How to Tell If a List Is Exhausted

Welcome to the new monthly column from Bill Singleton, president of Algonquin, IL-based consultancy Singleton Marketing.

You find what appears to be the perfect list to help you reach a target group. You mail a test quantity and get great results. In your next mailing, you go back for more. You closely watch your service bureau reports and don’t see high rates of intra- or interlist duplicates. But soon the new list selects aren’t pulling in new accounts like the old ones. What’s wrong?

The problem may be one of list exhaustion. Some market segments—say, businesses of a certain size in a single or a narrow range of industrial classifications—are not as large as the number of available names might suggest. I learned about this by creating a different kind of tracking report: a list family response trend report that did not require elaborate processing of promotional history.

You are no doubt familiar with family codes for list selects: Service bureaus will “family” together lists by broker, by source, and by select if you ask them to check for intrafamily duplication or high rates of edit drops at the start of processing. My service bureau gave me the family codes for list selects and lists coming from the brokers and sources I had used to reach a particular target market. I went back through the previous 12 months of list productivity reports and applied the family codes to the individual lists and selects. The graph I generated of the family of selects told the story clearly.

Prospecting to the target market had taken off and reached a peak after about eight or nine mailings that had occurred during the course of nearly a year. Productivity dropped steadily after that, though at first I couldn’t see why. Discussion with the broker gave me the answer.

There were actually just enough names to let me mail twice: half of the list the first time, and the other half the next time. For the second mailing I omitted the prior select order, thinking that doing so ensured fresh, new names. As a result, the list as a whole got fatigued over 16 mailings, eight to each half. The list owner was maximizing revenue by advertising different separate selects and double- and triple-counting the overall names. Only by grouping all the selects from the source across all the mailings could I analyze and explain the declining response.

That analysis taught me a lot about list fatigue and finite market segments. It also led me to promotional history analysis to identify the ideal number of contacts for a specific segment. That will be the next topic in my series: You Don’t Learn Anything Unless You Learn It the Hard Way.

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