This retailer designed its direct-mail campaigns by hand. These campaigns were designed to get customers who had purchased in only one product category to expand into another product category by making an offer for a product in a category they hadn't purchased from previously. Each campaign had creative elements combined with specific marketing offers, all derived subjectively. The resulting letter was sent to a subset of customers selected by using criteria designed to maximize the likelihood that the offer would be attractive. An industry-standard response rate of less than one percent was achieved.
A decision service generates direct-mail letters and automates the decision on what letter content to use with each customer. Data from the data warehouse produces extensive predictive analytic models that forecast which products specific customers might buy and which products are effective as first-in-category purchases. Business rules on marketing policies, objectives, target categories, and more are combined with these analytics. Each letter the decision service generates contains personalized customer information, specific recommendations based on analytics, and information localized to the customer's usual store derived by using more business rules. The result is a targeted, personalized piece of direct mail aimed at getting a specific customer to buy in an additional category.
Benefits