September 13th, 2007
Many publishers either don’t have a strategy for maximizing network revenue or use aging technies such as daisy-chaining to
Out of all the publishers that I’ve talked to many don’t have a solid strategy for maximizing revenue from ad-networks. Many simply don’t understand how networks price, since most are black-boxes that don’t publish how they optimize and choose which ads to display. Yet, there are a couple factors that I find can be large drivers of revenue.
The more times an individual user sees an ad, the less likely he is to respond to it. Ok, seems obvious right? What you may not realize is exactly how quickly user response to an individual ad drops. The following graph is fictitious but representative of the normal response curve of a user on a single site to repeatedly seeing the same ad.
What the above shows is that if you are to maximize revenue you need to start thinking about users and not impressions. A user that’s been on your site for hours and has seen a hundred ads is far less valuable than someone who just logged-on.
Of course every ad-network will tell you that they have a large # of advertisers and deals and that you shouldn’t worry about such things — but lets not forget the Pareto Principle, also known as the 80/20 rule. A small percentage of top advertisers will generate the majority of revenue (and hence higher rates). What that means is that each ad-network will only have one or a couple high CPM ads.
Hence the effective CPM that you receive per user from a network declines as that network continues to see him over and over again. The larger the network the slower the decline, but each will look similar — here’s a rather rough sketch of what various network payout look like (again, numbers are hypothetical, but shape of graph will generally be correct).
Obviously daisy-chaining will not work in this situation as both the medium and large networks have paying ads for each individual ad-view. In the hypothetical example above, you would want an individual user to see the following sequence of ads to maximize revenue:
Comparing the effective CPM of each network individually versus optimized together:
What you see is that you can vastly increase your CPMs by distributing your networks. Now — although these are fictional numbers — the concepts are real and they work. So how do you do it? Rather simple!
It’s impossible to allocate impressions on a per view basis as I did above so we must rely on a little bit of approximation. The way to do this is to setup multiple placements or zones with your ad-network and then to frequency cap them individually within your own adserver. The above could look something like this:
The key here is not to over-complicate. Sure, a Myspace, Facebook or Bebo may create hundreds of different placements each with different caps and priorities, but there are two reasons you shouldn’t
- It’s incredibly resource intensive to manage
- You don’t have enough inventory
Each placement needs to run a minimum amount of volume otherwise pulling out the effective CPM will be nearly impossible. A lot of pricing is based around user response to ads — eg CPC or CPA based pricing. Since clicks and conversions are rare events you need to have enough volume in each placement to get a predictable effective CPM. On CPC networks you can probably get away with a couple thousand impressions per placement per day but on CPA you’ll want to go closer to ten to twenty thousand.
There is some art here as you will have to update both the frequency caps and the pricing on your placements regularly. The first couple times chances are you’ll see your network cpms fluctuate as you play with the caps & inventory allocations but as you get a hang of it you should gain some serious lift.
Enough for today — next, how to effectively target network placements to maximize revenue.
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- RTB Part I: What is it?
- Introducing “buy side” versus “sell side”