Display Advertising has grown to be a $ 9.3 B industry in 2007 (WW), and is expected to grow to almost $ 18 B by 2011. This growth has been driven by both the explosion in web usage as well significant innovation by the display service providers. This innovation includes enabling standardized ad placements, consistent metrics and reporting as well as systems and processes to enable efficient buying and selling of ad inventory.
Yet, the display advertising business faces significant challenges, especially in terms of demonstrating its effectiveness. Users appear to ignore most display advertising: click through rates for displays ads are less than 0.5%. In fact, there is anecdotal evidence to indicate that users automatically block out the right column where most ads are placed. A leading software company tested a new version of their ERP application where they had designed the UI to look like a browser interface with a host of contextual links in the right column. When they tested the product for usability, they were surprised to find that not one of 500 testers used any of the functionality in the right column. Bewildered, they conducted focus groups to understand why. And users told them that they were habituated to ignore the right column because they associated that with ads!
In this posting, I will briefly propose a framework to discuss the evolution of display advertising and begin to make the case for accelerated innovation to improve the effectiveness of display advertising.
The first wave of innovation, Display 1.0, in display advertising established the foundations for a new medium. This included defining what would count as an impression, agreeing on standards (ad format, size, etc.) and building the systems that would allow large numbers of advertisements to be placed, served, tracked and paid for. Companies like DoubleClick, aQuantive (Atlas), 247 Real Media and comScore emerged out of the wave of innovation.
The second wave of innovation in display advertising, Display 2.0, was focused on improving the overall market efficiency, and were in some ways an attempt to “catch up” with Google’s auction based contextual advertising juggernaut. As part of the Display 2.0 wave, companies aggregated inventory (especially across mid and long tail publishers), improved pricing transparency, establishing risk sharing models (such as CPA pricing) and created markets to buy and sell remnant inventory. While there has been much activity on this front in the last 3-4 years, including M&A by the GYM (Google, Yahoo, Microsoft) gang, its still early days, and several new and exciting Display 2.0 start-ups have been funded in the last 6 months.
The third wave of innovation in display advertising, Display 3.0 will, I believe, focus on improving its effectiveness. There are many levers that can be pulled to improve display advertising ranging from dynamic creative construction to improved targeting and better landing page optimization. The common theme across all of these is the attempt to apply algorithmic approaches to improve the effectiveness of a medium that has been historically dominated by the “creative types”.
In subsequent posts, I will flesh out this framework and talk about the implications for the various stakeholders in the display advertising ecosystem – advertisers, agencies, ad networks/other intermediaries, and publishers.
I would also love to hear your comments about this thesis !!