HOW TO EMBRACE—INSTEAD OF FIGHT—BIG DATA

Sales numbers. Focus group results. Consumer surveys.

These old-fashioned business metrics used to constitute most of what we thought of as “data.” If a brand wanted to put a campaign in the market, a radio spot for example, they would use consumer surveys to understand the audience, and then they would test the creative in front of focus groups; and once the campaign was in market, the resulting sales numbers were the final arbiter of whether it was all a failure or success.

Today, brands and marketers have access to so much more data. There is an endless menu of software platforms, data sets and points, and integrations. Marketers can study dynamic cultural and behavioral patterns, psychographic patterns, and incredibly detailed purchase journeys, and they can study them all in real time. Brands and marketers no longer search for consumer look-alikes—they use data to identify psych-alikes in smaller and smaller clusters, niches, communities, and neighborhoods.

The ability to integrate and connect data sources has changed the way everyone does business. But all that data can be paralyzing for brands that don’t know how to effectively utilize it. And for smaller brands that can’t afford to employ a small army of analysts and strategists, data can often seem like yet another tool for category leaders to stay ahead of the chasing pack.

We help our clients understand why a tactical, reactive, and “business as usual” approach to marketing just won’t cut in the era of big data. We also help our clients understand why finding ways to make data work for them, as opposed to against them, is essential for every brand, of every size.

Big data has transformed how marketers and brands do business, and mostly for the better. Brands can now target consumers with more accuracy and efficiency, which means they can deliver content and products consumers actually care about. But big data has also changed how brands do business in ways that are more disruptive, and in ways that make it harder for many marketers to do their jobs.

1). DATA CAN JUMBLE INTERNAL DECISION-MAKING

Data has started a battle for supremacy inside many brands and agencies. This paragraph from the Wall Street Journal sums up the new reality: “Ad agencies’ increasing reliance on data is inverting the traditional creative model, where the teams dreaming up ad campaigns use their gut instincts to tap into the zeitgeist. Now, thanks to a preponderance of highly specific information about consumers collected from sources such as social media, surveys and search engines, more agencies are making creative choices based on what the data dictate.”

This same model also applies to internal teams at most brands. This new way of working sounds great, until you try executing it. Who controls the marketing? The account or management team? The strategists? The creatives? The IT or development team? And when in the workflow does data get introduced? The beginning? At the end? Who decides?

The answer tends to come down to how much an organization believes in data. That same Wall Street Journal article cited the example of Mark Fitzloff, founder of Opinionated, a creative agency in Portland, Oregon. Fitzloff, according to the article, “ignores the insights gleaned from data all the time because he believes an overreliance on consumer information has taken spontaneity and surprise out of the creative process, leading to a sense of homogeneity in advertising.”

Fitzloff may have a point, but most marketers and brands simply cannot afford to be so cavalier about data, not when ROIs and marketing dollars are scrutinized more closely than ever.

For an organization to effectively utilize all the data at its disposal, there must be clear internal consensus about the role data plays in decision-making processes. Otherwise, more data just means more chaos and dysfunction, the things data was supposed to get rid of in the first place.

2). IT’S HARD TO KNOW WHAT DATA REALLY MATTERS

“Half the money I spend on advertising is wasted; the trouble is, I don’t know which half.” This old adage has been replaced by a new, data-driven adage: “Half the money I spend on data is wasted; the trouble is, I don’t know which half.”

So what data streams should brands and marketers invest in? Which data points matter?

One approach is to identify KPIs (key performance indicators) and then work backward. For example, if web traffic is a KPI for a brand, then that brand should invest in data that accurately tracks web traffic. The same goes for click-through rate (CTR), cost per lead (CPL), or social media impressions. There are data sources that offer clear metrics for these KPIs, so if a brand invests in data that tracks something other than a KPI, that investment probably warrants scrutiny.

Working backward from KPIs isn’t the only way to approach data, but it does follow the general rule of thumb for figuring out what data really matters: it has to be attributable and measurable. If data is attributable and measurable, brands and marketers can, in real time, use it to balance their bottom-line calculations.

3). DATA, AND DATA SOURCES, ARE CONSTANTLY EVOLVING

Let’s say a brand figures out how to effectively integrate data into their organization. And let’s say they have also identified the data points that really help them balance their bottom line. Sounds like they have this whole data thing figured out, right?

But what happens when Google adjusts their RankBrain, Panda, Hummingbird, or other algorithms, and suddenly your website’s search engine results page (SERP) ranking goes from two to 15 in one day, which has a huge effect on your bottom line, since now only 200 users come to your website organically instead of 5,000?

Innovations like Google’s search algorithms and Facebook’s Newsfeed algorithm have made the jobs of brands and marketers much harder, because we have to continually educate ourselves on how to create branded content that is both optimized for algorithms and relevant and engaging for the consumer.

However, these innovations have also made our jobs easier. Now we can tap into different data sets more granularly, which means we can create automated activation based on customer journeys and intent and browser paths. It’s also easier to segment audiences and identify high-value and high-performance audience segments.

To get the most out of data, your team needs to have the capacity to keep up with all the latest innovations, and so many brands are slow to adapt. When your team is slow to adapt, your bottom line is impacted.