Editor’s note: Seth Redmore is CMO of computer software firm Lexalytics, Boston.
I keep hearing that data is king. And it’s true. But too often when we think of data, we only think of one kind: quantitative data. The hard numbers you get from analytics, A/B testing or multiple-choice surveys.
Qualitative data is the kind of data you get when you undertake interviews or pose open-ended questions. It’s the data that comes from social discussions, forums, blog posts and even the news. It helps provide context and background, and uncovers the motivations behind why people do what they do.
If you think about knowledge as an iceberg, quantitative data defines and describes the part above the water. But how do we get to and understand the hidden mass lying beneath? Qualitative research.
Essentially, quantitative approaches address the what while qualitative approaches help unearth the why.
Quant of quant is not enough
From a business perspective, it seems to make sense to throw your money at quantitative approaches. Unsurprisingly, most companies are on board with quant – but the ROI isn’t necessarily what you’d expect. Unless you’re Google, quant of quant is not enough.
Huge players like Google have access to enough data to draw trends and apply meaningful statistical analysis that can be used to inform its business approaches. Google might be looking at the tip of the iceberg, but it is big enough to apply enough pressure to the top to move the whole thing.
Most companies aren’t Google, however. The average company isn’t getting billions of clicks a month so it can’t test every possible combination of its marketing and product mix. You’re going to need to augment your quantitative research with a qualitative approach. One reason is that you can’t crunch data you don’t have. Another is that when you have a limited number of “whats” to work with, the “whys” become even more critical.
Qualitative data helps you capture and understand the motivations of your audience so you can anticipate their next steps and respond accordingly. You can plan ahead based on your knowledge of the world around you and how your business and audience fit into it. Quantitative data, on the other hand, looks at the past. It tells you what the steps were, but relies on you to try to determine the why.
The people behind your data
Imagine you run a cable company. You’ve developed quantitative models that predict when customers are likely to switch providers or cut their service. You’ve also figured out when it’s cost-effective to woo a customer back and when it’s best to let them go.
You’re looking at your 2004 data for Springhill, Tenn., and you’re seeing huge amounts of churn. Your models are telling you that this is simply a high-turnover area, and that perhaps it’s better to take your marketing efforts elsewhere.
But you wonder if there’s something else at play, and so you take some time to dig through the local newspapers. It turns out that this churn is the result of the closure of the Saturn automotive plant, the city’s major employer. Tens of thousands of people lost their jobs and needed to cut non-essentials from their budgets.
Now you have an understanding of both the situation and your customers’ motivations. With this context, you can conduct further research and approach the situation differently – you might find ways to keep your customers while building goodwill and showing support and understanding.
Value from social content
Mining for context and consumer motivation is invaluable for smaller companies wanting to get the best leverage from a limited research budget. So much of this information is readily available online – you can go as macro as world news to as granular as an individual tweet.
Qualitative data, particularly the massive stream of social content, can provide value not just from content that mentions your brands, but from conversations that mention your competitors and even conversations that discuss issues relevant to your products. If you don’t have a gluten-free pizza, you can’t measure how many of them you aren’t selling. But, you can see how popular that concept is becoming in your area by conducting a solid qualitative research study using social channels.
If you’re a bigger player, you can narrow your analysis to mentions of your products. If you’re smaller, you can broaden your search to see what people are saying about others and use that to your advantage.
When you have a corpus of consumers’ discussions about your product space, it’s much easier to understand their motivations and their subsequent decisions. You also have an opportunity to react before that decision is made, thus influencing the outcome.
In contrast, if you rely exclusively on quantitative data you’ll have to wait for enough prospects to bounce from your site or abandon their shopping carts before you can start drawing on trends.
We’re all savvy enough by now to know that correlation doesn’t equal causation. If you want to find that cause, turn your attention to qualitative analysis and start mining the motivation behind the behavior.