Jo Norton.
Joanne Norton - Managing Director, Insights
There's a line that's been doing the rounds in marketing circles for years now, repeated so often nobody quite remembers where it started: we have more data than ever before, but fewer insights. We're drowning in information and starving for wisdom. It's the kind of observation marketers nod along to in a conference hall and then ignore the moment they're back at their desk, staring at a dashboard that refreshes every fifteen minutes.
That contradiction is worth sitting with, because it points to one of the most expensive mistakes in modern marketing: the quiet assumption that data and insight are the same thing, just at different stages of polish. They are not. And the gap between them is where most marketing budgets go to die.
The Confusion Is the Point
Data tells you what happened. A click rate. A bounce rate. A basket abandonment spike on Tuesdays. Insight tells you why it happened, and more usefully, what to do about it. The first is a fact. The second is an explanation with a direction attached to it.
The reason this distinction keeps getting blurred isn't stupidity, it's incentive. Dashboards are easy to build, easy to defend in a budget meeting and easy to point to as evidence that something rigorous is happening. They produce the comforting illusion of knowledge without the harder, slower work of actually understanding the customer. A bar chart feels like proof. It rarely is.
So, marketing teams keep commissioning more dashboards, more basic trackers, more real-time reporting layers, while the actual strategic questions, the ones about why a segment is drifting, why a positioning isn't landing, why loyalty is eroding among a specific cohort, sit unanswered. Not because nobody is looking at numbers. Because nobody has asked the numbers the right question.
Insight Doesn't Live in a Spreadsheet
The uncomfortable truth is that insight is not a more advanced form of data. It's of a different category entirely. Data is observational; it records what occurred. Insight is interpretive; it requires a human mind asking why, testing assumptions and synthesising something that wasn't visible in the raw numbers at all. You cannot automate your way to it by adding another column to a report.
This is precisely why so much "data-driven" marketing produces decisions that are technically justified and strategically hollow. The data was real. The conclusion drawn from it wasn't insight, it was a guess with a chart attached. Marketers have become extremely good at measuring outcomes and noticeably worse at understanding causes, largely because measurement infrastructure has scaled far faster than the discipline of asking focused, sharp, structured questions of consumers themselves.
Why Existing Data Can't Answer the Question You Actually Have
Here's the part marketers tend to avoid admitting: the data you already have was built to answer yesterday's question, not today's. Your CRM, your analytics platform, your social listening tool, all of it was structured around whatever decisions someone needed to make months or years ago. It is, by design, retrospective and generic. It tells you about your consumers in aggregate, not about the specific, narrow, often strange question currently sitting on your desk: should we reposition this product for a new audience, will this messaging land with people who've never heard of us, why did loyalty disappear in this one region and nowhere else.
Off-the-shelf data cannot answer a bespoke question, because it wasn't designed with that question in mind. This is the case for tailor-made research, not as a nice-to-have, but as the only mechanism actually built to answer the specific thing a marketer needs to know right now. A custom study, properly designed, starts with your question and works backward to the right method and the right sample. Existing data starts with whatever was already being tracked and hopes your question fits inside it. Most of the time, it doesn't.
The Case for Asking Better Questions, On Purpose
None of this is an argument against data. It's an argument against mistaking its abundance for understanding. The marketers who will pull ahead over the next few years won't be the ones with the most dashboards. They'll be the ones disciplined enough to recognise when a dashboard has nothing left to tell them and curious enough to go and design a study that actually interrogates the question they're sitting with.
That means treating research as a strategic instrument, not a quarterly compliance exercise. It means being willing to ask focused, well-designed questions of real consumers, rather than mining a large dataset for a pattern that happens to confirm what you already believed. Understanding doesn't arrive through volume. It arrives through asking the right question of the right people, on purpose and being willing to sit with an uncomfortable answer.
The flood of information was supposed to make marketers smarter. Instead, for many, it's done the opposite, replacing judgment with reporting and curiosity with automation. The way out isn't more data. It's the much harder, much rarer discipline of going and finding out, deliberately, what the data was never going to tell you.