Watch: Stop Over-Targeting and Let TV Creative Drive Results

Third-party audience data used for targeting are less accurate than most marketers assume. One study reviewing gender targeting found the average accuracy rate to be just 42%. Research from Truthset puts email-to-IP address match accuracy at 16%. And according to Adverity, CMOs estimate that nearly half of the data their teams use to make decisions is inaccurate in some way.

As a result, precise targeting rarely provides the return marketers expect. And in a recent ADWEEK webinar, Marketing Architects CMO Elena Jasper argues the problem goes even deeper. The advertising industry has mistaken the act of targeting for a strategy itself.

"There's a concept called strategy surrogation," Elena told the audience. "It's when you start mistaking the manipulation of a metric for actual strategic control. A dashboard number feels like evidence of success, even when it's measuring correlation, not causation."

Watch the full session or read on for the highlights.

 

Precision targeting became the default because it feels rigorous. Even when it isn’t.

Before going further, it's worth drawing a line between two different things that often get lumped together.

Strategic targeting is understanding who your brand is for and what problems it solves. That work shapes product, message, and marketing strategy. Media targeting, on the other hand, refers to taking that audience definition and using it to narrow your ad buys to only those people. That's where hypertargeting logic starts to break down.

For most of advertising history, the distinction between strategic targeting and media targeting didn't really matter. Then the mid-2000s arrived with behavioral cookies and mobile device identifiers, and suddenly you could follow a specific person across the internet, serve them an ad, and record what they did next. For the first time, digital ad spend looked like a direct lever for revenue. Marketers finally had tangible numbers they could bring to a CFO.

The platforms had every financial incentive to reinforce that feeling. Google, Meta, and Amazon built their ad products on granularity. More targeting options means higher CPMs means more revenue for them. Roughly half of every ad dollar on these platforms goes to actual media. The rest goes to intermediaries, many of whom justify their fees through targeting complexity.

That complexity introduces error. Audience segments built on probabilistic inferences rather than verified data. Identity graphs filled with educated guesses. CPMs inflated by targeting fees that quietly eat into actual reach.

 

The real target audience is almost always bigger than you think.

Even when tight targeting works exactly as intended, it often reaches the wrong people.

When brands narrow their strategy around their most engaged customers, they over-index on heavy buyers. These are the people who already purchase frequently in your category. They’re easy to spot in your data. But they're also already buying. They don't need convincing.

The Ehrenberg-Bass Institute has spent decades studying how brands actually grow. Their conclusion is clear: growth comes from light buyers, not the loyal core. Most category buyers purchase only once or twice a year. Reaching them at the moment they enter the market is how brands compound market share over time. A targeting strategy aimed only at your most loyal 10% can't do that.

The gap even shows up in B2B categories, where it's tempting to think narrow targeting is the obvious move. Picture a project management software company targeting IT professionals. One day an IT pro finds the brand and is ready to buy. But their CFO recommended a competitor, and the sale goes elsewhere. Tight targeting reached the right person and still lost the deal, because the six to ten other people involved in the decision never saw the brand.

 

On Connected TV, hypertargeting creates a frequency problem.

Nowhere does this problem with precise hypertargeting play out more clearly than in Connected TV advertising.

CTV promised digital-style precision in TV's high-attention environment. Advertisers responded by doing exactly what they had been trained to do. They optimized for the smallest, most defined audience slice they could find. And then they showed that audience the same ad. Repeatedly.

Marketing Architects' data shows that as frequency rises, response rate declines. There are benefits to repeat exposure up to a point, including brand recall and improved conversion. But past that point, high frequency starts actively irritating the exact people you're trying to reach. (Anyone who's seen the same streaming ad four times in one episode knows this feeling well.) CTV over-exposure has actually been shown to reduce purchase intent according to research from MiQ.

That irritation is one cost. The other is the targeting itself. Every layer added to a CTV buy raises the total CPM. So the right question before adding a targeting layer isn't "Can I target these people?" It's whether targeting them provides real incremental value, or whether you're just paying more to reach fewer people with questionable accuracy.

 

For TV advertisers, creative quality is more important than precise targeting.

A meta-analysis published in the Journal of Advertising Research analyzed 53 studies with nearly 12,000 participants and found that when personalized ads outperformed generic ones, the effect was small, and the reason had nothing to do with targeting mechanics. It was perceived relevance. The creative earned the connection.

According to System1, poor creative is costing marketers more than we think. US brands would need to spend an additional $189 billion annually to make their current ads as effective as top-performing creative work. That number is wild. And it points to something important: no targeting strategy compensates for a forgettable ad.

The good news is that the things that make advertising work (emotion, memory, distinctiveness, and salience) operate broadly across human audiences. A heartwarming ad is heartwarming to most people. What marketers sometimes confuse is cultural relevance with audience segmentation. Making sure your creative doesn't feel tone-deaf to a particular group is good creative. Building 30 versions of an ad for 30 behavioral micro-segments is expensive, slow, and often unnecessary.

A better path is starting with a strong master spot and adapting it thoughtfully. Marketing Architects uses a tool called Mass Customizer to create contextually relevant versions of a TV ad without rebuilding from scratch.

 

What came up in the Q&A?

For brands that have been using precision targeting for years, what's the first thing you'd have them change?

Don't just blindly abandon your existing approach. Set up some tests first. Start targeting broader, try contextual targeting, and make sure you have the right measurement models in place to see the difference. Win trust with data over time.

 

How do you make the case internally that broad reach is the right move, especially to stakeholders used to narrow audience metrics?

Start with education. Read How Brands Grow by Byron Sharp. Follow Mark Ritson's work. Look into the Ehrenberg-Bass research. Once you have that foundation, it's a lot easier to share it with your team and stakeholders. And then test it. Let the results do the talking.

 

How do you A/B test creative? How do you measure what's actually working?

For TV commercials, Marketing Architects prefers pretesting over live market testing. Through a platform called ScriptSooth, clients can test creative before ever going into production.

On the digital side, in-market A/B tests can be informative, but you’ll still want to be careful. Algorithms often shift budget toward whatever drives the fastest response, which introduces bias against ads built for distinctiveness or long-term brand building.

 

Should targeting strategies be different between linear and Connected TV?

Yes. Linear TV's cost structure makes broad national buys more efficient since geographic targeting at the local level gets expensive fast. Streaming opens up more targeting options, including geography, genre, and retargeting.

But don't assume linear is worse just because you can target less. Linear might actually be better for some marketers precisely because it forces a broader strategy. Most Marketing Architects clients see the greatest success when layering both linear and Connected TV.

 

Is there ever a situation where precision targeting is actually the right move?

Of course. There are categories where the audience is genuinely niche, and broad reach doesn't make sense. The issue isn't precision itself. It's the assumption that it's always the best approach.

Before relying on third-party lists, ask how accurate they actually are. Test other forms of targeting. And don't let the fact that a platform makes precision easy be the reason you use it.

 

Want to go deeper?

Tune into this episode from The Marketing Architects Podcast. Elena joins CEO Angela Voss and Chief Product Architect Rob DeMars to chat targeting research, opportunity costs, and what balancing reach and relevance on mass marketing channels really looks like.