The Rise of the Demand Side Platform

  |  August 25, 2010   |  Comments

A close look at the evolution of automated bidding systems that place the right ads on the right pages for the best price. Last in a three-part series.

During the past few months, this column has briefly explored the history of digital ad serving. This month, we'll continue that journey as we look at recent ad serving developments that are creating significant changes throughout the industry.

Digital advertising, unlike more traditional mass media marketing, doesn't rely on group exposure models for its success. In reality, online advertising is less about reaching the greatest number of eyeballs and more about reaching the right eyeballs. This means that standard "blind" ad serving models (where ads are being served to any open ad slots on any available pages within the ad network) are being replaced by "smart" ad networks that look for the best recipients for an ad's message, regardless of where in the network they visit.

Not only does this approach mean that consumers receive more relevant ads, but it also means that advertisers get better results and higher conversion rates for their campaign because they're reaching a higher percentage of consumers who may take future action in line with the advertiser's needs.

But there's also a third winner in this scenario in the form of publishers who are able to better monetize the impressions they serve on behalf of the advertisers. Historically, most websites needed to divide their available inventory into a tiered value model to identify which pages were most popular (attracted the greatest number of eyeballs) and which were less popular. As a result, ads that appeared on the popular pages of a site cost more per impression than those on the less popular pages.

Because advertisers are able to rely on more behaviorally-driven ad models today, which page an ad appears on is becoming less and less significant. Instead, second or third tier online inventory can now be sold at a premium price, not because of where or when the ad runs, but because of who is seeing it when it does. This allows publishers to increase the value of all of their site impressions without having to weigh in on a page popularity contest first.

Most ad networks today utilize some level of audience targeting which allows publishers to better identify site visitor characteristics and behaviors that can be used to help define possible future interests and actions. Through the use of cookies, each user's browser is tagged and when that consumer revisits a site or ad network, that history is used to direct ads that are more in line with the personal needs and interests of the consumer.

These behaviorally-driven models allow advertisers to select the targeting criteria they wish to use (including advanced demographic, psychographic, and technographic parameters) to reach their core audiences instead of needing to buy ad impressions based on a blanket CPM (define) cost.

This approach has led to the rapid rise of demand side platforms that can serve ads to specific inventory slots based on relevancy to individual consumers and priced based on the demand for that target audience.

Most demand side platforms utilize real-time bidding practices to "sell" single impressions to advertisers based on how much they're willing to pay for those impressions. Like Google AdWords bidding, real-time bidding systems allow advertisers to remain competitive on price and still serve ads to those consumers most interested in seeing them. This means that advertisers can set budget limits, tweak their targeting criteria, and optimize campaigns based on the parameters they're using and the results they're getting. This level of transparency is a significant change from most previous ad network serving models.

While the features and services from demand side platforms differ (this is an emerging technology, of course, and is still very much in flux) a few significant features that advertisers should be on the lookout for include advanced and accurate audience targeting capabilities, easy-to-use inventory control and bidding dashboards, and the ability to set frequency caps on the ads being served. Bottom line on the last point is that reaching the "right consumer" too many times can lead to a significant decline in interest.

You should also be aware that some demand side platforms are willing to work with "buying groups" that buy discounted chunks of inventory that are then divided among participants. There has also been a recent emergence of data brokers (not unlike stock brokers) who can work with advertisers and demand side platforms to set up media deals that meet the needs of advertisers.

The one thing that is certain about these emerging models is that they will continue to evolve. The good news is that digital advertising is finally breaking away from largely insignificant reach and frequency models associated with mass media and are finding an exciting new path which will become the foundation for targeted advertising for years to come.

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ABOUT THE AUTHOR

Rob Graham

Rob Graham is the CCT (chief creative technologist) of Trainingcraft, Inc., where he heads up development of customized training programs for a wide range of digital marketing, entrepreneurial development, and digital media clients.

A 20 year veteran of digital media, Rob has served as the CEO of a multimedia development company; an interactive media strategist; a rich media production specialist; a Web analytics consultant; a corporate trainer and seminar leader; and a chief marketing officer.

When he isn't on the road presenting training workshops, Rob teaches at Harvard University, Emerson College, and the University of Massachusetts - Lowell where he teaches classes on Digital Media Development, Web Store Creation, Software Programming, Business Strategies, and Interactive Marketing Best Practices.

He is the author of "Fishing From a Barrel," a guide to using audience targeting in online advertising, and "Advertising Interactively," which explores the development and uses of rich-media-based advertising. He has been an industry columnist covering interactive marketing, digital media, and audience targeting topics since 1999.

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