Matchback Analytics: Tools to Understand the Relationship Between Catalog Mailings and the Flood of Web Buyers
In the first of a three-part series over the next three weeks, catalog circulation consultant Jim Coogan takes an in-depth look at the data catalogers should be obtaining from their matchback analytics.
In today’s multichannel commerce environment, the Web is producing a flood of orders. And typically these orders come without source codes. A growing number of catalogers are recognizing the need for matchback analysis to understand response to their catalog mailings.
Matchbacks simply are matching mailing files to order files to see who responded to a catalog mailing vs. responded online. As more catalogers recognize the need for matchbacks, they need to dig deep into this new type of analysis to understand what matchback analysis can tell marketers about optimizing their circulation.
Your matchback results provide a much richer and deeper source of data than merely telling you the total response of each list segment mailed, as well as those list segments that performed above breakeven. With the flood of Web orders lacking source codes, catalogers are using matchbacks to get more complete mailing results.
The Basic Analytics
When running a matchback, you get full response data for each list segment with both the source-coded orders and the matchback orders where no source code was given but the order matches a household that was recently mailed. This data is the basic response data catalogers use to track each mailing and each segment mailed in a catalog drop. Listed below are eight key factors involved in helping you get the most out of your matchback data.
1. Total response of each list segment mailed, sales per book, response rate and average order value: This comprises the basis of measuring list response. The difference with matchbacks is you get all the orders that match the mail file, not just the orders that come with source codes.