To deliver 100 GRPs in 1992, a company had to air an advertisement about 15 times. Today it takes about 47, which means you have to run three times as many ads to achieve the same volume of impressions. And with people watching an average of just 20 networks, unless you’re running ads all over cable, it’s likely that the more ads you run, the more times they’ll be seen by the exact same people.
While the biggest brands might see excess frequency as the cost of keeping their products top of mind across the country, most companies can’t absorb that kind of wasted spend without hurting their bottom line.
Take the example of a CPG brand, who this past April ran a lawn-product campaign aimed at Homeowners 25-54. Over the course of four weeks, the campaign had an average target-audience reach of just 45%, and of those people, 12% saw the ad over 21 times.
This isn’t just inefficient from a cost perspective, with fewer people seeing an ad, it also minimizes the overall effectiveness of TV on driving sales. While the biggest brands might see excess frequency as the cost of keeping their products top of mind across the country, most companies can’t absorb that kind of wasted spend without hurting their bottom line.
The good news for brand marketers, however, is that there’s a much smarter, more efficient way to buy TV advertising. Not direct response, not addressable, not programmatic — we’re talking about data-optimized, audience-based advertising on national linear TV.
What makes it smarter? There are several reasons, but let’s explore two of them.
Firstly, when it comes to targeting, you can go beyond age/gender demos, and even beyond category buyers. If you want to target tech-savvy A25-54 who are adventure travelers and like to fly business or first class to destinations all over the world, you can do that. This specificity enables you to reach more likely customers and reduce the number of impressions wasted on those who have no interest in your product. Secondly, some solutions (like Simulmedia’s VAMOS platform) can also connect customer data with viewing data. When you match what people watch with what they buy, you can close the loop and learn exactly how each ad performed. In other words, you can see which audience segments were most responsive, on which network, during which daypart—and use that information to optimize future campaigns and increase your ROI.
What makes it more efficient? Well, that depends on your approach, but VAMOS is designed to find your audiences wherever they are—even if it’s in an unexpected place. Here’s an example. Let’s say you’re trying to reach the first-class flying, adventure traveler audience segment outlined above. Imagine they’re up early to work out in their home gym and you have to choose between two inventory units in which to run your ad. The first falls during Million Dollar Listing NY on BRAVO, and the second falls during the true-crime show Fatal Vows on Investigation Discovery. You’d choose Million Dollar Listing, right? It’s a no brainer.
Or is it? Check out the graphic below. Million Dollar Listing NY indexes almost 4x higher for that target, but Fatal Vows actually has over twice the number of target audience viewers—and it’s 30% cheaper. Whereas conventional wisdom would be to buy the spot with a higher index and contextual relevancy, at Simulmedia, VAMOS would pick Fatal Vows every time.
So where does R.E.M. fit into all this? (Note for those born after 1990: the subtitle of this post is a reference to R.E.M. the band, not the sleep cycle.) Their lead singer, Michael Stipe, says that “What’s the Frequency, Kenneth” was a song about a guy desperately trying to understand what motivates the younger generation, and brand marketers are desperately trying to understand what motivates their customers. Unfortunately for marketers, by maintaining traditional practices and buying TV ads based on GRPs, they’re cutting themselves off from a treasure trove of data that could provide the answer.
While brands have different notions of effective frequency, there seems to be a general consensus that the optimal frequency for driving conversion is between 6 and 10. There is merit to this. But what matters even more, is that the people who see your ad are interested in what you have to offer, and then understanding what action they take afterwards. Data-driven, audience based advertising on national linear TV makes this possible.
By the end of “What’s the Frequency, Kenneth,” the protagonist has gone to great lengths to solve his problem, and he’s gotten nowhere. Maybe he just needed better data?
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