What Is the Cause & Remedy of All the Wasted Ad Spend?

Over the past few weeks, there have been a number of fairly alarming studies released that highlight the same general trend: Major advertisers are not buying the kind of ad inventory they envisioned they were.

It’s very clear there’s a problem, and the problem isn’t specific to just “open-web programmatic” ad sellers, as the Adalytics & Newsguard studies reveal.  The major walled garden ad platforms like Google & Facebook, as well as the quickly growing retail media platforms like Amazon, Walmart Connect, Target’s Roundel, etc., are all eager to extend their audience-buying capabilities into the wider web.  

This is a problem impacting everyone transacting digital media.

Unfortunately, the cause and solution to all of this is not entirely clear.  Most often, we chalk it up to a lack of transparency, followed by the prioritization of cost. These aren’t necessarily wrong, but they miss the broader opportunity for individual advertisers and the health of the wider ecosystem.

What we’d like to suggest: Shifting our measurement strategy may allow us to have our cake and eat it too.

Marketing Measurement & Attribution

Which of these two ad environments do you believe would result in more product sales and/or brand recognition/lift for an advertiser?

Example A

Example B

If the first environment strikes you as having little chance of producing a viable business result for your investment, trust your instincts.  The problem with all of this isn’t necessarily transparency or a focus on cost; it’s flawed measurement & attribution. 

The right attribution model addresses transparency and cost by its very nature.  In other words: If we get the former right, we really don’t need to worry about the latter.

Poor attribution models (looking at you, ‘last click/touch,’ ‘multi-touch,’ ‘platform reporting’) will lead you as an advertiser to give more credit to the ads in Example A above.  

Why would it do that?  Because those flawed attribution models aren’t factoring in whether ads cause results, just that they were served to a consumer who eventually landed on the result. They’re simply correlating exposure to sales. This causes what we call “correlation bias.”

If that’s the design of the game, your ad platform partners will always opt to serve ads in the first environment where consumers are click-baited (Michael Fox almost played Charles in Charge!?), and the reported cost per acquisition (CPA) or return on ad spend (ROAS) will appear the best due to lower ad costs.  

Consequently, advertisers inadvertently reward these low-quality environments with their ad dollars and perpetuate more low-quality internet content/ad environments.  With the rise of AI in the content game, lowering the cost of creating content to almost nothing, this could get bleak if advertisers don’t figure out how to properly attribute credit.

The Solution: Incrementality-Based Measurement

If advertisers measured the number of sales or how much brand lift was caused by the ad they paid for, we would effectively starve the beast that is click-bait/made-for-advertising style content. 

Instead, we would reward more well-lit, cleaner websites & ad environments where the ads actually have a chance to do their thing.  From a lens of incrementality/causality-based measurement, then, it becomes apparent that higher-quality publishers could thrive if not for flawed attribution.  

By adopting incrementality-based measurement, advertisers not only improve their ROI but also reward higher quality journalism and improve the internet environment for us all.  

Reach out to Measured to learn more about how to get started with this form of attribution.