A customer who last purchased over the phone six months ago might have a half-life indicator of “1,” while a customer purchasing in a store three months ago might have a half-life indicator of “0.” Execute marketing programs against the half-life indicators that have a value of “1.”
Finally, half-life indicators interact with each other. When a customer clicks through an e-mail campaign, online responsiveness temporarily increases, often significantly, before reverting back to a normal state. Thus, quantify the interactions, adjusting half-life indicators appropriately.
The modern database marketer creates data marts that store transactions across channels. Once data is in the data mart, another data mart is populated with actionable indicators designed to facilitate marketing programs. Half-life indicators represent a great way to identify points in time when a customer is likely to change behavior.
Kevin Hillstrom is president of MineThatData, a database marketing consultancy. He can be reached at kevinh@minethatdata.com.
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