Think IT's Approach To Big Data Will Solve For Marketing Accountability? Think Again

Let’s take a look at how IT tends to approach Big Data, including marketing data. First, IT tackles problems from the bottom up. IT’s plan seems to be: Gather up a big pile of whatever data we can most easily get our hands on, wait for someone to ask a question, then query the database. Business intelligence is essentially an after-the-fact exploration of data.

Second, IT typically pulls in the data that’s easy to pull in, rather than pulling in what matters. There’s an old joke about a guy who loses his keys at night and is searching for them under a lamppost. “Didn’t you drop them over there in the dark?” says a bystander. “Yes, but the light is better over here.” That’s not far off from IT pulling in only the easiest data. It’s true that some of the data that matters most is easy to get (Salesforce data via an API, for instance), but most of it is hard to get. Think of all the agency data that comes to you in PDF format. All the PR data. All the data and planning docs in PowerPoint and Excel that hold the keys to marketing performance calibration. That data isn’t easy to access, so it’s probably not coming to IT’s data warehouse any time soon.



And third, IT continues to recommend lengthy data infrastructure projects. When IT presents its plans, the conclusion is usually something like: “And then in 2017 we roll out reporting ….” Translation: We need to do years of infrastructure work, and after that you might be able to see something.

For all of the above reasons, marketers who want to understand the business impact of their marketing can’t just leave everything to IT or the Analytics department and say, “See what you can find in there.” Are analysts going to serendipitously sift out key insights for optimizing your marketing? Not likely.

The marketers who benefit most from Big Data will be the ones who take control and become the storytellers of their own success. And that begins with being intentional and having thoughtful, important questions in mind -- questions that data, teams and tools can help you answer. 

What are the questions that matter? That depends on your business, of course. Start a list, and when you or anyone asks a question about your marketing (the stumpers are the best), capture it -- everything you wish you had answers to. Then as the data rolls in, instead of asking IT “what can you find in there?” you can ask for specific answers to important questions.

“How’s it going with the XYZ campaign -- is it driving net new relationships?” That’s one question. “When we run offline and online campaigns in conjunction, are they more effective than when we only do one or the other?” That’s another question. “How's the buzz tracking around this store opening versus the last store opening we had? How about versus the best store opening we’ve ever had?” Great questions. “Which of our agencies drives the most net new leads per $10,000 we pay them in fees?” Another great question. Someone should know the answer to these questions!

Note that everyone on the marketing team has responsibility for capturing questions. The CMO may need answers to big questions, like which marketing efforts are moving the needle on the business objectives and how much is being spent against each one. An email marketing manager orchestrating a loyalty drip campaign, sending out a series of emails over the holidays, might be asking, “Which content types -- humorous, promotional or educational -- are leading to the highest click-through rates?”

Big Data may promise a new era of data-driven, ultra-effective marketing, but amazing, transformative answers won’t just come floating down the data stream for us to scoop up. After all, it’s called Big Data -- not Big Insight. We as marketers have to decide ahead of time what is most important to be looking for. If we don’t, we'll just grind to a halt, drowning in data overload.

1 comment about "Think IT's Approach To Big Data Will Solve For Marketing Accountability? Think Again".
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  1. Melinda Venable from Social Scouters, November 18, 2013 at 5:41 p.m.

    These are great example questions, Jennifer. Helps spark the possibilities! Thanks for the post.

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