How Psychographics Influence Ad Targeting

By using psychographic data, marketers can gain a deeper understanding of an individual’s lifestyle and interests, which can then be combined with demographic data for specific, highly granular targeting.

How Psychographics Influence Ad Targeting

Baby Boomers, Millennials, and Generations X, Y, Z—the list goes on. These ubiquitous demographic groups are widely used to target advertising, but do they really tell us anything about the people behind the labels?

Marketers and advertisers are accustomed to differentiating consumers by demographics, dividing them up using broad objective variables such as age, gender, geographical location, and ethnicity. While this approach undoubtedly has its benefits, relying on demographic data alone means marketers are missing a huge opportunity to increase audience engagement. By adding psychographic data into the mix, marketers can gain a far deeper understanding of an individual’s unique attitude, lifestyle, and interests, which can then be combined with demographic data for specific, highly granular targeting.

So what are psychographics, and why is it essential for advertisers to embrace this underutilized source of data to improve ad targeting?

Psychographic analysis is a way of increasing audience understanding based on an individual’s attitude, interests, and values. It allows advertisers to build a digital portrait of users that goes far beyond where they live and what they do. For example, demographic data can determine two women live on the same street, who are both aged between 18 and 24, but they may have radically different opinions and interests, which can only be determined by psychographic data.

The rise of the Internet and social media has reinforced the importance of psychographics. People can now interact more easily with those they share common values and interests with—regardless of demographic factors—creating digital communities of interest that advertisers can use for advanced, personalized targeting.

During a recent presentation at SXSW, technology researcher Alexandra Samuel illustrated the importance of recognizing psychographic data when marketing family tech products. Parenting styles and views on technology—for example, that technology should be fun or only be used for education—are far more likely to impact a parent’s reasons for making a tech purchase than demographic characteristics, such as income level or the age of children. Samuel identified three distinct psychographic groups in the family tech market—enablers, limiters, and mentors—each requiring a different approach from marketers based upon parenting attitudes and styles. Using this type of data, ad targeting can become granular and specific, rather than based on sweeping generalizations.

Prior to the development of smart technologies, capturing and taking action on this type of psychographic data was problematic, but various technologies are now emerging to meet this challenge. Sentiment analysis is one vital method for digging deeper into psychographic attitudes and providing actionable insights. Using semantic understanding and Advanced Natural Language Processing technologies to read online content in the same way the human brain does, accurately extracts the content’s meaning in the correct emotional context to provide an in-depth understanding of opinions and values—all in real time. This allows advertisers to deliver the most appropriate messaging according to the emotional context of content, reaching audiences based on interests, attitudes, and sentiment—rather than just demographics—providing the essential foundation to forge a powerful connection.

Psychographic data and its correct interpretation is a vital element in differentiating marketing strategies between competing brands. Through the construction of digital user portraits, advertisers have more opportunities to develop increasingly engaging and customized campaigns for their target audiences. For truly relevant and increasingly granular targeting, psychographics must be used to complement demographic data—uncovering values and interests to improve the overall consumer experience.