If you are a direct marketer, there’s a strong chance that at some point you’ve enhanced your internal customer file with an external data append, which contains a gamut of data elements describing individual and/or household characteristics.
Most large direct marketers have ongoing relationships with major data compilers. Subscribers to a data enhancement package receive upward of 100+ demographic and psychographic data elements, which generally are appended quarterly to the in-house database.
However, marketers typically end up leveraging only a few appended data elements. Key demographics such as age, gender, income, education and household composition are most commonly utilized, while dozens of appended psychographics (e.g. golf, travel, wine, crafts, etc.) are usually neglected.
The low impact of psychographics stems from the difficulty of identifying and defining lifestyle and interest traits. Compared with many demographic variables, psychographic data cannot be modeled or implied from the census data. It must be recognized on an individual/household level and compiled through a particular source (survey, subscription, membership, past purchase, etc.) causing relatively low incidents of “known/yes” psychographic traits.
This relatively low coverage, combined with the predictive force of transactional and demographic data, usually causes psychographic data elements to be left out of targeting models. Even though they are rightfully excluded initially from the models, psychographic data should not be forgotten as it can prove to be a valuable source of testing ideas.
Marketers often use psychographics to get ideas for message and creative executions. But psychographics also can be a great platform source for testing third-party lists.
If you haven’t already done so, enhance your customer file with standard psychographic data, available for purchase from third-party data compilers, and conduct a simple data mining exercise. Develop a Likelihood Index for each psychographic data element to identify lifestyles and interests that have above-average association with your product or service. Pick the top psychographic data elements and buy names from lists reflecting these lifestyles and interests. In your next mailing, test these lists to determine their ROI. The results will surprise you.
