Take two identical bottles of wine. Pour one into a paper cup at an airport hotel. Pour the other in a beautiful restaurant after the sommelier tells you about the tiny vineyard in Burgundy where it was made.
Chemically, they are identical. Commercially, they are not even close. A Rolex tells the time. So does a Casio. A Hermès bag carries things. A Ferrari gets stuck in traffic.
We like to imagine there is some objective quantity called value buried inside a product. Engineering puts it there. Operations improves it. Finance measures it. Marketing comes along afterward and explains it.
Rory Sutherland has spent years arguing against this way of thinking. His line is better than mine:
“Value can be created in the mind every bit as much as it can be created in the factory.”
That is the whole idea. The psychological value is not fairy dust sprinkled on top of the real product. It is part of the product.
This is just as true in enterprise software. Nobody buys cybersecurity because they love packet inspection. They buy confidence that they will not be standing in front of the board explaining a breach. Nobody particularly wants accounting software. They want to stop worrying that the numbers are wrong. The emotional job does not disappear because the buyer is wearing a suit.
Why Companies Miss This
Companies have a bias toward value they can point at: more features, better materials, faster processors, more engineers. These improvements are easy to defend internally. If somebody proposes spending $2 million making the product 20% faster, engineering can estimate the work, finance can model the cost, and the board can put it in a spreadsheet.
Now suppose the real problem is that customers do not trust you. Or the product looks cheap. Or your pricing makes people suspicious. Or you are explaining something remarkable in a way that makes it sound ordinary.
Those arguments are harder. There may be no dataset proving them. There may only be an observation about human behavior and a conviction that people are responding to something different from what the company thinks it is selling.
This is where analysis reaches its limit. Data is extremely good at describing the world under the existing frame. It is much worse at imagining a different frame. If nobody buys your $20 product, the spreadsheet can tell you nobody buys it. It cannot necessarily tell you that they might desperately want the same thing for $200 once you change who it is for, what it means, and what the price itself signals.
Data Has a Creativity Problem
Modern business is extraordinarily good at optimization. We measure conversion, CAC, LTV, retention, attribution, engagement, churn, and almost anything else worth putting on a dashboard. That is useful once you are heading in the right direction. It is much less useful when the direction itself is wrong.
Data is very good at helping you choose between A and B. The interesting commercial move is often realizing the answer is Q.
That requires understanding what people are afraid of, what they want to become, what makes them feel clever or stupid, what they brag about, what they hide, and what story they are already telling themselves. Then you change the business to fit that reality.
Sometimes that means changing the advertising. Sometimes it means changing the product, increasing the price, removing features, changing the customer, or putting the exact same thing in a different category. At that point, the distinction between product and marketing becomes fairly meaningless. Both are working on the same thing: the reason somebody cares.
Solve the Psychological Problem
One of Sutherland’s favorite examples is the Uber map. What people hate about waiting for a taxi is not only the wait. It is the uncertainty. Showing the car moving toward you changes the experience without making the car move much faster.
The same logic appears everywhere once you start looking for it. A hotel can spend millions reducing check-in time, or simply give somebody a drink while they wait. A train operator can run more trains, or tell passengers exactly when the next one will arrive. In each case, the physical problem and the psychological problem are different.
This is the kind of move I am always looking for, not because it is cheap, but because it is asymmetric. A company can spend years engineering a 10% improvement while a change in perception produces a radically larger change in willingness to buy.
That does not mean psychology can rescue a bad product forever. Reality eventually wins. But I see the opposite mistake much more often: companies assume that if they keep improving reality, perception will eventually take care of itself.
It often doesn’t.
You can have an extraordinary product that looks ordinary. You can solve a painful problem in language that makes it sound trivial. You can have technology capable of changing an industry and package it like another SaaS tool. At that point, building more is not product development. It is avoidance.
The job is to understand why the value you see has not appeared in the customer’s mind, then change whatever needs changing until it does: the product, the price, the story, the context, the customer, and sometimes even the category.
The customer does not experience the boundaries between product, positioning, brand, and marketing. They experience one question:
Do I want this?
That is where value becomes real.