3 Questions for Marketers Applying Big Data

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There are a lot of misconceptions about Big Data, but one of the most frustrating is the pervasive belief that Big Data is for Big Business only. The feeling isn’t restricted to Ma and Pop shops, either. In our day-to-day conversations, we frequently hear CMOs and marketing managers at established, mid-sized brands express uncertainty about Big Data’s applications for their business. Perceptions — some true, some not — about cost and complexity typically fuel this attitude. And it doesn’t help that the media buzz is largely focused on major big data companies like IBM, Oracle and HP.

There are elements of truth here: Big Data can be complex and applying it to marketing decision-making can be expensive. But the idea that Big Data is for Big Business alone is just plain wrong. Big Data can have tremendously useful applications for businesses of all sizes, but before taking the plunge marketers must ask the right questions. Here are 3 questions for small to mid-size brand marketers to consider when approaching Big Data:

1)      What is the objective?

Hopefully this one doesn’t come as a surprise, because gathering, analyzing and applying data can be costly and time-intensive. Leveraging Big Data is a lot like life: Anything is possible, everything is not. Know where you’re going before deciding how to get there.

2)      What data is available?

A lot of marketers seem to think that they need to subscribe to “premium” database or analytics products (e.g. IBM’s DB2 or Microsoft’s HDInsight) in order to leverage Big Data. Two issues here: 1) see #1 above – these products may make sense, but only if they complement your objective; and 2) before making a significant investment in new data services, inventory what information is already available. Most brands don’t even come close to fully leveraging existing data from their CRM and other sources. Start there.

3)      How will measure efficiency?

Most brands turn to Big Data hoping to identify insights to increase ROI. Yet many fail to actually measure the efficiency of their Big Data initiatives themselves. Data collection and analysis can be a rabbit hole, but it doesn’t need to be. In addition to addressing #1 and #2 above, tracking time and resources spent on Big Data — as well as bottom-line business outcomes — will help keep you out of the weeds (and hopefully out of the red).

Big Data isn’t a thing, it’s an idea — one for businesses of all sizes.

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