Audience Verification - Another Awful Idea?

By validating audiences at the campaign level, there is the potential for massive discrepancies and friction in the buying process.

There is a lot of talk and hype surrounding audience verification these days. Advertisers and their agencies like the idea of deploying vendors like comScore or Nielsen along with their campaigns to validate the audiences reached within a campaign. The process for verification is pretty straightforward and most folks probably don’t think there is much risk in it. However, by validating audiences at the campaign level, there is the potential for massive discrepancies and friction in the buying process.

I can appreciate why an agency would want to clearly understand the composition of the audience reached with their campaign and limit exposure to people outside their core target. However, the current methods for determining audiences create a number of challenges for both the client and the publisher. When a buyer asks a publisher to deliver a certain audience, say men 18 to 34, there are few ways to approach the targeting. The publisher can deliver the campaign in context, like sports, where they know from prior research that they have a high concentration of men 18 to 34, or they can directly target the audience using either first-party registration data or third-party data sources like BlueKai.

But this is where the friction begins. By using a different source of data for targeting versus verification, there will inherently be a large discrepancy in the audiences reported. When a client receives a report that has a major audience discrepancy, there can be a number of negative outcomes:

  • Lost faith in buyer and plan
  • Confusion on why the audience wasn’t reached
  • Question performance and the channel
  • Potential cancellation
  • Less likely to renew with publisher

At the end of the day, no one likes discrepancies and when they happen it creates more work for both the agency and the publisher. The agency often rushes to reallocate spend or make billing adjustments. The publishers are then wasting inventory, losing revenue, and doing additional work to either justify the inventory quality or the associated audience composition. The vendors and their associated data can also be questioned, in which case they risk losing business and adding confusion and cost to the buying process.

How can we avoid this additional tax on the industry while still helping clients and agencies understand the composition of the audiences they reach with their campaigns? I would propose a universal standard for audience verification that can be used by both marketer and publisher. Or, at least, publishers should be demanding that the same data set used for targeting also be used to verify the campaign. The latter is not as efficient, but in the near term it would go a long way to limit audience discrepancies, provide the marketer with assurance that the right audiences are reached, and help limit lost revenues for publishers.

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