Home On TV & Video Is Attribution Bias Killing Brand Metrics?

Is Attribution Bias Killing Brand Metrics?

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On TV And Video” is a column exploring opportunities and challenges in advanced TV and video.

Today’s column is written by Brent Gaskamp, senior vice president of North American development at Videology.

My overexposure to industry events has led me to really examine what’s being represented in our marketplace by different constituents versus the reality of what’s actually happening in the market.

Many marketers have long considered TV to be the best driver of ROI. Recently, however, as data continues to play an increasingly important role in evaluating return on ad spend, TV is taking an undeserved hit.

Since attribution data and the associated metrics tied to sales lift or conversions have their roots in digital media, TV may not be getting the true credit it deserves. Data-rich digital giants are often the winners in these kinds of attribution chains and the beneficiaries of redirected ad budgets.

The end result is a new kind of attribution bias aimed squarely against TV that could be costing the industry significantly. Unfortunately, it’s not just the TV companies that fall victim; it’s brands that are seeing their performance suffer.

The Rise Of Attribution Bias

The early days of digital advertising were dominated by display, and attribution was largely focused on clicks or call-to-action metrics. This environment attracted more direct-response advertisers, as brands preferred the awareness-building capabilities of TV to drive what were primarily offline sales opportunities. Then, three things happened.

First, digital’s influence in the path to purchase continued to grow, along with the rise of ecommerce for everything from clothing to groceries. Second, the measurement of offline sales tied to digital media exposure became much more sophisticated. And, finally, digital giants like Google, Facebook and Amazon came to dominate the industry, touching at least part of almost every consumer’s journey to purchase.

Before most major purchases – and even some not-so-major purchases – someone will search, research, visit a website or consult social media. What this means is that it’s likely an offline purchase was to some degree influenced by digital media. Whether a consumer used Google to search, was retargeted on Facebook or ultimately made a purchase on Amazon, any one of those media sites could potentially claim credit via attribution techniques.

This is one reason why in the last 18 months, major advertisers have doubled down on digital. For example, Adidas decided to leave TV advertising behind earlier this year in an effort to quadruple its ecommerce revenues by 2020. RetailMeNot is also reportedly moving its working media budget into digital video from linear TV spend.

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What this leaves out of the equation, however, is what happens at the top of the funnel – the realm still dominated by TV. If exposure to a TV ad prompted a search, which led to retargeting and a purchase, this would not necessarily show up in reports generated by digital media companies. In theory, this could cause a marketer to cut spending on TV and give more money to digital channels, which could lead to a sales decline.

The truth is that TV works. Coca-Cola’s CMO, Marcos de Quinto, recently spoke out at a Beverage Digest conference about how “[d]igital is important, of course, but the effectiveness of TV is still very, very critical for our business. It still offers the best ROI across media channels.” Dollar Shave Club also saw a 100% increase in revenue upon moving to TV advertising.

Moreover, some companies are moving from TV to digital and then pulling out of digital, similar to P&G’s recent move to cut more than $100 million in digital marketing spend.

The Paradox Of Data-Driven TV

Ironically, convergence may actually be exacerbating the problem of attribution bias. TV is being held to the same data standards as digital, but TV has a different place in the purchase funnel.

In terms of targeting, TV now follows the same protocols as digital video, often sharing the common data sets across screens. This means that when calculating unduplicated reach against a strategic target, TV and digital are equal partners, each contributing to the overall delivery of cross-screen campaigns.

It would seem then that TV’s problems in attribution would be solved. But when it comes to attribution – even with the application of advanced data – TV isn’t digital, and the rules are different. Premium TV remains a huge driver of ROI, but it is not that “last click.” TV is a top-of-the-funnel driver, and digital media is a bottom-of-the-funnel driver. Advertisers need both.

What’s important when measuring attribution is tying them together. Using data to link digital and TV investments allows an advertiser to measure true cross-channel attribution, including instances where exposure to TV influenced digital behavior and, when applicable, how it drove offline sales. Most attribution bias is driven by a siloed measurement approach that does not look at what is happening across the entire media portfolio. It may not be the fault of the walled gardens, but the commitments made by marketers to any one of these digital giants based on a single-source attribution analysis impedes their ability to understand the full purchase-decision funnel.

Now What?

Attribution is not black and white. And, in truth, many companies have not had the infrastructure to model data in a way that allows them to truly understand how their investments are driving ROI across TV and digital media. But now, those capabilities exist.

Those who can are now using data to not only improve TV advertising, but also to improve cross-screen measurement. We now know that bringing advanced data to TV can produce exceptional results that mimic the precision of digital, yet each medium retains its own unique characteristics that must be accounted for – including contribution to attribution – to drive maximum performance.

Follow Videology (@VideologyGroup) and AdExchanger (@adexchanger) on Twitter.

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