Editor’s note: Kevin Gray is president of Cannon Gray, a marketing science and analytics consultancy. Koen Pauwels is distinguished professor of marketing at Northeastern University.

Marketing researchers can now access more data (and a greater variety of data) and do so faster than ever. Advances in statistics and machine learning enable us to discover important insights in data never before possible. We can now answer questions that not long ago we might not have thought of. Qualitative research has also benefitted from recent developments in information and communications technology.

But when it comes to obtaining useful research results, technology isn’t everything. What if we’re answering the wrong questions? Let’s look at a few examples of what we mean.

Q: Our KPIs have been improving but sales have been flat. Is there something wrong with our tracking survey?

A: Why do you believe these KPIs are related to sales? Do you have empirical evidence that they are?

Q: Our social media tracker tells us overall sentiment is down, especially among young men. Panic!

A: Are young men your target customers? If so, what do they say offline, which often has more impact?

Q: Our data tell us sales among young women are up, so why are total sales down?

A: How important are young women in your current and desired customer base? What drives total sales?

Even with masses of data and sophisticated analytics, much precious time and budget can be squandered if we answer the wrong questions. Humans are natural satisficers and information misers. These tendencies are reinforced in today’s complex marketing world in which managers feel pressured to make many decisions very quickly. 

In our busy daily lives, we tend not to be introspective or to examine our assumptions – or perhaps even recognize that we have made crucial assumptions. Furthermore, though they may have been overh...