Home Data-Driven Thinking Paralysis By Analysis: Is Too Much Data A Bad Thing?

Paralysis By Analysis: Is Too Much Data A Bad Thing?

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anthony-katsur-ddt“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 Anthony Katsur, CEO of Maxifier.

Want to target your online ad to men living in Wisconsin who like to read about politics, are researching a vacation in Hawaii, have an interest in motorcycles, and listen to classical music? Now you can! Fantastic, right?

This is hyperbole, of course, but it illustrates how the advent of digital has heralded hyperfocused targeting, segmentation, placement, and performance to the degree that niche audiences can be defined and targeted with tactical precision. Data-management platforms enable marketers to collect a wealth of behavioral information, such as sites or pages visited, searches made, content viewed, frequency of consuming specific types of content, and time spent on certain actions, and combine it with third-party data sources to provide a data-rich audience segment.

But is all this data actually improving advertising? Are we driving the key metrics that are important to the marketer? Are we improving efficacy, or are we just finding efficiencies in reaching a cookie pool? Our focus on data has attracted and supported direct response more than any other channel, but is it also limiting us from unlocking brands?

I think our obsession with data may, in some ways, be limiting our growth instead of boosting it. As an industry, we’re drowning in a sea of data because we believe that more is better. But, too often, it feels as though we’re throwing data at our clients simply to see what will stick. Instead, we should simplify our targeting and audience segmentation and support data with relevant attributions and metrics.

If we look at the offline data giants such as Experian and Acxiom, we can see that these companies have achieved success by sticking to the guiding principle that “less can be more.” In spite of their huge volumes of data and many years of experience developing accurate and relevant segmentation, they offer only a small number of audience segments. Experian’s Mosaic USA, for example, breaks the population into 71 segments, which fit into 19 broader groups. While it could create many more segments, it recognizes that giving marketers more to choose from wouldn’t win it more business. On the contrary, choice can be demotivating. Just think of large versus small restaurant menus, for example. More choice means more confusion and more procrastination, whereas fewer choices — as long as they’re good ones — can make finding the right fit easy and quick.

Great content and context can often be more than enough, and I would argue that this combination is vastly undervalued and overlooked. All too often, online, the cookie has become the sole arbiter of audience qualification, unlike in TV, where content is still just as important and effective as an audience proxy. There’s a reason male-oriented advertising appears during sports games and female-targeted advertising runs during “The Bachelorette.”

Online Lessons From The Offline World

We can learn lessons from the offline world about how online targeting should evolve and be packaged into simple, yet scalable, audience segments. Marketers want to target segments that are selectable and scalable while ensuring their desired audiences can be reached across all campaign mediums. If we can address these needs to help drive online targeting, perhaps we can make the Web a more relevant environment for brands, further encouraging more digital advertising.

There’s no easy path, but I would argue that the amount of data currently employed almost feels like data for data’s sake. While traditional channels often don’t come close to the volume and recency of digital data, online remains the bastion of the direct-response advertiser while brands continue to invest in traditional channels to achieve their goals. Digital offers great starting data points which should resonate with brands, but this is only part of the story. How, for example, do reach, frequency, and viewability translate into the brand awareness and favorability metrics that brands want to measure online? We have the building blocks, but we need to craft the data and metrics to create a compelling value proposition that advertisers want to buy into.

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Don’t get me wrong, I’m not saying all this data is a bad thing. After all, no other marketing channel is as measurable as digital. But there needs to be a balanced approach to its use. In an attempt to quantify every element of the digital-media transaction, we get caught up in the data (take a shot every time you hear “big data” thrown around our industry!), while often ignoring the fundamentals of marketing.

Some of the hesitancy around embracing digital is probably a cultural or comfort issue. The old adage “no one ever got fired for buying IBM” applies; similarly, no one is likely to get fired for buying advertising on “Mad Men.” Traditional channels are not only safe, but they’re packaged with supporting data and relevant metrics that make it easier for brands to work with them. We’re still in the early days of our digital culture, but we need to realize that jargon, complexity, and vast amounts of data can alienate the very brands we want to attract. We need, instead, to take steps to bring information together in a way that is simple, scalable, and translates into the vernacular of the marketer.

The a la carte menu of data we’re providing — without solid correlation to the success metrics of brand marketers — is type-casting our entire ecosystem. Our obsession with data, while one of our greatest strengths, is also our Achilles’ heel.

Follow Anthony Katsur (@sleepwhendead) and AdExchanger (@adexchanger) on Twitter.

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