• Marcela Gaviria

4 types of customer segments defined from data

Updated: May 12

Customer segmentation from the order and campaign data to improve marketing personalization


Successfully segmenting customers is much about the right timing and right messaging. The first part isn’t too hard to figure out by mapping out customer journeys and setting a few rules. Timing is where I dig in with these types of customer segments. It’s important to note that segmentation alone will not result in personalization that works because you need to understand behaviors and attitudes, and timing. But segments are still precious and are easy to define with data rules. So it is a great place to start. At VIEWN, we’ve focused on what you can do with data at the intersection of customer, campaign, and orders, so segmentation is sort of our thing.


Ground Rules


Customer segmentation with data using timing terms requires an exact tag and definition unique to the group. The labels should help someone; generally, a marketing analyst immediately understands the label in the journey’s context. Business objectives need to align with the segments as well. For example, something with a long lead-time to close may require more touchpoints. To get us out of a mental stalemate about which to apply, I’m introducing 12 types of customer segments you get from looking at transaction data (order data) and campaign data. Some of the names may sound cheesy, but as I mention before, tags that connote context are better ones. Work should be fun anyway.


4 types of customer segments

  1. Loyal Champion: these are your most valuable customers. They bought the most often and have spent the most in your online shop. Their latest order has been recently placed. Keep this segment within the loyalty program.

  2. Dating: these are active customers who have placed a couple of orders, the last one being placed recently. Engage within four days of the latest order. This is key to building a relationship.

  3. Should Nurture: these customers placed 1-2 orders of the average value. Engage with discount codes to keep them coming back. More importantly, you are getting that essential touchpoint with something to offer.

  4. Tease: these customers are active on and off. They’ve placed a couple of orders of high-value orders but are inconsistent. These customers you may need to understand more about- perhaps survey to figure out why.

Segments and personas are not the same things, and in my opinion, working with personas will be the way to innovative this field of customer data. Personas can contain more than one segment but include insights on unique factors influencing the audience. Perhaps it is a greater emphasis on the convenience of artificial intelligence VIEWN; we can go beyond simple rule-based models and give you more than four to analyze. We have been able to isolate unique personas from different kinds of customer data. That’s coming up soon.



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