Part III: Network Optimizers to the Rescue (?)
Network Optimizers weren’t created to stop the bleeding of publisher sales to network sales, they were built to solve the latency and user experience problem by figuring out which network to serve what ad and outsource the implementation and management process for publishers. They accomplished this feat with raw manpower to start, and then got their hands on some venture cap money to build out technology and algorithms to figure it out and scale their operations.
As I mentioned in Part I, no one ad network wanted all the impressions a publisher could provide, they just wanted a little, or up to a certain frequency, or within a certain geography, or during a certain time of day, or with some other specific characteristic. If you were a publisher you could setup this kind of targeting to point users with certain characteristics to certain networks, but after a certain level of scale, things started to fall apart. it was much easier to just traffic one redirect to a network optimizer, and let them figure out which network was most likely to take the impression. Usually publishers would pull a weekly report to figure this out for themselves, but a network optimizer with an API connection to the ad network’s reporting server could pull data every few minutes and start to learn what impression the network wanted, and which ones it didn’t. By figuring out which ad network was most willing to take the impression on the first try and not keep redirecting users through the so-called daisy-chain of ad calls, network optimizers could reduce latency from the ad server, improve user experience, and increase revenue to the publisher. Optimizers could also handle the operational hassles of managing an advertiser blocklist through multiple ad networks, enforcing ad quality guidelines to keep tobacco or alcohol advertising off a publisher’s site, and could even do the bill collecting if need be. It was like outsourcing an entire back office of Ad Operations, Reporting, and Billing team all at once for a small revenue share.
As a business strategy, this worked pretty well – major digital publishers signed contracts to manage billions of unsold impressions with network optimizers like Collective Media, Pubmatic, AdMeld, and Rubicon Project. It was a giant step forward for publishers, but another industry force was just starting to emerge that would present publishers with a new opportunity as well as new challenges: the ad exchange.