How Store Distance Affects ROI Measurement
Retail direct marketers are blessed in that they get to observe marketing results that are somewhat different than what traditional marketers observe. Consider the retail direct marketer who sends catalogs to customers. While direct marketers segment their customer files on the basis of classic recency, frequency and monetary (RFM) parameters, retail direct marketers go one step further.
Retail store distance is also appended to the RFM segmentation strategy. Customers are subsegmented by zero- to 10-mile store distance, 11- to 25-mile store distance, 26- to 50-mile store distance and 51-plus-mile store distance.
Customers within 10 miles of a store like to shop in stores. Retail direct marketers are likely to see retail sales lifts during the first weekend after their catalogs are sent. Direct mail sent into retail trade areas tends to have a short “half-life.”
Customers who live between 11 miles and 25 miles from a store are the classic “multichannel” customers that we so often hear about. These customers are likely to shop in stores, as well as online on the first Monday or Tuesday after the catalog is mailed.
Customers who live between 26 miles and 50 miles from a store are often the most productive direct channel customers, sharing dollars between online and telephone orders.
Customers who live more than 50 miles from a store, especially those in rural areas, are likely to further shift their money from online to telephone sales. These customers often have a long order curve — i.e., they hold on to direct mail longer than the average customer.
Many retail direct marketers have learned that page counts can vary by store distance. A simple postcard may be all that's needed to get the customer within 10 miles of a store to shop in that store. Smaller page counts can be used to get the suburban shopper to visit a store or shop online. Large page counts are often effective among rural customers who aren't likely to visit a store.
Given what retail direct marketers observe in their results analyses, why not set up a test? Create three test panels, with the first panel receiving catalogs, the second panel receiving postcards and the third panel “held out,” not receiving anything. Assuming that the three test groups are equally populated with good and marginal customers, subsegment the test panels by store distance. Measure the results of your test, and identify the best strategy to employ to different customers based on distance from a store.