Greg Hills

[Thanks to AdExchanger for publishing the original of this post, which I'm now reblogging. There was a lively comment thread over on the original post.]

My work focuses on the economics of advertising, but recently I’ve been thinking about the political economy of advertising. After all, advertising dollars don’t have a mind of their own. They need industry professionals to push them around from one company to another. Trusted personal relationships have historically been the conduits through which ad dollars flow.

This relationship driven world of advertising is now being replaced by the data driven world of advertising. RTB, DSP, SSP….these acronyms have got sales leaders thinking. How do you staff up for this alphabet soup of new business models? Who do you call on and what do you tell them? What does the advertiser need and how do you win their business as a publisher?

When I was a media planner, I had the answer to the last question. I could tell you what the advertiser needed and I would decide whether or not you met that need. This is the type of arbitrary power that brings a recent college graduate towering seafood platters, custom sneakers, and a taste for fine scotch.

Working on the new demand side, I still meet with major publishers and tell them what my clients need. The needs themselves don’t change that much, in fact. Brands still want effectively priced advertising units in safe environments that will get consumers to engage with and buy their products. The key shift is that I no longer decide whether any specific publisher or web page fits that need. The algorithm is the new decision maker.

The algorithm is a better decision maker. It bids rationally by fully incorporating learnings from past performance. It can value tens of thousands of individual impressions per second based on multiple data points.

Algorithms also remove the physical constraints that limits agencies to a small list of publisher partners.  An actual media planner using phone, fax and email can evaluate proposals from a couple dozen properties at most. From a time management standpoint, it is inefficient to actually go through with buying and optimizing more than a dozen sites/networks. But with algorithmic buying, the agency can buy and optimize in real time across thousands of sites.

Advertising is the art of persuasion but personal persuasion has now been taken out of the media buying process. Is it fair to make publishers compete on raw performance and not give them any appeals process when they lose? I would argue yes. It’s certainly a better deal for the brand whose marketing dollar is now working harder. I’d also argue that it makes things more fair for publishers, since they are no longer competing on the basis of access to decision makers. The algorithm is the decisionmaker, it will evaluate all publishers in the secondary channel, and its unbiased.

The traditional sales conversation — scheduling a conversation, determining if the product is a fit, then negotiating price — still happens but it occurs between agencies and technology vendors, not between agencies and publishers.

Now, the agency-publisher conversation is less of a sales conversation, and more of a collaborative problem solving conversation. Both agency and publisher are solving for the same thing: getting as much inventory as possible in front of the true decision maker, the buyside’s bidding algorithm.  Below is the complex equation – the now infamous ecosystem slide:

Ideally, this chart would be much simpler. There would be one big pool inventory that everyone plugged into, and bidding optimization would be entirely automated. This is not the case, unfortunately. Between the brand and the publisher, there are lots of different TradingDesk+DSP+Exchange+PubOptimizer+Publisher permutations, some of which may lead buy-side actors and sell-side actors to be disconnected. Coarse-grained optimization, like eliminating entire contextual channels or entire exchanges, also removes individual publishers from consideration.  So the conversation becomes about managing the supply chain to minimize these disconnects.

To use the old media buying paradigm as a metaphor, its as though agencies and publishers are administrative assistants, working together on logistics so that the the publisher’s inventory can get in front of the ultimate decision maker, the algorithm. That doesn’t sound glamorous, but getting the supply chain right offers much greater rewards than even the biggest direct deal.

Tagged: algorithm, buy-side, optimization, publisher relations, sell-side, yield-optimization