Now You Can Clone Your Best Customers

Your next customers will likely look like your existing customers.

But in order to know what to look for in those next customers, you need to know your own customers. In fact, knowing your own customers is generally the most important first step to acquiring new ones, period.

If you’re a marketer, you may groan at the mention of customer research – envisioning uphill battles with surveys, endless user interviews, and repeated doubts about what makes the right sample size. Yet without this research, you’re relying solely on assumptions to target your messages and offers. 

From Doubt to Doppelgänger

If you’ve ever thought, “wouldn’t it be great if I could just clone my existing customers,” then you aren’t far off from the cutting edge of marketing technology.

Using a process called Semantic Behavioral Profiling, we give you a dynamic, three-dimensional picture of an existing pool of customers: their interests, pain points, hobbies and where they congregate.

From as few as 300 existing customers, we create a Semantic Twin, a target audience of users who are not already part of your audience but display similar traits. With flexible controls to determine the balance between high affinity (stronger match to the traits of existing customers) and high scale (a larger segment), segments can be fine-tuned to suit any campaign.

Top-down vs. Bottom-up

Traditionally, audiences have been built using “top-down” taxonomical targeting  a set of key terms determined through educated guesses and prior campaign data. And that can be somewhat effective. But not every audience is so easy to figure out, and not every space has readily available targeting data.

Semantic Twinning, by comparison, creates audiences through a “bottom-up” method. Rather than selecting terms, we let the existing user pool reveal themselves to us, creating an audience that looks the most like the customers you already know so well.


Author: David Abravanel

Marketing consultant for Semasio with a passion for all things data, emerging tech, and electronic music. NYC-based.
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