The duality of data: What qualitative data can do that Big Data cannot
Originally published on LinkedIn · August 09, 2017
I recently ran across a great read in Financial Express that outlines an important complementary approach to Big Data-driven consumer insights, one that juxtaposes Big Data (quantitative) against Thick Data (qualitative) to deliver deeper insights. Once you make it past the jargon, the article is enlightening, brief and, best of all, true.
Big Data in marketing is all about capturing every interaction during the customer journey, then using machine learning algorithms to process and analyze the data to produce a greater understanding of consumer behavior. But, as the aforementioned article points out, there’s a gap in there.
As it stands today, Big Data-powered, machine learning-driven consumer insights are good for producing quantitative driven insights. Even emotions and sentiments can be captured, quantified and fed back into the equation. But Big Data can’t capture everything.
Consider a consumer goods company trying to get their packaging just right. They’re hearing that customers are frustrated with the current situation, but no matter how much Big Data driven number crunching they do, they can’t find the solution. That’s because Big Data isn’t enough. The company needs to take a closer look at how customers interact with their product – how they handle it, unpack it and react to it. And they have to observe a large sample of customers. Next, they need to apply some distinctly human intelligence to interpret the customer experience and monitor their emotions throughout. Big Data can’t do that.
There are millions of situations where quantitative insights need to be paired with qualitative data to really be useful.
What kind of store layout will make customers feel welcome?
What unexpected ways are customers using your product?
What’s the demand for a new product in a completely different category?
Even in a completely digital world, you can’t ignore qualitative data. How can you get new customers to try out your digital product when offline alternatives are available? That was the challenge Netflix faced when they separated the DVD rental business from the streaming business, effectively doubling monthly fees. These days, it feels like a no-brainer. But Netflix was initially panned for that decision! If you’re a company like Groupon that creates a category defining product, how can you encourage skeptical consumers to try it out? Those non-Groupon members aren’t providing quantitative information as non-users. In cases like these, your only option is to go to the field, run focus groups, parse qualitative data and fine tune your strategy.
The bottom line is this: the best insights come from a combination of quantitative and qualitative research. They complement each other. And if you want a fuller picture for further fine tuning, you’ll have to keep them both in mind.
What are the various techniques you have adopted for capturing qualitative data?
Thank you for reading the post.
About Author: Suresh Chaganti, Co-Founder & Strategy advisor at VectorScient. Suresh specializes in Big Data and applying it to solve real world business problems. He brings in 2 decades of experience in architecting B2B and B2C applications across a variety of Industry verticals. Connect with suresh on linkedin
