Your Demand Model Is Lying to You

A demand model is a structured framework that maps how customer demand is generated, captured, and converted across a market. It defines where demand comes from, how it moves through the funnel, and which marketing activities are responsible for which parts of that process. Get it right and you have a coherent growth strategy. Get it wrong and you end up pouring budget into channels that look productive but are mostly taking credit for demand that already existed.

Most businesses are running the second version and calling it a strategy.

I spent a significant part of my early career optimising for lower-funnel performance. Conversion rates, cost per acquisition, return on ad spend. The numbers looked good. Clients were happy. And then I started asking a harder question: how much of this demand did we actually create? The honest answer, more often than not, was: not much. We were very good at being in the right place when someone had already decided to buy. That is a useful skill. It is not a growth strategy.

What Does a Demand Model Actually Include?

The term gets used loosely, which is part of the problem. A demand model is not a marketing funnel. A funnel describes a process. A demand model describes a theory: specifically, a theory about the structure of demand in your market and how your business intends to participate in it.

A working demand model has four components. First, it identifies the total addressable demand in the market: how many people could conceivably buy what you sell, and over what time horizon. Second, it distinguishes between demand that already exists (people actively searching, comparing, or evaluating) and demand that needs to be created (people who have the problem but have not yet recognised it, or have not yet considered your category as the solution). Third, it maps the mechanisms by which your marketing activities move people from one state to another. Fourth, it assigns realistic expectations to each mechanism, including how long it takes and how you will know if it is working.

Most demand models I have seen in agency pitches and client planning sessions are missing the second component entirely. They assume that demand exists and that marketing’s job is to capture it efficiently. That assumption is fine for a mature category with high search volume and strong brand awareness. It is a disaster for a challenger brand, a new category, or any business trying to grow beyond its existing customer base.

If you are thinking about how demand models fit into broader go-to-market planning, the Go-To-Market and Growth Strategy hub covers the wider strategic context, including how to sequence investment across different growth levers.

Why Most Demand Models Are Built Backwards

Here is how most demand models get built in practice. The business looks at its attribution data. It sees that paid search and retargeting are driving the majority of conversions. It concludes that these channels are the most effective and increases investment in them. The model is then constructed to justify that conclusion.

The problem is that attribution data tells you where conversions happened, not what caused them. Someone who clicks a paid search ad and converts was almost certainly going to buy anyway. They searched because they were already in-market. The ad intercepted them at the point of purchase, which is valuable, but it did not create the demand. Something else did: a recommendation, a piece of content, a brand they had seen months earlier, a problem that became urgent enough to act on.

I think about this in terms of a clothes shop. Someone who tries something on is many times more likely to buy it than someone who walks past the window. If you only measure transactions at the till, you will conclude that the fitting room is your most important asset and stop investing in the shop window, the window display, the location. That is a reasonable short-term efficiency play. It is a terrible long-term growth strategy.

The reason go-to-market feels harder than it used to is partly because the channels that create demand and the channels that capture it have become increasingly separated, and most measurement systems are only good at seeing the latter. That gap creates a structural bias in how businesses allocate budget.

Demand Creation vs. Demand Capture: Why the Distinction Matters

The demand creation versus demand capture distinction is not new. But it remains one of the most consistently misunderstood ideas in marketing, partly because the industry has spent the last decade building tools that make demand capture look like demand creation.

Demand capture is efficient. You show up when someone is already looking. You convert them. The economics are clean and the attribution is clear. Performance marketing has become extraordinarily good at this, and market penetration strategies often rely on it heavily in mature categories where the demand pool is already established.

Demand creation is harder to measure and slower to pay back. It involves reaching people who are not yet in the market, changing how they think about a problem, and building the mental availability that means they think of you when they are eventually ready to buy. The return is real, but it is distributed across time in a way that attribution models cannot easily track.

When I was running iProspect and we were scaling the team from around 20 people to over 100, one of the hardest internal conversations was about how to balance these two things for clients. Performance marketing was our core product. It was measurable, defensible, and clients loved the dashboards. But I could see that some of our clients were growing despite their marketing, not because of it, because their category was growing and they were capturing demand that the market was generating for them. That is not a demand model. That is a rising tide.

The businesses that struggled most were the ones that hit the ceiling of existing demand and had no mechanism for creating new demand. They had never needed to build that muscle because performance had always delivered. When it stopped delivering, they did not know why.

How to Build a Demand Model That Reflects Reality

Building a demand model that actually works starts with rejecting the idea that your attribution data is a reliable map of your demand landscape. It is one perspective on reality, not reality itself. Here is how I approach it.

Start with the market, not your funnel. Before you look at your own data, try to understand the structure of demand in your category. How many people are actively in-market at any given time? How many have the problem but are not yet looking for a solution? How many are entirely unaware? This is not always easy to quantify precisely, but making an honest estimate forces you to confront how much of the demand pool you are currently reaching.

Separate your demand into two buckets. Existing demand (people who are actively searching, comparing, or evaluating your category) and latent demand (people who have the problem but are not yet in-market). Your performance marketing is almost certainly serving the first bucket well. The question is whether you have any strategy for the second.

Map your demand creation mechanisms explicitly. What are you doing to reach people who are not already looking? Content, brand advertising, partnerships, earned media, community, word of mouth: these are all demand creation mechanisms. They need to be in your model with realistic expectations about timelines and measurement approaches. BCG’s work on brand and go-to-market strategy has consistently pointed to the importance of aligning brand investment with commercial strategy rather than treating them as separate disciplines.

Be honest about attribution limitations. Your demand model should include an explicit acknowledgment of what you can and cannot measure. If you are running brand activity, you probably cannot attribute conversions to it directly. That does not mean it is not working. It means you need a different measurement approach: brand tracking, share of search, customer surveys, cohort analysis of markets where brand investment is higher.

Build in a growth loop assumption. The strongest demand models include a mechanism for compounding: where satisfied customers generate new demand through referral, review, or repeat purchase. Growth loops are more durable than linear funnels because they do not require constant external input to sustain momentum. If your demand model has no loop, you are on a treadmill.

The Danger of a Demand Model That Appears to Be Working

One of the more uncomfortable things I have had to tell clients over the years is that their marketing might not be the reason their business is growing. Category growth, economic tailwinds, a competitor’s misstep, a viral moment that was never part of the plan: any of these can drive revenue growth that gets attributed to marketing activity that had little to do with it.

I have judged the Effie Awards, which recognise marketing effectiveness, and the best entries are always the ones that can demonstrate a credible causal link between the marketing activity and the business outcome, controlling for other factors. Most entries cannot do that. They show correlation and call it proof. The same is true of most internal marketing reports I have reviewed.

A demand model that appears to be working because the business is growing is the most dangerous kind, because it gives you false confidence. You scale the wrong things, you under-invest in demand creation, and you only discover the problem when growth stalls and you have no mechanism to restart it. BCG’s analysis of go-to-market launches highlights how often businesses mistake market momentum for strategic effectiveness, particularly in the early stages of a product or category.

The test I use is simple: if your market stopped growing tomorrow, what would happen to your revenue? If the honest answer is “it would fall significantly,” you probably do not have a demand model. You have a demand capture operation running in a favourable environment.

Where Growth Hacking Fits Into a Demand Model

Growth hacking gets a lot of attention as a methodology, and some of the tools and tactics associated with it are genuinely useful for identifying demand signals and optimising conversion. Growth hacking tools can help you find pockets of latent demand, test messaging quickly, and iterate on acquisition channels with relatively low cost.

But growth hacking is a set of tactics, not a demand model. The mistake I see regularly is businesses treating growth hacking as a substitute for strategic thinking about demand. You can optimise your onboarding flow, your referral programme, and your activation sequence and still have a fundamentally broken demand model if you do not understand where your customers are coming from and why.

Growth hacking as a discipline is most effective when it operates within a clear demand model, not instead of one. It helps you convert demand more efficiently. It rarely creates demand where none exists.

My first week at Cybercom, I was in a brainstorm for Guinness. The founder had to step out for a client call and handed me the whiteboard pen. My internal reaction was something close to panic. But the experience taught me something useful: having a framework for thinking about demand, even a rough one, is what separates someone who can lead a room from someone who just fills time until the real decision-maker comes back. Tactics without a demand model are exactly that: filling time.

Applying a Demand Model Across Different Market Contexts

A demand model is not a universal template. It needs to reflect the specific structure of demand in your market. A few contexts where this matters most.

New categories. If you are creating a category that does not yet exist, your demand model is almost entirely about demand creation. There is no existing search volume to capture. The job is to make people aware that the problem exists and that your solution is the right response to it. This requires patience and a willingness to invest in channels that will not show clean attribution data for months or years. Forrester’s analysis of go-to-market challenges in healthcare illustrates how even well-funded businesses underestimate the time and investment required to build category awareness from scratch.

Mature categories. In a mature category with high search volume and established competitors, demand capture is more important relative to demand creation. The market already understands the problem. Your job is to be the preferred solution when someone is ready to buy. Brand investment still matters here, because it shapes preference before the search happens, but the ratio shifts.

Challenger brands. Challengers face a specific demand model problem: the category leader is capturing the majority of existing demand, often because they have higher brand awareness and more resources to compete on performance channels. The only viable demand model for a challenger usually involves creating demand in segments or use cases the leader is not serving well, or reframing the category in a way that makes the leader’s position a disadvantage.

Across all three contexts, the discipline is the same: be explicit about where your demand is coming from, what you are doing to expand it, and how you will know if your theory is correct. A demand model is a hypothesis about your market. It should be tested, not assumed.

If you are working through how to sequence these investments across a full go-to-market plan, the broader thinking on growth strategy and go-to-market planning covers how demand modelling connects to channel strategy, positioning, and commercial planning.

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.

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