Audience Insights Are Not the Problem. Acting on Them Is.

Audience insights tell you who your customers are, what they care about, and why they buy. Most marketing teams have more of this data than they know what to do with. The problem is rarely a shortage of insight. It is the gap between what the data says and what the business actually does with it.

That gap is where growth stalls. And it is more common, and more costly, than most senior marketers want to admit.

Why Most Audience Insight Work Produces Decks, Not Decisions

I have sat in a lot of audience insight presentations over the years. The research is usually solid. The synthesis is often impressive. And then the deck gets shared, everyone nods, and three months later the campaign brief looks almost identical to the one before it.

This is not a research problem. It is a translation problem. Somewhere between the insight and the brief, the commercial implication gets lost. Teams default to what they know how to build, rather than what the audience actually needs from them.

Part of the issue is structural. Audience research is often commissioned by strategy or planning, but the people who act on it sit in channel teams, creative, or media. By the time the insight reaches the people making execution decisions, it has been filtered through three layers of briefing and lost most of its specificity. What starts as “this segment responds to social proof from peers, not from authority figures” becomes “use testimonials.” That is not the same thing.

The other part of the issue is that insight work is often treated as a project rather than a practice. You do the research, you present the findings, you move on. But audiences are not static. The person who bought from you eighteen months ago is not the same person today. Their priorities have shifted, their context has changed, and the competitive set around them looks different. Insight that was accurate last year may be actively misleading now.

The Difference Between Knowing Your Audience and Understanding Them

There is a version of audience insight that feels thorough but is actually quite shallow. You know the demographics. You have the persona cards. You can describe the typical customer in terms of age, income, category behaviour, and media consumption. That is useful as a starting point. It is not enough to build strategy on.

Understanding goes deeper. It is the difference between knowing that your audience is 35-to-54-year-old homeowners and knowing what keeps them up at night when they think about the category you operate in. It is the difference between knowing they use comparison sites and knowing what moment in their decision process triggers that behaviour and what they are actually looking for when they get there.

Early in my career I spent a lot of time optimising for the bottom of the funnel, chasing signals from people who were already close to buying. It felt efficient. The numbers looked good. But I was mostly capturing demand that already existed, not shaping it. The insight work that supported that approach was technically accurate but commercially incomplete. We knew who was buying. We had very little understanding of who was not buying, and why, and what it would take to change that.

That distinction matters enormously when you are trying to grow. Reaching people who are already in-market is a conversion problem. Reaching people who are not yet in-market, and moving them toward consideration, is an audience understanding problem. The two require very different insight inputs.

If you are thinking about how audience insight fits into a broader growth strategy, the Go-To-Market and Growth Strategy hub on The Marketing Juice covers the commercial frameworks that sit around this work.

Behavioural Data Tells You What Happened. It Does Not Tell You Why.

One of the most persistent misuses of audience insight is treating behavioural data as if it explains motivation. Someone clicked on an ad. Someone spent four minutes on a product page. Someone abandoned a basket at checkout. These are facts. They are not explanations.

The temptation is to infer the “why” from the “what.” And sometimes that inference is reasonable. But it is always an interpretation, not a finding. When you build strategy on top of interpretations that have never been tested against actual human beings, you are working on assumptions dressed up as data.

I have seen this play out in client work more times than I can count. A team would pull behavioural data from their analytics platform, identify a pattern, and build an entire campaign hypothesis around it. The pattern was real. The interpretation was wrong. The campaign underperformed, the team blamed the creative, and the underlying assumption was never examined.

Behavioural data is essential. But it needs to be interrogated alongside qualitative input. What do customers say when you ask them directly? What do they say in reviews, in support tickets, in conversations with your sales team? The combination of behavioural signal and declared motivation is far more useful than either on its own. Tools that help you collect and analyse user behaviour, like the feedback and heatmap capabilities covered in resources from Hotjar, are a starting point for that process, not the end of it.

The same caution applies in the other direction. What people say they do and what they actually do are often different. Declared preferences in surveys are shaped by social desirability, by the framing of the question, by what feels like the right answer in the moment. If you rely entirely on what customers tell you, you will miss the behaviour that contradicts it.

Segmentation Is Only Useful If It Changes What You Do

Segmentation is one of the most over-invested and under-used activities in marketing. Teams spend months building segment frameworks, validating them with research, naming the personas, and then running broadly the same campaign to all of them with minor copy variations.

If your segmentation does not change your channel strategy, your messaging, your offer, or your timing, it is not segmentation. It is categorisation. And categorisation does not drive growth.

Useful segmentation is built around commercial differences, not just demographic or psychographic ones. The question is not “who are these people?” It is “what does this group need from us that is different from what that group needs, and what does that mean for how we go to market?” If the answer is “not much,” you have either found a genuinely homogeneous audience or you have not cut the data in the right way.

BCG published work on go-to-market strategy in financial services that illustrated this clearly, showing how understanding the evolving financial needs of different population segments required fundamentally different approaches to product, channel, and communication, not just different creative executions. The commercial implication of the segmentation drove the strategy. That is the direction of travel. Most teams do it the other way around.

Prioritisation is the other half of this. You cannot go to market effectively against every segment simultaneously, especially if you are working with finite budget and team capacity. Insight work should help you decide where to concentrate, not just where to be present. That requires honest commercial judgement about which segments have the highest value potential and the lowest acquisition friction, and being willing to deprioritise the rest, at least for now.

The Moment That Sharpened My Thinking on This

Early in my time at Cybercom, in my first week, there was a brainstorm for Guinness. The founder had to step out for a client call and handed me the whiteboard pen. My internal response was something close to panic. I had been in the room for five days. I did not know the client, I did not know the team’s history with the brief, and I was now expected to lead the thinking.

What I noticed in that moment was how quickly I wanted to reach for assumptions. I knew Guinness as a brand. I had opinions about the audience. I was ready to run on instinct. And instinct, in that context, would have been a disaster, because my instinct was built on my own relationship with the brand, not on any real understanding of the people we were supposed to be talking to.

That experience stayed with me. The discipline of separating what you think you know about an audience from what you have actually learned about them is harder than it sounds, especially when you have been in a category for a long time. Familiarity breeds assumption. And assumption is the enemy of good insight work.

The teams I have worked with that do this best are the ones who stay genuinely curious about their audience, even when they think they know them well. Especially when they think they know them well.

Where Audience Insight Fits in the Go-To-Market Process

Audience insight is not a stage in the go-to-market process. It is an input that should run through all of them. It shapes positioning decisions, channel selection, messaging hierarchy, offer design, and measurement priorities. When it is treated as a discrete phase that happens before the “real” work starts, it gets compressed, commoditised, and in the end ignored.

The practical implication is that insight needs to be kept live. Not necessarily through continuous large-scale research programmes, which most businesses cannot sustain, but through a set of lightweight, ongoing mechanisms that keep the audience signal fresh. This might be a monthly review of customer support themes. It might be a quarterly pass through recent reviews and social listening data. It might be a standing agenda item in sales and marketing alignment meetings where frontline feedback gets surfaced and discussed.

None of that is expensive. All of it requires discipline. The teams that do it consistently have a material advantage over the ones who treat insight as something you commission before a campaign and then set aside.

Forrester’s work on go-to-market struggles in complex categories, including device and diagnostics markets, points to a consistent theme: the companies that struggle most are often the ones whose internal view of the customer has drifted furthest from the customer’s actual experience. The insight existed. It was just not being used to challenge internal assumptions.

The growth strategy implications of this kind of ongoing insight practice are worth exploring in more depth. The Go-To-Market and Growth Strategy hub covers how audience understanding connects to the broader commercial decisions that determine whether a market entry or expansion actually works.

The Audiences You Are Not Talking To

Most audience insight work is built around existing customers. That makes sense as a starting point. You have data on them. You can talk to them. You can observe their behaviour. But it creates a systematic blind spot: the people who could be your customers but are not yet.

Non-customers are harder to reach and harder to understand. They have not opted in to your CRM. They do not appear in your analytics. They may not even be aware that your category is relevant to them. But they represent the growth opportunity that existing customer data cannot show you.

There is an analogy I have used before that captures this well. Think about a clothes shop. Someone who picks up a garment and tries it on is dramatically more likely to buy than someone who walks past the rail. The act of trying it on changes the probability of purchase. But the person who never walked into the shop in the first place is invisible to any data you collect inside it. Your conversion rate optimisation work, however sophisticated, cannot reach them. Only your reach strategy can.

Understanding non-customers requires different methods. Qualitative research with people who match your target profile but have never bought from you. Category-level data that shows you where the total addressable market sits relative to your current penetration. Competitor analysis that reveals who is buying from them and why. This kind of work is less comfortable than analysing your own customer base, because it surfaces gaps rather than confirming strengths. That is precisely why it is valuable.

Growth hacking frameworks, which resources like Semrush’s breakdown of growth hacking examples cover well, often focus on acquisition and activation loops. The insight that makes those loops effective is an understanding of why the non-customer has not yet entered the funnel, and what it would take to change that. Without that, you are optimising a funnel for the people already inclined to use it.

Turning Insight Into Operational Habit

The practical challenge for most marketing teams is not knowing that audience insight matters. It is building the habits and structures that keep it live and connected to decision-making.

A few things I have seen work consistently across different organisations and sectors.

First, assign ownership. Insight that belongs to everyone belongs to no one. Someone needs to be responsible for keeping the audience picture current and for ensuring it gets surfaced at the right moments in the planning and briefing process. That does not have to be a full-time role, but it does need to be a named responsibility.

Second, connect insight to briefs explicitly. The brief is the moment where insight either gets used or gets lost. Building a section into your brief template that requires the author to articulate what they know about the audience, what they are assuming, and what they are uncertain about forces the discipline. It also makes the assumptions visible and therefore challengeable.

Third, treat insight reviews as a standing agenda item, not a project milestone. A quarterly review of what you know about your audience, what has changed, and what that means for your current strategy takes two hours. It is one of the highest-value two hours a marketing leadership team can spend. Most teams do not do it.

Fourth, use your sales team. The people who talk to customers and prospects every day are sitting on a continuous stream of qualitative insight that most marketing teams never systematically access. Building a simple feedback loop between sales and marketing, not just for lead quality but for what prospects are actually saying, is one of the most cost-effective insight mechanisms available. Vidyard’s research into untapped pipeline potential for go-to-market teams points to alignment between sales and marketing as a consistent differentiator in revenue performance. That alignment starts with shared understanding of the audience.

Fifth, test your assumptions explicitly. When you make a strategic decision based on an audience insight, name the assumption it rests on and design a way to test it. Not a full research programme. Just a signal. A campaign variant. A conversation. Something that will tell you whether the assumption held. This turns insight from a one-time input into a learning loop.

What Good Audience Insight Work Actually Looks Like

When I have seen audience insight used well, it tends to share a few characteristics. It is specific rather than generic. It distinguishes between segments rather than describing an average. It is honest about what is known versus assumed. And it is connected to a commercial question, not just an interesting observation.

“Our audience values convenience” is not an insight. It is a platitude. “Our highest-value segment is willing to pay a 20% premium for same-day availability, but only when the purchase is time-sensitive, and that time-sensitivity is triggered by a specific set of life events we can identify through behavioural signals” is an insight. One of those changes your pricing strategy, your targeting, and your messaging. The other does not.

The specificity is what makes insight actionable. And specificity comes from going further than most teams are willing to go. It requires asking uncomfortable questions about why your audience does what it does, rather than just documenting that it does it. It requires talking to people who did not buy, not just people who did. It requires holding your assumptions up to the light and being willing to find out they are wrong.

That is harder than running a survey. It is harder than pulling a segment report from your CRM. But it is the work that produces the kind of understanding that actually changes how a business goes to market. And that is what audience insight is supposed to do.

About the Author

Keith Lacy is a marketing strategist and former agency CEO with 20+ years of experience across agency leadership, performance marketing, and commercial strategy. He writes The Marketing Juice to cut through the noise and share what works.

Frequently Asked Questions