After creating a consumer segmentation, brand teams often have trouble activating marketing programs against the newly defined segments. For example, I often hear a brand’s agency say, “I cannot buy media based on these segment definitions.” In addition, most media agencies are still measured and compensated by demo-based CPMs. I personally experienced the same challenges working at a media agency trying to implement “buyer” segments versus lower-priced standard demos like women 18-34.
This is not only frustrating for the agency, but also for the advertiser. Brand managers spend time and resources to create high-value segments to reach their consumers with tailored messages. But they are leaving ROI on the table with this disconnect between planning and buying.
The bottom line is that achieving a meaningful ROI from your segmentation will mean linking definable traits of your targets with “softer” elements that help you understand why and what. With this linkage you can truly drive engagement and grow your business.”
Standard age/gender demographics combined with digital behavior are still the primary way brands create online audiences. But this leaves the ever-important psychographics, needs, attitudes, and lifestyle information out of the equation. For example, I once worked with a quick service restaurant who used mobile location data to create targets based on people who previously visited one of several QSRs within a 15-mile radius. Device IDs of people who have visited a QSR restaurant are anonymized to create the target audience. Unfortunately, this data alone lacks key information about the purchasers to help connect with them based on the “why” behind their actions (i.e. needs, attitudes, psychographics, etc.)
Advances in analytics and data science allows brands to employ two methods to bridge the gap between marketable traits that define strong segments and targetable traits that facilitate media buying and outreach:
- Enhancing existing CRM & behavioral data with survey insights.
- Using new sample sources in a privacy compliant manner to create digital targets based on survey data (aka your segmentation typing tool questions.)
For the first method, we have created a process called Targetable Segmentation. In this case, a client’s segmentation is enhanced by connecting behavior and attitudes to yield identifiable groups that are unique in their motivations. By appending database information to the survey respondents, we can employ a “micro-segmentation.” This allows us to simultaneously differentiate our audience based on both their marketable traits (i.e. attitudes, needs, behaviors) and their targetable traits (i.e. database variables). The result is a set of targetable segments that create new digital audiences for activation.
The second approach is similar but may require a larger sample size to accommodate for a lack of CRM data. Generally, a sample size of 1,000 is needed to turn a survey segment into a digital audience. In both cases, once the digital target audience is deployed, the advertiser can A-B test custom messages and different media approaches by micro-segments to measure the differences in their campaign’s ROI metrics. Regardless of which approach you take, the bottom line is that achieving a meaningful ROI from your segmentation will mean linking definable traits of your targets with “softer” elements that help you understand why and what. With this linkage, you can truly drive engagement and grow your business.
Want to learn more about creating a targeting strategy that will deliver better ROI?