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Big Data’s Big Moment

Big data. It’s the big marketing buzzword of the moment. Using tools unimaginable even five years ago, companies are now able to collect an onslaught of data on their current and prospective customers. Just think: As you research your next gadget on the internet, enter your phone number at the grocery store, or respond to that coupon mailing you received, you are sending little data points to companies all around the world.

How does all that data become information, and what story is it telling? That’s the crux of the conversation we’re having in the market research community.

At a recent industry conference, I heard from a number of brands about how they are using data-driven customer insights to improve marketing and product development.

A representative from LinkedIn, the world’s fastest growing social networking platform, emphasized that data by itself might not mean what you think it means. Their team combined digital behavior quantitative data with qualitative insights from customer panels to determine that one of their most-clicked-on features was, in fact, unpopular, leading to a change that improved customer satisfaction.

Work clothing manufacturer Wolverine and tool manufacturer DeWALT used customer insights to change their product lines, even soliciting customer design suggestions for new and existing products. The information they collected led to a much more rapid product development process, increased sales, and a more positive brand reputation for each.

At CLM, we collect data for our clients using a balance of qualitative and quantitative methods. Qualitative data contextualizes the quantitative data, and leads to more accurate and actionable insights that can be prioritized and implemented.

Data is king in today’s fast-paced, highly relevant environment, but there’s no easy or fast way to do it right. Regardless of your political beliefs, this past election cycle was a perfect illustration of the complexities that come with interpreting incoming information in the chaos of the real world. The wildly-off polling predictions proved that not all data collection, even “tried-and-true” methods, will lead you to an accurate conclusion. It takes careful consideration and strategy to determine what the data means and how to respond.

The more we understand what story big data is telling, the more accurate our insights will be.

Becki Woodbury | Jan 24, 2017