How To Clone Your Best Customers


The idea that you can clone your very best customers to create new ones is not nearly as fantastical as you might think. Allow me to explain:

For years, direct marketers have used robust data to understand the attributes of their very best customers. These insights are then used to find folks within over 140M U.S. households that share these same data attributes – so called “look-alike” targets. These targets become an obvious source of new potential customers, the lifeblood of any DTC business. The techniques used to develop look-alike targets is a relatively simple two-step process:

  1. Data Overlay & Enhancement

During this phase of the process, rich third-party data is attached, or overlaid, to your customer house file. Your house file, with very limited customer-volunteered data, is then returned with extremely granular insights – sometimes as many as 1,000 fields of demographic, psychographic, and ethnographic data. Magically (well, almost), your data-anemic house file is returned data-enhanced. This enhanced file is generally returned in a sizable report called a “customer profile”.

By the way, even if you never ever get to step two, an enhanced file will allow you to understand your customers much more deeply. You may think you know your customers but, take my word, until you enhance your file, you don’t.

  1. Regression-Based Look-Alike Modeling

During this phase, a regression-based look-alike model is built to replicate the attributes of your very best customers. At its most basic level, the model finds what attributes most deeply correlate with other attributes.

I once ran a spiritual (not religious) DTC film club. What we found when building our models was that our most ardent club customers were also avid gardeners. A relatively obvious hindsight epiphany, but one we never made before our modeling process.

Anyway, this informed an entirely new pool of potential customers for us – not those people who identified as spiritual, but gardening folks. This pool became our most efficient (CAC: LTV) source of new spiritual film club members not only in the U.S., but internationally, as well.


Now, I’m very much simplifying the sophistication of these models and how they are ultimately used to test new customer outreach. That said, I hope you embrace the very real idea that the wine industry should be using third-party data to find new customer ponds to fish from because, as we all know, tasting room visits and new customer acquisition are slowing.

 Be bold, be innovative, and test new customer acquisition strategies because in the world of DTC, if you’re not testing, you’re losing.


By: Jeff Giordano