In an earlier post, I teed up the idea of Display 3.0 and how the next wave of innovation in display advertising will focus on improving its effectiveness. In this post, I will begin to flesh out the Display 3.0 concept.
It is widely accepted that click through rates for display advertising are abysmally low, less than 0.25 % in aggregate. Recent research indicates that even these numbers might be over-stated: in a recent study (http://www.redherring.com/Home/23756), 6 % of users account for 50% of all clicks and 68 % did not click on a single ad. Clearly click through rates present an incomplete picture and there is brand value associated with placing the right ad in front of the right person at the right time and in the right context. But studies indicate that most users ignore the display ads that they are exposed to, especially static banner ads. Yet, other studies indicate that even if a person does not perceptibly notice a display ad, repeated exposure leads to a positive perception of the brand (see http://adverlab.blogspot.com/2007/09/study-banners-work-even-when-overlooked.html).
So, other than concluding that there is a need to over-haul the metrics associated with display advertising (which is a topic for another day), where does this leave us ? I think that there is an immense opportunity to improve the effectiveness of display advertising and that doing so has the potential to significantly accelerate the growth of the industry by accelerating the shift of both brand and direct response $$ to display advertising and possibly even opening up the SMB market for display (though that will take much more than the stuff I discuss below and is also a topic for another day).
So, what is Display 3.0 all about ? I believe that its about solving 3 core problems:
- Figuring out what Offer to show when an opportunity to serve an ad presents itself (I will refer to this as targeting)
- Determing what Creative (assuming there are multiple Creatives associated with each offer) to serve to meet the campaign goals (Dynamic Creative Construction)
- Deciding what Landing Page to send a user to should s/he click on the ad (Landing Page Optimization)
None of these are new problems and companies like Tacoda and Revenue Sciences pioneered a while ago. What’s new though is the opportunity to make targeting decisions based on a combination of behavioral, demographic, contextual, geo. and site (or url) related attributes. And to combine hundreds of data sources (including off-line data) to create user profiles that are then aggregated into 1000+ segments or possibly even to generate thousands of targetable attributes that can be used to generate custom segments on the fly. Also, in the new world, rule based segmentation will give way to predictive modeling and machine learning based segmentation. Turn is a good example of a start-up focused on driving improvements in targeting using machine learning while companies like NebuAdd and AdZilla are providing rich profile data that is on par with the data that Google collects via its tool bar (though their foot print is still tiny at this point – in the hundreds of thousands for both companies )
Traditionally, Creatives are manually created by the agency with huge pride and “skill” associated with developing the “right” creative. Over the last 2-3 years, multivariate testing has become popular and agencies develop 100s of creatives that are tested and multiple creatives are often used within a campaign – for example a different creative for each target segment. Yet this is still an extension of of the print world and represents a mental model that screams “we know what you want”. Also, most display ads continue to static in nature, a mis-fit, given the interactive nature of the web. In the Display 3.0 world, creatives will be dynamically generated (ideally in real time) and optimized (using machine learning) to ensure that the most effective creative is served when an ad call is made. Also, the creatives will be more akin to micro-sites allowing the user to engage with the ad (and even transact) without clicking on it. Finally, I believe that the distinction betwene ads and content will blur (the web’s equivalent of infomercials) a a result of dynamic creative construction. Afterall., if Aggregate Knowledge’s Pique network shows you a series of ties that complement the shirt that you are paying for on the gap.com site, is that ad or relevent content ?
Companies like Offermatica (recently acquired by Omniture) pioneered the notion of landing page optimization. Lead generation firms consider this to be a core part of their tool set. Yet there is an opportunity to further innovate on this front, with dynamic landing page generation, machine learning based optimization (leveraging the insight gained via targeting, and taking advantage of dynamic nature of the ad unit). Furthermore, closed loop analysis will enable conversion path optimization, which for the purpose of this discussion I will club with landing page optimization.
In summary, the Display 3.0 wave of innovation will dramatically improve display ad effectiveness via targeting, dynamic ad construction and landing page optimization. I will discuss each of these in more detail in subsequent posts.
Tell me what you think ?