile users, Mobile marketing is becoming an important marketing approach adopted by large emporiums. The proliferation of mobile phone users create new opportunity for development to mobile commerce and precise marketing. The convenience, low cost, customizable, real-time of mobile marketing, has been widely recognized, and it also becomes a exchanging platform between merchants and customers.However,The current mobile marketing model has some limitations on prediction of future locations of customers. The status quo of mobile marketing is that the message sender do not make full use of the personalized marketing advantage of SMS, and often send the same message to all the members, therefore, the effect is often not ideal. How to develop effective mobile marketing strategy, so that businesses can target customers effectively and send personalized marketing messages to customers, become difficulties in current mobile marketing research.Against the personalized mobile marketing issues which is increasingly prominent in recent years, this paper explore how to use mobile media to deliver critical information at the right time and place in a suitable way to the target customer groups more effectively. An optimization strategy of mobile marketing which maximize the expectant benefits of emporiums was proposed by analyzing customers'historical information.The main research in this paper are as follows:(1) On the basis of traditional RFM theory analysis, the method of analysing customers' reponse rate using the improved RFM theory are presented.Then the solution of the mobile marketing strategy problem which is base on improved RFM theory is confirmed.(2) Using integer programming to construct mobile marketing optimization modelbased on improved RFM analysis, lingo software is used to analyze an example to verify the validity of the model.(3) Customer location prediction methods under the location based marketing environment, and then build the mobile marketing optimization model based on location prediction. Lingo software is used to analyze an example to verify the validity of the model.The presented two models are proved to be efficient in improving the marketing activities and in minimizing the decline in customer satisfaction and cost of loss.