How to Use Customer Data Segmentation
When I began working in CRM and analytics, brands segmented audiences in a highly rigid, top-down way. For example, to attract high-value customers (HVCs), they targeted consumers based on a single demographic attribute—for example, a high-income zip codes. Two decades into my career, I still see many brands approach customer data segmentation this way.
In the digital age, you no longer need to rely on such guesswork. Instead of a top-down model based on assumptions, you can work from a bottom-up approach based on reality. With the right tools, you can quickly identify who your HVCs really are. You can discover the key attributes your HVCs share, e.g. product affinities, online and offline behaviors, etc. And you reach out to other consumers with the same attributes in order to convert them to the brand.
I have worked with a number of top brands to help them embrace this modern approach to segmentation. Read the full article in WWD, How to Harness the Four Dimensions of Customer Data, for more on:
- A clear definition of modern segmentation—what I call behavioral + contextual targeting
- The four dimensions of customer data that fuel modern segmentation.
- Three critical best practices to start putting modern segmentation into practice.
Read the full article here.