It's time to rethink and welcome new opportunities for audience buying - whether that means remnant, premium, and exchange or non-exchange inventory buys.
The year 2010 is experiencing rapid growth in digital display and a widespread adoption of real-time bidding. It is motivated by audience-based media buying, but we've also come to embrace the added bonus of greater reach and efficiency by pooling many bidders together in a transparent auction platform. Ad exchanges and supply-side platforms have enabled a fundamental change in digital display advertising by combining audience buying with algorithmic intelligence. But, let's not leave premium inventory out of our audience targeting discussion.
ClickZ recently reported that nearly 50 percent of targeted digital display campaigns will be purchased on real-time platforms by 2015. While this is a clear indication that real-time bidding and audience targeting are here to stay, the premium or guaranteed inventory will continue to be the bigger half of the pie chart. Demand-side platforms provide mass reach through inventory from the major exchanges and supply-side platforms, and some demand-side platforms can augment this with inventory not normally available on exchanges. In fact, I've seen this first hand as many brands and agencies are taking advantage of tools to leverage direct publisher relations to buy impression-level inventory based on their custom audience segments. In 2011, I suspect we will hear more about publisher direct tools that empower agencies and brands to capitalize on their publisher relationships in order to tap into premium inventories.
Should brands be built on remnant inventory or premium inventory? Tucked under this duality of premium vs. real-time bidding-powered remnant is another entangled pair of media buying principles: audience vs. content. This idea of marketers having exclusive partnerships with publishers is motivated by the desire to have guaranteed control of content and placement, in addition to the control of audience. So the answer to this type of either-or question is why choose one type of inventory, when you can have both.
For many brands, premium buys and exchange buys also represent the balance between brand exposure and online response performance objectives. New bid management algorithms, such as multi-event optimization, will enable brands to scientifically balance these objectives. Thus, the full flexibility for inventory buying on both premium and ad exchanges will enable them to optimize both the exposure and performance for their brands, while increasing eCPMs and revenue for publishers. Recently, PubMatic released a study at the 2010 Ad Revenue Conference, which looked at real-time bidding and audience targeting in comparison to traditional run-of-network buys. The study found that real-time bidding outperformed traditional run-of-network by an average of 749 percent and audience targeted non-real-time bidding outperformed run-of-network, non-real-time bidding by an average of 324 percent. PubMatic's study also indicated that publishers generated larger revenue from real-time bidding campaigns by an average of 64 percent.
The combination of exchange trading alongside premium placement buys allows marketers to track campaign and creative performances across all inventory types and sources. The emerging solutions such as global frequency optimization and multi-touch attribution reporting will further enable marketers to visualize, control, and optimize frequency, ad placement, and messaging with unprecedented precision on both exchange and premium buys. Marketers can also cut exclusive deals with publishers that match advertiser-defined audiences' segments.
On the other hand, the ability to sell audiences directly to an advertiser enables a publisher to gain more control over inventory. Publishers can price inventory at different CPMs and manage yield internally within their own ad server - sending only inventory that matches an advertiser's audience. Last, but certainly not least, there's a clear opportunity for publishers to build custom packages that provide agencies the ability to purchase pre-defined audience segments for home page takeovers, custom placements, and unique channel buys. By working directly with marketers, publishers can track the volume of impressions that matched the custom-build audience from an agency. These levels of transparency enable publishers to monitor and understand the advertising spend across audience-based campaigns.
In 2011, we'll start to see audience targeting gain market share and advertisers tap into premium inventories for audience-enabled campaigns. The beauty of today's digital advertising ecosystem is that it's not an either-or situation and there's plenty of ways to leverage the best of both worlds. Having a mix of flexible media transaction modes at different block sizes is a sign of a maturing ecosystem and a meta-level efficiency gain. It's time to rethink and welcome new opportunities for audience buying - whether that means remnant, premium, and exchange or non-exchange inventory buys.
As Chief Technology Officer at Turn, Xuhui Shao focuses on the power of optimization, machine learning, and advanced analytics solutions in driving new business models, products, and services across all industries. Xuhui is responsible for architecting the machine learning and optimization technology to deliver the most effective data-driven digital advertising in the world. He is passionate about the dynamic online advertising community and works closely with industry leaders developing data transparency and consumer privacy protection.
For the last 12 years, Xuhui has practiced research and development in machine learning, statistical theory, and computational intelligence for Fortune 100 companies in various industries from banking, finance, online retailing, healthcare, insurance, marketing, and online advertising. As the lead inventor and co-inventor of three awarded patents in the areas of advanced analytics and optimization, Xuhui is a recognized expert in harnessing data and transforming analytics into actionable insights and optimization strategies.
He earned his bachelor's and master's of science degrees from Tsinghua University, Beijing, and his Ph.D. in electrical engineering from the University of Minnesota.
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