Unlike value-added pricing and strategic pricing, intelligent couponing scenarios are implemented here. Above and beyond determining global profit relationships, this also requires the analysis of individual customer preferences and reliable prediction of customer behavior. Based on global price elasticity, intelligent decision models calculate individual customer preferences and generate predictions about purchase probability. These behavioral predictions can be taken from current customer behavior, historical transaction data or geo data. This way, consumers receive individually relevant product recommendations and individual discounts in real time. It is not a personalized base price that is calculated but rather the amount of the discount is individualized to provide incentive to customers. The algorithms are targeted to achieve customer loyalty, maximize customer value and for cross-selling and up-selling.
Individual couponing is especially used to win over A-clients. These clients exhibit higher purchase frequency and generate more expensive shopping baskets.
Thanks to the combination of personalized product recommendations and individual coupons, customers are rewarded with discounts on products that are relevant to them. Individualized coupons created automatically in customer newsletters, mass mailings and mobile apps are particularly useful ways of implementing intelligent couponing. Personalized discounts can also be generated as part of check-out couponing on the receipt, using customer loyalty cards or by way of in-store kiosk systems.