Avoid These Segmentation Errors for Max List ROI

List segmentation is key in targeted direct marketing, and the secret to success is as much a matter of strategic mindset as technical expertise. A recent MarketingProfs article by Mitch Markel, a partner in Benenson Strategy Group, identifies some of the common strategic errors. First, marketers need to be aware that segmentation models can slip into an ROI rut. Use of obvious profiling parameters and assumptions is one reason. Certainly, demographics (or firmographics), stated needs, and past purchase behavior are essential in grouping for likely response and lifetime value, but people don't make decisions solely based on these factors. Markel urges research that also looks at fears, values, motivations and other psychographics in order to segment customers or prospects not just as lookalikes but also as "thinkalikes." Markel cites the examples of car buyers grouped by whether they value safety over performance, and food purchasers sorted for whether they stress healthy lifestyle or convenience. Past success is another reason segmentation can get stuck in a rut. Because segmentation requires an upfront investment, marketers tend to want to stick with proven targeting once the segmentation study is completed. But today's hyper-personalized, digital environment has accelerated the pace of change in markets, perhaps shifting customer expectations and preferences away from an existing segmentation model. Markel advises an annual "look under the hood" of the segmentation engine to see if segments are still valid or need appending/updating. One outcome of segmentation based on existing customers or surveys of people marketers assume are the right targets is blindness to potential audiences that Markel calls "ghost segments." Markel suggests a periodic look at non-customers for conversion potential as one way to capture these "ghosts." And, of course, if a new product or service is in the works, research should ask whether it will attract new groups differing from the existing customer profile. Another reason ghost segments are common is that marketers, overwhelmed by the task of sifting "big data," fall back on whatever data sets are handy. Markel suggests that it would be better to bring in big data at the tail end of segmentation. He advises analysts to start by creating segments using primary research, add existing customer "big data" to target segments more efficiently, and then plug segments into a data management platform for insights on other products, services, interests, and media that may correlate. Finally, Markel stresses that a segmentation study will fail to live up to its ROI potential unless it informs the whole organization. Customer and prospect insights have relevance for multiple departments and teams, from sales to customer service to finance. Markel suggests creating 360-degree customer personas and promoting them throughout the organization via workshops and periodic team updates on results. For more, see https://www.acculist.com/avoid-segmentation-missteps-to-boost-list-roi/