Winning In An Ad Exchange World

Pascal Bensoussan of Aggregate Knowledge"Data Driven Thinking" is a column written by members of the media community and containing fresh ideas on the digital revolution in media.

Today's column is written by Pascal Bensoussan, VP of Products at Aggregate Knowledge, a buy-side optimization platform.

Over the last two years, ad exchanges have brought an unprecedented level of targeting and efficiency to display advertising.  However, early adopters may have already reaped the greatest benefits of the ad exchanges (the lowest hanging fruit has already been eaten). Over the next two years, as adoption grows and more ad exchanges, ad networks, and publishers fight for the same cookies, it is going to become increasingly more difficult to achieve sustainable value from media arbitrage decisions.

The true winners of the ad exchange era will be those few companies that will be able to leverage a company-wide business strategy, a proven operational discipline, and a unified platform to excel in the following three areas:

  1. Centralized data collection and custom audience management
  2. Cookie-level retargeting and impression-level bidding
  3. Creative optimization and personalization

Everyone else will merely fight for what’s left.

Many advertisers and agencies have sharpened their teeth in one or more of the three areas listed above through one-off, disconnected advertising campaigns that may only have provided a taste for the future possibilities without revealing their true potential.

There is another barrier, mostly psychological. Most marketers and media planners still approach their digital campaign with a one-size-fits-all model in mind, targeting a large, but "average" audience that ignores the true disparities between its members. As a result, media planning revolves around the comScore 250 web properties where this elusive and generic audience might be. In addition, campaigns pay average CPMs that discount the true value of each impression, and deliver generic marketing messages designed for the "average" audience.

Joanna L. O'Connell with Razorfish wrote in Redefining Transparency that the transparent nature of ad exchanges brought a multitude of optimization levers never before at her disposal. Transparency brought new insights, greater repeatability in media buying decisions, and more direct control over campaign performance instead of the poorly-informed and surface-level optimization decisions only allowed by more opaque ad networks.

While I agree with Joanna, I believe that transparency is a double-edged sword that will make it harder for agencies and advertisers to buy targeted media cost-effectively and at scale, unless they dramatically expand the realm of their decisions beyond the simpler media buying one. Best-in-class companies will take full control over audience and creative decisions to deliver the best messages to the right audiences.

So the most important question will become how to leverage ad exchanges to test and reach the right audience with the right creative.

In his MediaPost article “2010: A Watershed Year for Digital”, Eldad Persky justifiably points out that combining the ability to buy the right audience cost-effectively and the ability to tailor the right message to the targeted individuals into a tight marketing machine is pretty close to the "Holy Grail" of marketing.

Ad exchanges were purposefully built to enable this game-changing advertising model, but very few companies provide the integrated and transparent infrastructure necessary to reap the full benefits of those ad exchanges.

The value of an integrated approach is significant, but the technical challenges for delivering a cost-effective and easy-to-use infrastructure should not be under-estimated. Doing this right requires either a lot of money or a hard-to-find combination of deep industry expertise and proven high performance engineering to deliver an integrated system capable of:

  • collecting and storing terabytes of user data with massively parallel I/O processing
  • synchronizing custom audience segments with robust auditing and cost tracking, and
  • delivering micro-targeted creative messages without burdening the creative design and trafficking process

First, the ability to leverage a universal tagging structure to centralize massive amount of disparate data from advertiser sites, campaign history, and third-party providers make it possible for agencies and advertisers to define their own audiences as precisely as they want. Next, cookie-level retargeting and impression-level bidding across multiple ad exchanges allows for a multitude of custom audience segments to be targeted via any media buy at scale and cost-efficiently. Finally, the ability to serve thousands of creative variations, optimized dynamically to each user – based on their profile, past site visits, and campaign history – with one single ad call and creative template, brings a new level of relevance and performance to digital campaigns.

Seamlessly connecting and controlling those three fundamental pieces of the value chain, in a completely transparent manner, will deliver huge and sustainable benefits to advertisers and agencies:

  • Combining ad serving data with third party attributes and site traffic data to build a richer, 360 degree view of each unique user
  • Cherry-picking the most promising look-alike users (i.e. similar profile) and like-minded users (i.e. similar interests or behavior) at scale
  • Segmenting and retargeting past visitors with the best possible messages
  • Building, recombining, and testing new audience segments quickly and cost-effectively
  • Managing impression-level bids and dynamic creative decisions for optimal ROI

Ad exchanges are just a powerful enabler. Under their influence, a few companies are driving fast to achieve greater and more automated control over every audience, media, and creative decision.  With that in mind, look around you and ask yourself: is my company really ready to win on the exchanges?

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3 Comments

  1. Nicely done!
    Agree with most of what you said except a couple of things related to data analytics: I do not think finding look-a-like audience is the right framework; also, segmentation could be a bit outdated/insufficient analytics technique to handle the level of complexity unique to this.

    Reply
  2. Huayin,

    Thanks for the comment, which I agree with.

    Let me clarify.

    As you point you, the quality of both "look-alike" and "like-minded" comparisons is relatively low when done at the segment/attribute level (e.g. "car intender" or "high income").

    However, in our experience, those comparison techniques become extremely powerful if they can run in real-time down to comparing individual users based on their event streams, without a-priori segmentation (e.g. ads they clicked on, products they added to their cart or purchased, articles they read).

    To your point, real-time bidders and dynamic ad servers have to be able to perform real-time, user-level similarity computations to be most effective. This is a requirement that we, at AK, are very familiar with.

    I am happy to take this discussion off-line if you would like more details.

    Best,

    Reply

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