Commentary

Attribution For RTB Marketers: Why Should I Care?

If you work in real-time advertising, you shouldn’t just care about attribution models, you should be downright obsessed with them. Why? Because attribution means figuring out which aspects of your campaign are working, and how you can do better. And if you don’t care about that, well, then real-time advertising might not be your true calling.

Let’s remember that the great promise of real-time advertising has always been that it’s much more efficient and trackable than offline advertising. No, real-time marketer hasn’t turned advertising into a perfect science as some of its early evangelists had hoped, but it has turned advertising into something much more rigorous and efficient than ever before. And attribution models are at the heart of this new rigor and efficiency. A good model can make it much easier to understand how each dollar you’re spending is contributing (or not contributing) to the success of your campaign.

In other words, saying you don’t care about marketing attribution is a bit like saying you don’t care about money.

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Take the simple example of someone arriving at a software company’s website after clicking on Facebook Exchange (FBX)  ad. Let’s say this customer fills out a form on the company’s website. And let’s also say we know that the customer eventually became a client after attending a webinar.

If you’re not using an attribution model -- or are using an overly simplified and misleading model -- you might conclude that the click on the FBX ad and the viewing of the webinar drove the conversion. And you might then start putting all of your dollars toward search ads and webinars.

But what if the customer had seen lots of the software company’s display banners before ever clicking on that FBX ad or viewing that webinar? What if the customer had also read a native article about the software, or seen a pre-roll on YouTube? These might be critical touchpoints that moved the customer along. After all, we have mountains of data indicating that many types of conversions take place only after multiple interactions withtouch points. In the absence of an intelligent attribution model, it will be impossible to know how those earlier touchpoints contributed to the conversion. It’s a bit like a winning basketball team deciding that the best player on the team is the one who makes the last shot.

It might seem hard to believe that marketers today could still be so cavalier on the subject of what’s driving conversions. And most marketers certainly know that the last-click approach described above makes little sense. And yet, amazingly, many real-time marketers (perhaps as many as half) are still using last-click models.

That's not all. If attribution modeling has always been crucial for real-time marketers, it’s perhaps even more crucial than ever in today’s mobile and cross-device world. While marketers used to think about different touchpoints on a single device, we now need models that allow us to understand the complicated relationship between the given type of media and the given screen. And we need models that can account for the bridge that mobile provides between online and offline channels. If you’re trying to make sense of all of this data without an attribution model, you’re essentially flying blind.

This doesn’t mean there aren’t fair criticisms of attribution modeling. Some models are better than others. And some marketers have oversold what marketing attribution really can do. It can’t, as some people mistakenly think, give you a definitive, absolute truth. When you’re building a model, you’re always making decisions about how much value to assign to different components of a campaign. For this reason an attribution model is more of a macroanalysis than a microanalysis tool.

But such macroanalysis makes all the difference. According to a report in Forbes, 90% of marketing organizations that have begun to use attribution models “are seeing significant benefits.” The benefits cited include a “better understanding of the customer journey” and the ability to optimize the media mix in a given campaign.

It comes down to this: Attribution models provide valuable insights. Those insights can inform your next spend, which can save you money and increase conversions at the very same time. How can anyone not care about that?

2 comments about "Attribution For RTB Marketers: Why Should I Care?".
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  1. jack Brown from BDAI, September 25, 2014 at 3:11 p.m.

    You are absolutely right on each and every point. And yes they should care considering the majority of real time campaigns are currently throwing away up to 50+% of their ad spend.

    Your article echo's exactly what we at BDAI we have been screaming from the mountain tops. Our product / service is Algorithmic Attribution. Our proprietary algorithms are best of bread we identify and assign conversion credit across all touch points preceding the conversion. Our Algorithmic attribution delivers transparent actionable data beginning 72 hours from the start of the event and daily until event conclusion. We analyze both converting and non-converting paths across all channels. The complete digital journey of the customer not just the last viewable cookie.

    Our software is a powerful provider of actionable data so you can better spend your ad dollars; it provides a series of additional content to facilitate better decisions including:

    • Time that ads are "in view" by a consumer
    • Ability to ascertain quality (>5 seconds in view) and premium
    (>10 seconds in view) placements for maximum buy efficiency
    • Which websites ad placements were viewed (includes
    exchanges where this data is not readily available)
    • Which IAB formats are performing best - relative to other parts
    of the campaign
    • Proper assignment of CREDIT for which ad WORKS best… not
    simply consumer's last touch
    • Ability to run unlimited tags without degradation of site
    performance
    • Ability to apply a consumer panel poll to secondarily validate
    digital outcomes reporting
    • Ability to overlay customer-file analytics (determined with
    PRIZM data)
    • Provide insight into both the psychographic and demographic
    profile of visitors

    Decreasing granularity, allowing the data to identify the correlations and insights within the marketing effort. resulting in up to 40+% lift in ROI.

    "How can anyone not care about that"

  2. Jonathan David from Tapstone, October 2, 2014 at 1:02 p.m.

    Jeff makes a valuable point and I have to agree – not being interesting in attribution IS like not being interested in money. But once we finally all agree on the importance of attribution, we’ll need to help advertisers identify the most relevant attribution approach for their goals – be it a post-view/view through or post-click. My sense is that illuminating the specific strengths of each will be the next step toward better use and incorporation of attribution data in to digital campaign strategy.

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