Psychographic Segmentation

Identify and group readers by their values, beliefs, lifestyles, and motivations so that content and products respond to the question of "why", not just "who".

Use this model if…

  • …you want to grow digital subscriptions or advertising revenue by aligning messaging and campaigns with reader mindsets and values (for example, sustainability, career ambition, or global curiosity).

  • ...you are launching a newsletter, podcast, or product that should resonate with a specific passion segment (such as eco-conscious home renovators or indulgent DIY crafters).

  • …you are ready to invest in qualitative research and/or AI tools to build psychographic profiles from surveys, behavior data, or social media insights.

Traditionally for news… we define the audience not by demographics but psychographic measures. We call it the Curious reader.”

Anna Dubenko, The New York Times

Origin: Psychographic segmentation began in the 1960s when market researcher Emanuel Demby used the term to describe differences in consumer values, behaviors, and attitudes inside demographic groups. The first structured framework, AIO (Activities, Interests, Opinions), profiled consumer lifestyles. In 1978 SRI International introduced VALS, the Values, Attitudes, and Lifestyles model, which linked psychological traits to buying patterns and drew on Maslow’s hierarchy of needs. Since then, many additional approaches have emerged that group people by mindset or motivation. These models have become common in publishing, where first-party data helps publishers build value- and interest-based segments that enhance content strategy, advertising results, and subscription growth.

What does the model really do? It converts scattered audience data into actionable insight by clustering readers who share values, attitudes, interests, and lifestyles, revealing the motivations behind their behavior. With these deeper drivers visible, publishers can align content, product features, and ads to each segment’s worldview and keep strategies current by updating the model with fresh behavioral and AI-enriched signals.

Examples of segments:

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