Research

How to merge Big Data with Small Data for deeper customer insight

How to merge Big Data with Small Data for deeper customer insight

If you want to truly understand your customers, you can’t rely on just one type of data. That’s one of the main takeaways from brand strategist Martin Lindstrom when he spoke at the recent Vision Critical webinar How Companies Can Discover Real Value in Small Data. Andrew Reid, Vision Critical founder and president of corporate innovation, joined Lindstrom in the webinar. As many marketers are aware, Lindstrom is the author of the new book, Small Data: The Tiny Clues That Uncover Huge Trends.

The one-hour webinar explored how marketers can get more from Big Data by using what Lindstrom refers to as Small Data: the seemingly insignificant information found in the daily lives of customers. According to Lindstrom, Small Data is the real key to finding insight into who your customers are—into true human behaviors.

So, how can marketers get more out of Small Data? The webinar offered some important and practical tips.

  1. Don’t just collect data.

Marketers today heavily rely on data provided by marketing technology to understand their customers. According to Reid, that over-reliance on Big Data can be dangerous. Many tools in the marketing stack “are simply collecting data,” further adding to the complexities of truly understanding the customer.

Big Data poses three main challenges. First, there’s the issue of finding the strongest signal—the right signal—in all the noise that emerges from Big Data. Secondly, quantitative data doesn’t reveal the why of customer behavior.

The third issue is what Reid refers to as “the creepy factor.” Often, companies use Big Data to spam their customers with more emails and surveys. “Spamming your customers doesn’t help you,” Reid points out.

The solution isn’t to collect more data. Instead, companies need to redefine their relationship with customers and recognize them as real people, not just data points.

  1. Find causations, not just correlations.

There’s a tendency for marketers to interpret the information they get from Big Data as causations. That’s a huge mistake, according to Lindstrom. While Big Data is useful for finding correlations, Small Data identifies something more important: causations.

Lindstrom’s advice is to use Small Data to come up with hypotheses about customer behavior and then to validate those with more research. (He proposes a thorough process of doing this in his new book.)

“If we want to build brands, it’s all about finding that needle in the haystack,” he said. “It’s all about identifying, first of all, the causation, leading to the correlation [which then leads to] the conclusion.”

  1.  Connect with people on a human level.

Perhaps the most important takeaway from both Lindstrom and Reid is the importance of connecting with customers on a one-on-one basis. The stories that Lindstrom shared during the webinar all involved companies engaging directly with their customers—either through ethnographic studies or by engaging with them on a one-to-one basis—and gaining insight as a result. Small Data is most effectively derived from direct engagement with customers.

Data is not a substitute for customer engagement. It’s also not the same as insight. Adds Lindstrom, “Insight is an articulation of a situation. Small Data is just the step before insight.”

Ultimately, companies need to use both Small Data and Big Data. It’s not either-or; to succeed, companies need to master the fine art of combining both. More importantly, companies need to infuse the voice of the customer in the process to validate what both sets of data are saying with real people.

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