Ask a customer why they chose you and you’ll usually get a perfectly reasonable answer – considered, well articulated and entirely plausible. The trouble is that it’s often only part of the story. People are notoriously poor witnesses to their own decisions, especially a few months after the fact. They remember the rational reasons they gave the CFO and forget the moment of doubt, the colleague who pushed for you in a meeting, or the competitor who took three days to call back. So what a customer tells you and what actually happened end up as two quite different accounts of the same decision.

We call this the say–do gap, and our latest research suggests a lot of tech companies are operating inside it without realising.

Confident, but…

We commissioned Lightspeed Research (Kantar) to survey 163 B2B technology decision-makers across marketing, sales and product in Australia, the UK and the US, and asked them how well they understand their customers.

On the face of it, confidence is high, with 86% saying they understand what their customers value. Yet when we asked about behaviour, 59% admitted they know what customers do but not why they do it. I find that combination fascinating, because it means most leaders are sure about what customers value while being unable to explain many of the choices those same customers make. In my experience that’s mostly because teams have never had a practical way of putting the two side by side.

The say–do gap

Confident about customers. Unsure why they act.

We understand what customers value and why

86%

We predict customer needs before they happen

84%

We know what customers do, but not why

59%

We can’t articulate a data-backed difference

50%

ConfidenceStruggle% who agree

Survey of 163 B2B tech leaders, AU/UK/US
Lightspeed Research (Kantar)

Two records of one decision

Most of the customer understanding I come across in tech is built on two kinds of evidence. There’s what customers say, which comes from surveys, NPS comments, feedback forms and whatever a rep types into the CRM after a call. Then there’s what customers do, which lives in usage data, pipeline stages, renewal rates and the click trail.

Both are useful, yet neither explains the other on its own. A survey might tell you a customer values ‘ease of integration’, while the data tells you they churned after eight months. What neither will tell you is that the integration really was easy, but the second team who had to use the product was never trained and went back to the old tool. That explanation sits in the space between the two records, and you’ll only find it by looking at them together.

What it costs you

When you act on what customers say and little else, a few things tend to follow. Your messaging gradually drifts towards the generic, because customers describe their choices in category language – ‘reliable’, ‘scalable’, ‘great support’ – and that language finds its way into your positioning (along with everyone else’s). Product and marketing can end up chasing the wrong priorities, since the feature customers ask for most isn’t always the one that changes what they do. And losses get misread. If the stated reason is price you’ll probably discount, which is fine if price really was the problem and an expensive mistake if the real reason was risk.

A quick health check

If you want to gauge how wide your own gap might be, try answering three questions honestly. When did you last hear a customer explain a decision in their own words, more than a month after they made it? Can you name one thing customers say they value that their behaviour contradicts? And do your loss reasons come from the buyer, or from the seller’s notes? If any of those made you pause, the gap is probably wider than it looks.

Closing the gap

More surveys won’t close it, because they only add to the ‘say’ side of the ledger. What does work is a series of structured conversations with recent customers and lost deals, mapped against what those same people actually did – what they evaluated, where they stalled, who joined the decision late and what they did after signing.

That’s the work we do at Meta Strategy, and it’s what our reasoning engine, TesseraIQ, was built for. It connects what customers say to what they do so the reasons behind the behaviour become visible, and teams usually have the findings within a week of the interviews.

About the research: an online survey of 163 decision-makers in marketing, sales and product at B2B technology companies with annual revenue of $20m or more, in Australia, the UK and the US. Fieldwork by Lightspeed Research (Kantar).