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Data Fog Blinds Marketers

“Companies are caught in a data fog, and they’ll probably stay there for a few years.” This is a bleak outlook from Jeff Tanner, professor of marketing at Baylor University’s Hankamer School of Business. Although the InformationWeek piece (below) focuses on retailers and consumer packaged goods companies, I can’t disagree with his insights into how marketers are struggling to analyze their customer data and glean useful information.

B2B marketers have the daunting task of proving their impact on revenue, and fortunately there are a number of tools at our disposal to better understand – and more specifically – target customers to engage them in a meaningful way. The more insights we have into targeting the right buyers, the better chance we have at converting potential customers into active customers. However, there’s a great deal of uncertainty if we’re measuring the right criteria, if our reporting can accurately track marketing effectiveness, if the tediousness of lead nurturing is actually paying off.

It seems that many B2B marketers feel like they are drowning in data, and lack the tools to properly nurture leads through the purchase process. I was intrigued by Tanner’s idea that the challenges companies face in analyzing data will lead to a period of “information brokering.” This concept of companies outsourcing their data to others to analyze, doesn’t sound farfetched to me at all. I’d be grateful for a professional service that understood how to analyze our customer data and could help prove when and how my team’s marketing efforts turned a prospect into a customer.

Could this service become a reality? I’d like to think that more effective tools for lead nurture are coming this year. In the meantime, I’m going to pretend I’m not stuck in the “murkiness” of data.

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Data Fog Blinds Marketers

Companies spend too much time simply getting data into a form where it can be analyzed, professor says. That doesn’t leave enough time for business problems.

Companies are caught in a data fog, and they’ll probably stay there for a few years, said Jeff Tanner, professor of marketing at Baylor University’s Hankamer School of Business.

Tanner was involved in helping to value a recent sale of customer transaction data, something he said has grown more common as new sources of data, like social media, emerge. Companies want data they can use to create more complete pictures of individual customers to tailor their marketing.

By and large, though, he said that companies are still struggling to get data into a form where they can analyze it. A study he did of retailers and consumer packaged goods companies found that companies spend 70% to 90% of their time getting data into a form where it can be analyzed. That means as little as 10% of that time is spent on actually using the data to help the business.

This study tells us companies by and large aren’t able to see what’s in their data. For privacy advocates, the good news is that we’re nowhere near a time when this pizza-ordering nightmare will come true. Of course, companies can already piece together enough information to raise privacy hackles. But as Tanner told InformationWeek, privacy is a bifurcated thing — some people care a lot, some people don’t. Companies will have to learn how to craft messages that don’t inadvertently trigger outrage, as Target did when it turned out it had accidentally outed a pregnant teen, raising concerns.

“The mistake they made was in announcing her as pregnant when she wasn’t ready,” Tanner said. He said Target has reformulated the way it makes such offers, blending items a pregnant woman might want with other products and not directly making references to being pregnant.

Most companies still struggle to get such useful information out of their data. Tanner says the challenges companies face in analyzing data will lead to a period of what he calls “information brokering,” where companies outsource their data to others to analyze. Data sales will become less common in the short term. “We’re running up into analysis and storage and preparation capacity limits,” Tanner said.

So what is data worth? The answer boils down to how close it gets you to a valuable transaction.

Note that it doesn’t mean how close it gets you to a customer. Location data by itself isn’t valuable. “What I keep hearing over and over from vendors is that you’ll be able to give discounts to buyers, and blahblahblahblah. If I know your regular stop is 3rd and Broad, and there’s a Starbucks there, and I push you a note saying ‘here’s $1 off a latte,’ that’s just mindless discounting.”

Tanner says what companies need to do is glean better information from their data. In his Starbucks scenario, the company would want to know if the driver at 3rd and Broad ever actually goes into a Starbucks, and if so, what does she buy, and when? For himself, he notes that sometimes his local 7-11 is out of his favorite apple fritter when he stops in. The company loses a sale and Tanner doesn’t get what he wants. Ideally, the 7-11 should be able to use data about when things sell and when they don’t to create a more efficient supply chain.

For now, his fritter is lost in what he calls “a lot of murkiness” in the data.

Original post on InformationWeek on January 13, 2014. Michael Fitzgerald writes about the power of ideas and the people who bring them to bear on business, technology, and culture.