A decade ago, I had an idea for a new way to create high-response prospect audiences for direct mail. It was completely different from anything available at the time. To my knowledge, no one had tried it, probably because most thought it wasn’t even possible. I figured out the how (now patented) and convinced a dozen clients/friends who used direct mail lists to test it.
Then I got the email that I thought doomed my idea to failure before the first mailing even went out.
One way to determine if a new prospect audience will work in classic direct mail is to measure the overlap between the new audience and lists that have proven successful over time. Generally, good prospect audiences share a natural overlap in the 35-50% range. Pre-mailing analysis showed that my new audience had only about a 10% overlap. Either we had found a new source of prospect audiences, or my idea was a bust. My money was on the latter.
Fortunately, my friends had more faith in my idea than I did. They all decided to mail the new prospect audience. Back then, like today, finding new, successful prospect audiences is a challenge for all brands. They were willing to take a chance.
The results stunned me. In 75% of the tests, the new prospect audience was one of the top performers!
We created this new audience by scoring unknown browsers who had abandoned my friends’ websites.
NaviStone subsequently found other uses for this audience creation methodology that made a bigger difference for marketers and didn’t require that they have an existing direct mail program. These include daily retargeting with personalized postcards, lookalike models, triggered postcards to reach email opt-outs, and enhancing CRM data to improve all campaigns, including email and SMS.
We dropped our focus on classic direct mail years ago and nearly forgot about our original use case.
The sad news about Oracle Advertising (which many of us knew as Oracle Data Cloud or Datalogix) had me think of it again.
While we focus on digital marketing, our first product, using web browsing data for direct mail lists, still exists. Over the years, we’ve expanded and improved our identity network and modeling. It’s more effective today than it was when we tested in 2015!
And you can refine the audience based on the categories of products an unknown visitor has browsed, something we didn’t offer in 2015 and I highly recommend. At the very least, create some test cells—you’ll be amazed how much better prospects who have browsed the categories you’re featuring respond (note: this also works as a CRM enhancement). If you’re looking for new prospect audiences for classic direct mail, you should test this approach.
As always, we don’t require (or allow!) any data contribution.