It starts with a pitch.
We’ve all seen the story. Media agencies go into a pitch. Many of them have wonderful thinking. But when push comes to shove, the criteria used more often than not is the cost of media that agency is able to commit to — the effective price paid.
Publicly, agencies have complained about it, some of them vocally.
Clients, particularly marketers, seem to also admit it’s a problem. But with procurement and finance departments asking for clear KPIs, it’s not always a problem simply fixed. There are myriad reasons why. But fundamentally, it comes down to how we view and price media.
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How do we do that?
Largely, it’s based on cost to reach someone. Most channels have a variation on that metric. GRPs [gross rating points], for example, are TV’s way of representing reach. In digital, CPM [cost per thousand impressions] is often the number most are asked to focus on.
That’s a big problem. Mostly, because when you look at the data, not all reach should be priced equally.
Why?
Reach doesn’t equate to impact. If you’re on a shitty site for two seconds riddled with bots, it doesn’t really matter how many bots or how much ‘reach’ you get. You’re not going to see a sale.
Issues like brand safety, ad fraud and ineffective marketing are largely a consequence of a race to the bottom on price for the supply of media, without considering the effectiveness of that media in models. It’s like buying low grade steel for high grade construction.
You wouldn’t buy crap steel to build a bridge, so why are you buying crap media to build a brand?
That’s why I suspect the next big issue for our industry to solve will be building a more efficient and effective view on data to drive a price for effective media, instead of just efficient media. The good news is it’s now possible with a combination of cloud technology, statistical automation and the productisation of media analytics.
More effective market pricing isn’t without precedent. In the 80s and 90s, the bond markets went through similar issues — largely being priced on the cost of a bond. It created an ineffective market, and hedge funds and traders weren’t able to make effective decisions on their clients’ behalf because of that market problem.
Then along came a company called Bloomberg to solve it. Bonds and the hedge funds that trade them owe a debt of gratitude to Bloomberg as a result.
I think there will be a similar, emerging trend in the media market.
We call it media investment analytics, and my suspicion is it will be the antidote to the race to the bottom created by the first wave of programmatic.
And if we solve the media pricing problem, we might come a long way on prioritising effective, rather than efficient, marketing for our clients.
Henry Innis is a co-founder and managing partner at Mutiny. Mutiny’s core focus is WarChest, a media investment analytics product that helps marketers model and predict financial returns of brand, media and marketing activity.