The Market for Attention

The media market is structured as an exchange of dollars for ‘impressions’ or ‘viewers’. But these assets, and their derivatives such as Gross Rating Points (GRPs) and Target Rating Points (TRPs) are only proxies for the real value that is being sought in the exchange: attention.

The age-old problem with buying views or viewers on volume — which is the nature of the media market — is the difficulty in measuring whether what is purchased actually delivers the intended value. Media buyers intend for the views they purchase to convert to a desired response from consumers; usually a purchase behavior, or in the realm of politics, an entrenchment of belief.

But there are many gaps in understanding results through the theoretical chain of cause and effect from an exposure to an advertisement to the desired outcome expected from that advertisement. A top three list will help us dive deeper:

1. Actual reach: Did the exposure actually achieve an ‘impression’? Although it was on a screen (or on a page or on a billboard or making a sound), did our target consumer actually notice it?
2. Relevant reach: Did the impression impact the consumer’s perspective in our favor? If our impression did get attention, did it also impact the consumer’s way of thinking in a way that should deliver incrementally better outcomes for our cause than if no advertising had been conducted?
3. Effective reach: Can the exposure to a paid media message be attributed to a desired “conversion” event?

What Matters, and What Can Be Measured

Advertisers know that their goal of converting a dollar spent in advertising to more than a dollar in sales (their Return on Ad Spend or ROAS) is dependent on being effective in all three steps above.

The challenge for advertisers is that the very first step in the process — whether exposures were actually paid attention to — is very hard to measure. We can easily count the number (and type) of people who view channels at a certain time, or stream specific content, or play specific apps, and so on. What is less certain is whether those people are mentally involved when our ad appears in those contexts.

Digital measurement allows the quality of exposures to be assessed in a way that helps establish a probability that the exposure got attention. Metrics can tell us the visibility of the content on a screen, and how long a video was viewed, and whether interactive content was interacted with.

Metrics like these offer the best proxies for the impossible knowledge of whether a person actually noticed the content that was served. So this is where the analysis of media performance needs to begin.

The Efficiency Trap

Unfortunately for advertisers, the century long absence of any measure of the “quality” of exposures spanning from print to radio to television and even early digital means that the “norm” in advertising measurement is currently still based on quantity measures; specifically Cost Per Thousand Impressions (CPM).

Because it has been impossible to answer “how many people actually received my message?”, the measure of success in reach has been limited to “how many people had a chance of exposure to my message?”.

And because the quality of an exposure could not be measured vs. any other exposure, it has made perfect sense to build strategies around getting the most exposures possible for the least amount of dollars. In other words, always pursuing the lowest CPM was a very reasonable core media strategy.

This was acceptable when the quality of exposures was not measurable. But, with more information about whether impressions are likely converting to “reach” to a consumer — are garnering actual attention — the question of how quality impacts price in the media market comes into play.

With better information, it becomes a self-made trap for advertisers to revert to a focus on comparing CPMs only as the basis for investment at the most important decision making moments.

Seeing Things Differently

Let’s end this post with one example of how the picture of effectiveness changes as new data enters the picture.

Take one hypothetical video advertising partner who can serve both skippable and forced-view ads.

The platform prices the forced-view ads at a higher CPM than the skippable ads; let’s say $14.50 CPM for forced-view and $2.50 for skippable. The supply curve here (in yellow) is built on “number of people who will have full exposure to the ad”, with more people per 1000 seeing a forced-view add (the demand in red) than to a skippable ad (blue, which they tend to go ahead and skip).

In the efficiency trap focused on CPMs, some marketers might revert to investing in the lower CPM tactic on the basis that it gets more impressions per dollar. The next level of strategic thinking however is evaluating the quality of each 1000 impressions, and sees value in paying more to get more attention, more actual reach.

A level of thinking beyond that is questioning the type of attention that forced views are getting. They are “forced” after all. Does the forced view effectively convert higher actual reach to relevant reach?

In this example, our focus on the picture changes when we shift the demand from a scale of cost per 1000 impressions to “cost per completed view (per 1000 exposures)”.

With this metric about how many views are completed, the price per 1000 for “forced view” stays exactly the same: $14.50. However, the problem of getting attention becomes much clearer in the pricing for skippable ads, which rise to around $115 for completed views in 1000 exposures.

This pricing clearly illustrates how rare and thus valuable it is to get attention to content when people have the option to skip it.

It also now calls into question the actual value of the “forced view” ads in terms of relevant reach. If the people who actually find our content relevant to the end is so rare when they’re given the option to skip, then why would the content be more relevant when they’re forced to view? Yes, they are seeing what we have to say, but the pricing on skippable indicates that most people would avoid this content if they could.

Where We Land

Like most projects that dig into data, we’re left with some initial conclusions in this case, and with more questions to answer.

We know that attention is what advertisers are trying to buy in the media market, and we know that they’ll need to pay more if they want to increase their chances of getting attention.

However, we also now know that just forcing access to eyeballs doesn’t necessarily mean getting relevant reach. Why would the people who are forced to see the content all the way through feel any differently about it than the people who chose to skip it? Does paying more to make people watch something they’d prefer to skip actually help the cause in establishing relevant reach that moves to effective reach?

The answers to how exposures become attention and then become action are out there — they just need testing, measurement and analysis to reach.