AI and Customer Segmentation
In today’s digital landscape, AI is transforming how companies engage with consumers. That’s particularly true in the area of customer segmentation and targeting, where monitoring and interpreting viewing and consumption habits to customize acquisition and product engagement experiences is commonplace. However, as AI evolves and becomes intrinsic to more marketing strategies, so do concerns around ethics and privacy.
AI’s ability to process and analyze large amounts of data allows marketers to profile their audiences with remarkable accuracy. By analyzing behavioral patterns such as purchase histories and social media activity, AI can also deliver tailored content and ads with unprecedented precision and timeliness.
But it doesn’t have to stop there. When creating target audiences, marketers can now move beyond the usual targeting variables - demographics, preferences/interests and behaviors to include dimensions that have previously been difficult if not impossible to action: psychographics.
Psychographics: The New Frontier in Targeting
Historically, psychographic data fed compelling audience profiles with catchy segment names (“Toolbelt Traditionalists,” anyone?). However, these profiles often lacked practical application for media buying and campaign execution, making their value questionable. Lifemind is changing that.
By harnessing AI’s analytical and decisioning capabilities, incorporating psychographic variables such as values, beliefs and attitudes in customer segmentation is now possible and can result in much more impactful campaigns. Moreover, psychographic customer segmentation helps marketers navigate the privacy and ethical issues they currently face.
Minimizing ethical concerns and AI Bias With Values-based Customer Segmentation
Despite its benefits, AI's increasing role in marketing raises ethical challenges, particularly around data privacy. AI systems rely heavily on consumer data, fueling questions about data collection, usage, and storage. Consumers are demanding greater transparency and in response, regulations like GDPR and CCPA now require companies to obtain consent for data usage and provide consumers with more control over their information.
A promising approach to alleviating privacy concerns and minimizing model bias is to segment and target customers based on their values rather than on their personally identifiable information (PII) or behavioral data. Understanding consumers' life outlooks - whether they are more conservative or liberal shaped by their regional and generational values - allows marketers to differentiate and create messaging that resonates on a deeper, more meaningful (and less transactional level) that doesn’t require explicit consent.
The Future of AI-Driven Customer Segmentation
By focusing on values, marketers can target consumers in a way that better aligns with customers’ expectations of ethical treatment and respect for their fundamental beliefs rather than purely commercial interests. And because values tend to be shared amongst people with a common cultural background and amongst those who live in proximity to one another, they can be analyzed by geographic cohorts (i.e. by zip code) rather than at the individual level, thereby eliminating the need for PII.
