How not targeting makes you a better marketer

Written by Pete LaFond, vice president of marketing, TruSignal, Inc.

If you’re a direct response marketer and your conversion rates are 100 percent, this article probably isn’t for you. For the rest of you looking to move the needle in your digital campaigns, continue on.

The premise of direct response campaigns is that they drive immediate results. As a marketing professional, you’re likely testing and iterating constantly to figure out how to optimize each channel to the nth degree, striving to squeeze out a few more new customers with an acceptable cost per acquisition.

The challenge is, no matter how many levers you pull, your campaigns always target a combination of high and low converters. But what if you could avoid many of the low converters? Here’s where NOT targeting (a.k.a. audience filtering) comes in to play.

Turning targeting on its head
Audience filtering should be a critical part of your digital strategy. Audience filtering, also known as “exclusion targeting,” allows you to exclude people from your campaigns who are highly unlikely to convert. In turn, the money saved by not buying those people can be redirected toward advertising to quality prospects —people likely to convert with an attractive revenue-per-lead.

While it’s common practice to target the best prospects with the highest revenue-per-lead, you can also create extremely efficient campaigns by eliminating unlikely converters pre-campaign, before valuable resources are exhausted.

Not your typical exclusion targeting
Today, there are multiple ways to exclude audiences from your media buy, but most of the filters are either too specific or restrictive, thereby eliminating exclusion targeting at scale (e.g. if user A visited website X in past 2 days, then exclude from retargeting campaign). Or, they are so broad (age, geography, etc.) that you can’t utilize exclusion targeting without throwing the baby out with the bath water.

Audience filtering, on the other hand, uses your known customer data and predictive analytics to build a custom model to score people, one-at-a-time, and determine likelihood to NOT convert. Using this technique, you can pinpoint and eliminate specific individual poor performers who are dragging down your overall conversion rate. The result? Fewer wasted impressions and a lower CPA.

TS_filtering_chart

Put the new strategy to the test
It’s unlikely you’ll ever get a 100 percent conversion rate, but predictive audience filtering can reduce wasted impressions by 20 percent or more and get you one step closer to targeting nirvana. Understanding who to avoid can be just as powerful as understanding who to target.

https://staging.digiday.com/?p=118865

More from Digiday

Sliders test article

Amazon bulldozes into new markets, upending the status quo and challenging rivals. Today, it’s the turn of the ad-supported streaming world, and Amazon is coming out of the gate strong.  Why, you ask? Because Amazon is serving marketers an opportunity beginning today to reach a whopping 115 million monthly viewers in the U.S. alone, courtesy […]

How CTV and DOOH are growing this political season for smaller agencies

Connected TV and digital out-of-home are playing a bigger role in upcoming elections and politics – especially for smaller agencies looking to place clients’ dollars.

CMO Strategies: Advertisers identify the top attributes on ad-supported streaming platforms

This is the third installment in Digiday’s multi-part series covering the top ad-supported streaming services and part of Digiday’s CMO Strategies series. In this report, we examine which ad attributes matter the most to marketers on streaming platforms.