"Consider this scenario of two women, both 38 years old, with very different profiles: Individual A is a single mother. She follows eco-conscious parenting influencers on Instagram, subscribes to YouTube channels focused on quick plant-based meals, and frequently engages with content on gentle parenting and mental health. She shops online for organic products and joins virtual wellness workshops through Instagram Live."
"Individual B is a tech executive. She's child-free, passionate about finance and AI, and consumes long-form YouTube content on design, geopolitics and productivity hacks. Her feed is dominated by creators who review the latest tech trends and share advanced digital tools, and she likes brick-and-mortar shopping but does substantial shopping online. Though both are 38, their content ecosystems, daily routines, purchase drivers and social influences are completely different. Marketing to them based on age would result in generic messaging that resonates with neither."
Marketers have long relied on simple demographic categories such as age, gender, income and region to segment audiences. Demographics are convenient, easily understood and widely available on campaign platforms. Shared birth years do not imply shared needs, routines, purchase drivers or social influences. Behavioral signals — what people watch, like, save and subscribe to — reveal intent, context and usage more accurately. Segmenting by behavioral and contextual signals enables more relevant, actionable targeting. Relying solely on age yields generic messaging that fails to resonate with diverse individuals within the same demographic.
Read at Forbes
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