Data Mining Strategies for CRM Negotiation Prescription Problems
In some data mining problems, there are some input features that can be freely modified at prediction time. Examples happen in retailing, prescription or control (prices, warranties, medicine doses, delivery times, temperatures, etc.). If a traditional model is learned, many possible values for the special attribute will have to be tried to attain the maximum profit. In this paper, we exploit the relationship between these modifiable (or negotiable) input features and the output to (1) change the problem presentation, possibly turning a classification problem into a regression problem, and (2) maximise profits and derive negotiation strategies. We illustrate our proposal with a paradigmatic Customer Relationship Management (CRM) problem: maximising the profit of a retailing operation where the price is the negotiable input feature. Different negotiation strategies have been experimentally tested to estimate optimal prices, showing that strategies based on negotiable features get higher profits.
KeywordsInput Feature Customer Relationship Management Baseline Method Negotiation Strategy Inversion Problem
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