“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media.
Today’s column is written by Venkat Krishnan, senior vice president of product at YuMe.
One of the best-known stories about the early days of Google has Mel Karmazin, then the CEO of Viacom, visiting the company, then still in its infancy. When the conversation turned to advertising, Karmazin compared selling ads to magic.
“Advertisers don’t know what works and what doesn’t,” he said. “That’s a great model.”
Google executives were taken aback. Putting an ad on television and hoping for the best, without any kind of measurement, struck them as terribly inefficient. They believed they could do better. “You’re [messing] with the magic!” Karmazin told them.
Years later, the tide seems to have turned in the opposite direction. Rather than fearing the metrics-centered approach to audience analysis, executives, marketers and others obsessively collect a wide array of information to help them make better business decisions. Sadly, at the same time, many are too busy looking at the trees to see the forest by examining individual metrics with care without tying each back to the overarching larger objective.
Despite all the benefits to transparency this proliferation of metrics has brought to the industry, many are either laser-focused on holding campaign success accountable to one specific metric or they’re on the opposite end of the spectrum, favoring mass measurement with success dependent on meeting multiple and often conflicting metrics.
Both approaches can be dizzying. Too often we fret about data points, such as the quality of the ad exposure, without understanding whether a quality ad exposure actually contributed to a brand meeting its overarching business challenge or marketing objectives.
To illustrate this point, consider the highly standardized document that comes across everyone’s desks daily: the request for proposal (RFP). When looking at an RFP, there are the key performance indicators (KPIs) and the overall business challenge or marketing objective. It seems logical that the overarching objective would influence the KPIs because KPIs can provide strong deterministic correlation to tie past events, such as video completion rate and click-through rate, to future events, such as product research or opinion changes. There is, however, a need to confirm or validate these future events with additional customized metrics specific to the overarching objective.
Advertisers judge their ad technology partners based on their ability to serve quality media. Additionally, if a planner or buyer finds that the media delivered met their quality standards, he or she must also be confident that the media impacted those who saw it.
To cure the metric vertigo and ensure that tech partners are offering real insight and not just confusing numbers, they must commit to delivering meaningful and useful data. That may include data pertaining to placement, creative, daily, hourly and geography cuts of delivery, click-through rate, viewability and traffic quality. This alone won’t be enough to cure metric vertigo, but paired with some additional tools it might go a long way.
At the end of the day, what advertisers need is validation that their media is working for them, not just reams of complex and nuanced information. In today’s day and age, data is critical to make informed and impactful decisions, but only if it is used properly.
Technological progress in the highly complex digital media advertising environment will always uncover more ways in which the quality of an ad exposure can be assessed, but we must always be mindful of how we determine whether the exposure impacted a brand’s overarching objective of awareness, purchase intent or revenue.
By constantly developing new and better ways to assess ad effectiveness, the industry can cure its vertigo and reconcile it with the old advertising traditions, creating something that is both heavily driven by data and, at the same time, pure magic.
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