“Truth,” said Mark Twain, “is stranger than fiction, but it is because fiction is obliged to stick to possibilities; truth isn’t.”
Mark Twain could be a fabulous modern CMO. Why? Because he’d be focused on the facts.
As an industry, marketers frequently rely on audience segments to define who to target with digital media. This is a performance-limiting approach because it’s based on who you think your customer is—not who they actually are.
Moving beyond segments is a paradigm shift for many marketers, but it ultimately comes down to rooting your prospecting campaigns in a deep, as opposed to superficial, understanding of your best customers—and finding more people who are truly like them.
Why is this shift so important? And how did Mark Twain get it? Let’s take a look.
Even really good segmentation misses the mark
As digital marketing matured over the past two decades, marketers have been able to reach people they may not know at all, through third-party data and media activation across multiple channels. They can use third-party data to create lists of customers who match broad behavioral or demographic attributes important to their “ideal” customer profile. That might be: health enthusiasts, value shoppers, women ages 25-35, pet owners and everything in between.
The amount of digital data has only grown over the years, and so the natural evolution of marketing has been to make each segment smaller and more granular with that new information.
This is how many marketers operate today, and it remains the industry standard. Sure, you can reach a segment as small as 50 people, which (admittedly) is pretty specific. But even in a segment of 50 people, you still have 50 unique individuals that are probably a lot more different in person than they are on paper.
It’s not a completely wrong way to activate media, but it’s missing the fundamental goal of marketing: to deliver your message to the right people. Segments, however small, contain a lot of people who aren’t like your best customers. Marketing to those people is pretty much a waste of time and money.
Segments of one
As much as people—especially marketers—like to say they have good instincts, those instincts take you only so far when stacked against the insights that come from first-party data.
When you use third-party data to create segmented lists based off behavioral or demographic attributes, you’re essentially making a guess that all people who are, say, health enthusiasts will like your organic brownies.
But if you actually look at your current best customers and model a list of prospective customers off of them, you will find much better matches than your instincts alone, in addition to quite a few prospective customers who you may have never considered. For example, my father-in-law loves military marches; at the age of 80, he bought an MP3 player to hold his collection, but I doubt that anyone marketing MP3 players would have thought of him as a prospective customer. Mark Twain would love him—stranger than fiction.
Segments of one let you replace inefficient shotgun approaches to marketing with laser targeting, and you can use the money saved to focus on reaching the best prospects. In a nutshell: Instead of hitting a broad audience and relying on them to self-select to your brand, you’re starting with the right people and guiding them efficiently through the full buyer journey.
The results speak for themselves
Today’s marketing technology has developed AI to a point where we can build optimized modeled audiences for every campaign to reach the right people and cut out the waste—every time.
To illustrate how effective this can be, we had one client who tested the performance of two campaigns:
- Audience A: Modeled an audience off of its best current customers using first-party data-based individual customer IDs.
- Audience B: Used third-party data to segment an audience by behavioral attributes.
Although the two campaigns spent the same amount, audience A had double the reach and performance, and the cost per correlated outcome was 45% less.
Another client compared the performance of:
- Audience A: a first-party data modeled audience
- Audience B: a third-party behavioral segmented audience
- Audience C: a third-party demographic segmented audience
The cost per correlated outcome for audience A was $1, which is only 10-15% the cost of the other audience campaigns at $10 and $7.
Truth is stranger than fiction, so rely on the truth
We’re in a time of transition: Shifting from an old way of digital marketing, anchored to traditional mass media targeting that relies on segments, to a new one that is personalized. Rather than starting broad with a “guess” at the top of the funnel, you’re using your knowledge of your best current customers to target new ones.
Rather than guess, just know. That’s what marketing technology is capable of today, and, as you saw with the numbers here, it makes a very big difference. In a time when there’s ever greater scrutiny on marketing budgets and leaner teams, every ROI improvement matters. Take a page from Mark Twain and focus on the facts—they’ll never lie, and your marketing will be all the better for it.This article was originally published on Adweek, January 2022.