Why it’s Time to Break Up with Customer Segmentation
You’ve probably heard this a million times, but it still bears repeating:
“Customers are expecting more than ever from their interactions with brands. Getting it right in this increasingly competitive age of retail can be make-or-break.”
According to Forrester Principal Analyst, Brandon Purcell, the days of traditional customer segmentation are over. The world of rules-based segmentation is losing ground because it no longer provides the level of value required to justify the effort.
“Traditional segmentation methods lead to static, incoherent results because they don’t take dynamic customer preferences into account. The ability to layer AI on top of external, unstructured data sources can help CI pros glean smarter insights on how to refine their market strategies and expand beyond their existing customer base.”
Understandably, you might find it hard to cut the proverbial apron strings to traditional segmentation. After all, as Forrester points out, customer segmentation has been a cornerstone of marketing campaigns for a long time because it’s provided organizations with a way to separate their customer bases and plan interactions with them.
But automation and triggered messaging are a partial solution, at best, accounting for only a fraction of the comprehensive customer marketing plan.
Growing customer expectations for personalized experiences, as well as the availability of AI technologies that provide smarter insights about these customers, signal a time for marketers and CI pros to reevaluate their segmentation strategies.
“While segmentation is a useful tool, it’s important to remember that customers are individuals that yearn for more personalized interactions. Be equipped to deliver the next best experience by ingesting signals across the customer journey and tailoring your customer experiences accordingly.”
While it may seem scary to stop relying on traditional segmentation rules in your customer campaigns, you might be surprised by the results you get.
For example, French retailer, Galeries Lafayette, was used to targeting primarily women when promoting women’s products, and mostly men for men’s products.
Once they incorporated an AI-driven customer marketing solution that tapped their first-party data to help determine the audiences most likely to deliver engagement and revenue, however, they discovered something surprising:
- targeting for men’s campaigns actually should’ve been mostly women (80%)
- women’s campaigns should’ve been targeting about 25% men
The change helped the brand achieve an in-store and online campaign revenue increase of 34%.
“The erosion of traditional segmentation and emerging primacy of personalization will have profound effects on the role of CI pros and their internal partners,” says Forrester.
It’s important to note, too, that developing personalization models for identifying and addressing customer needs isn’t just a technical challenge—it’s also an organizational one.
As Forrester points out, “The move from segmentation to personalization is a cultural shift as well as an analytical evolution. And it requires new operational processes for developing and delivering experiences.”
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