If you mix real Cheerios with knock off Cheerios (at a ratio of 1:1) – and close your eyes, you can barely taste the difference – and you can save $20 per month!
This is one of the lessons I learned starting out in NYC at the age of 22. Accounting for my starting media planner salary and bare necessities, I had exactly forty dollars per month of discretionary income (half of which was due to the Cheerios hack). Needless to say, I didn’t have enough money to do anything besides work — which was ok, because I was completely obsessed with trying to understand how media buying and selling actually worked.
On weekends, when no one was around, I’d come into the office alone (at the old FCB office at 100 W 33rd street), spread out across the floor with stacks of printouts, maps of the media landscape, and a dog-eared copy of Media Planning and Buying by Jack Sissors and Roger Baron. My goal was to create a unified theory — one framework that explained how advertising value was created, priced, and traded.
Here are a real photo of me doing this ~17 years ago (complete with original iPhone photo resolution).
One concept tripped me up more than any other: GRPs — Gross Rating Points. They were, and, in some places, still are, the foundation of how media is transacted. GRPs are calculated as reach × frequency, a deceptively simple equation with one fatal assumption: all ad impressions are worth the same amount.
Even then, that didn’t make sense to me.
The impact of a billboard you walk past in Times Square is not the same as the impact of a billboard you drive by at the holland tunnel. The impact of a 15-second TV commercial at 2am is not the same as a 30-second TV commercial at 1pm. A digital video ad isn’t the same as a display ad. A viewable banner ad is not the same as one that never appeared on screen.
In my weekend scrawlings, I tried to rewrite the GRP formula. I added a third variable: impact. I even concepted a wearable device that could be outfitted on a panel of people, recording everything they saw across every media type— an omnichannel measure of advertising exposure and impact. (This was 2008, so wildly unrealistic at the time. Today, it’s probably possible.)
What I was reaching for was a system that priced attention and impact, not just exposure.
Back then, the media world was still largely IO-based. But today, in the era of programmatic and real-time bidding, we finally have something that can achieve what I was sketching on those floor maps: price discovery.
Price discovery is the mechanism by which each impression finds its own fair value — where buyers and sellers, through transparency, accurate descriptions, and an open auction, determine what an ad is actually worth based on its context, visibility, engagement, and outcomes.
In a sense, price discovery is the modern evolution of the GRP. It’s a more elegant, dynamic, and empirical way to measure value. Instead of assuming all impressions are equal, price discovery lets the market decide which impressions truly matter.
Bad things happen when there’s no price discovery.
When prices are opaque or disconnected from quality, good impressions get lumped in with bad ones. Incentives drift away quality and toward volume and obfuscation instead of impact. This is one of the most persistent problems facing the open internet today.
Using my Cheerios hack as an analogy… a GRP based system without price discovery, incentivizes sellers to put more and more fake Cheerios into the bowl because quality is not accurately valued or rewarded.
If we want the open internet to compete on a level playing field with walled gardens, buyers, armed with advanced DSPs, should be able to value each impression at exactly what it is worth to them.
That’s how we move from a world of GRPs and “lowest common denominators” to one of efficient and accurate valuation — and finally give the open web the economic foundation it deserves.