Psychographic Segmentation: Stealing the Tobacco Industry's Approach to Segmenting Populations for More Effective Change

Theoretical Background and research questions/hypothesis: 

Tobacco industry documents describe an advanced “psychographic segmentation” model that targets potential smokers based on their interests, values, lifestyles and identity. This approach is dramatically different from tobacco prevention and cessation efforts which typically focus on demographics such as age, race/ethnicity, socioeconomic status and geography. Psychographic segmentation could be used within tobacco control to more directly combat the tobacco industry’s marketing practices.

The study of “peer crowds” is an emerging science that can provide public health practitioners the psychographic segmentation tool they need to combat the industry. Peer crowds are the macro-level connections between peer groups that transcend geography, are known to influence clothing style and music preference, in addition to values and beliefs (Sussman et al., 2007). Peer crowds have also been shown to influence youth behaviors, including risky health behaviors such as tobacco use (Sussman et al., 2007; Lee et al. 2014; La Greca et al., 2001; Fuqua et al., 2012). As such, peer crowd segmentation may be a useful tool for identifying high-risk groups of youth in need of targeted health marketing strategies. The research described in this presentation was designed to measure peer crowd influence and tobacco risk among Virginia youth through the Youth Risk Behavior Survey to identify psychographic segments in need of intervention.

Methods and Results (informing the conceptual analysis):

The 2015 Virginia Youth Risk Behavior Surveillance Survey (n = 5,043 high school students) included a quantitative peer crowd measurement tool, which assessed the respondent’s peer crowd affiliation to the Mainstream, Preppy, Alternative, Country, and Hip Hop peer crowds. Distinct patterns of risk by peer crowd were observed, including elevated risk of cigarette use among Alternative teens; cigar, hookah, and e-cigarette use among Hip Hop teens; and smokeless tobacco use among Country teens, along with significantly lower risk for all products among Mainstream. Analyses of multiple peer crowd influences and tobacco risk pinpointed niche groups with further elevated risk, such as Alternative/Hip Hop. Regression analyses identified significant associations between peer crowd influence and risk, including a 21%-38% increase in risk for all products for a 1-point increase in Hip Hop influence. Peer crowd influence accounted for more of the variance in tobacco use rates than all measured demographics combined.

Conclusions: 

Psychographic characteristics, such as peer crowds, can predict tobacco use more effectively than most demographics alone. Psychographics can help tobacco control practitioners create messages and strategies that more authentically address the barriers special populations face, aiding in their quest for true health equity.

Implications for research and/or practice:  Practitioners can make significant improvements to their tobacco control strategies by adopting the tobacco industry’s psychographic segmentation strategies and by understanding peer crowd segmentation.