The ‘Shazam Of Targeting’


Today’s column is written by Lung Huang, head of strategic partnerships at 84.51°.

As a fan of HBO’s “Silicon Valley,” there are always parallels to the digital advertising industry that make me laugh uncomfortably at the story lines.

In one episode, two of the characters presented their See Food app to investors, who called it the “Shazam of food,” which was completely counter to the original intent. This feedback enabled them to refocus their app to identify food types, but it ended up only being able to identify “hot dog” or “not hot dog.”

If I was as entrepreneurial as some of the characters on “Silicon Valley,” I would build an app called See Targets, and I would characterize it as the “Shazam of targeting.”

My pitch would go something like this: “What would you say if I told you there is an app that can tell you if you have a good advanced audience segment or a not-good advanced audience segment?”

All Targeting Is Not Created Equal

For my app to really take off, it has to learn what is considered to be good targeting.

I am continually amazed with marketers who look at a data dictionary of any data management platform or demand-side platform, pick an off-the-shelf audience segment and call it a day. This willy-nilly, off-the-shelf segment from your DMP can’t be the only targeting element that you’d use since it can be used by anyone who would buy that segment after you.

Good targeting takes time and effort and should pass this litmus test when picking an audience segment:

  1. Can you validate the audience segment and its source?
  2. Are you able to get the desired reach of this audience segment in the marketplace?
  3. Will this audience segment resonate with your target audience?
  4. What was your customers’ reaction from exposure to the advertisement?

To be truly data-driven in their targeting, marketers will need to be the leader in understanding their data and the data that is available.

It’s A Mad, Mad, Mad, Mad, Mad World Of Targeting

Now the true test for any application is the adoption and usage within the marketplace. I can honestly say that, based on most targeting elements out there, my particular app is needed and would be kept quite busy. I am sure I know someone who would actually use it.

Further underscoring this urgent need is Fox, Turner and Viacom announcing OpenAP, which will be an advanced audience platform standard for cross-publisher audience targeting. In theory, when launched this summer, the buyers will be able to use one audience target that will work with all three networks’ systems. NBCUniversal made a similar announcement some years ago, but did not mention any new partners.

This is big since Fox, Turner and Viacom are all industry-leading companies that collectively sell about $71 billion annually in advertising, according to eMarketer. They are also fierce competitors, and rarely do any networks not owned by the same company ever work together. This means that the networks really believe that the bigger competitors are the large digital publishers versus the other broadcasting networks.

I applaud these networks and give them my patience when everything does not go out on time or as planned. This is not an easy undertaking, especially when you consider the many different systems and services. But the real fireworks show starts when that same segment will be priced differently across the three networks.

Follow Lung Huang (@Lung_Huang), 84.51° (@8451group) and AdExchanger (@adexchanger) on Twitter.

1 Comment

  1. Ted McConnell

    Absolutely. Its kind of an insult to Shazam, which is right a lot. The big issue imo is not that observational data is "wrong" but that an observational dataset is selected as a surrogate of the desired target. Technically, a segment of people who looked at content about Television sets, for example, is probably correct inasmuch as those people did that. But, will they buy one? Did they already buy one? A Sony? Are they receptive? and so on.


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