Better Data Won’t Save a Customer Who Still Feels Stuck
Better data can expose better options, but if the customer still cannot decide, the business has not solved the real problem.
Better data can expose better options, but if the customer still cannot decide, the business has not solved the real problem.
Better Data is one of the easiest ideas to believe in when you come from a technology, analytics or product background.
It feels logical. If people have better information, they should make better decisions. If the market is confusing, show them more signals. If the options are hard to compare, build a better dashboard. If the customer is uncertain, give them more analysis.
For a long time, I believed some version of this.
That belief was not completely wrong. Data can reduce confusion. It can reveal patterns that are otherwise hidden. It can challenge assumptions. It can make a market, a process or a decision more visible. In many industries, the absence of good data is a real problem.
But building AbodeFinder taught me that data alone rarely completes the customer’s journey.
The Assumption Behind Better Data
AbodeFinder started inside Intellicy. It was not originally a standalone property advisory business.
At the time, I was thinking about a broader problem inside consulting. Consulting creates value, but it also has a structural limitation: much of the value is tied to expert time. More clients usually mean more hours, more delivery pressure and more dependence on the judgement of specific people.
That led me to explore how parts of our expertise could become more repeatable through software, data and AI-enabled services. This was before ChatGPT became the public symbol of AI. We were not trying to follow a trend. We were trying to answer a business-model question: how can knowledge, judgement and analysis become more scalable without losing their usefulness?
One of the products that came out of that thinking eventually became AbodeFinder.
The original idea behind AbodeFinder was simple. Property buyers face an overwhelming amount of information. They need to compare suburbs, understand market signals, look at affordability, assess opportunity and avoid emotional or poorly informed decisions. A better product could organise that information and help buyers see the market more clearly.
So we built in that direction.
When Useful Is Not Enough
The application was designed to make property analysis more accessible. It could bring together information, compare locations and help buyers think about opportunities with more structure.
From a product perspective, this made sense.
From a data perspective, it made sense.
From a founder’s perspective, it felt like a useful answer to a real problem.
But usefulness is not the same as completion.
A customer could look at better suburb data and still feel uncertain. They could understand a market more clearly and still not know whether the decision made sense for their personal situation. They could compare locations and still feel exposed.
That was the uncomfortable lesson.
The customer was not only asking, “Where is the opportunity?”
They were also asking, “Is this the right decision for me?”
Those are different questions.
The Difference Between Information and Confidence
The first question can often be supported by data. The second question requires a broader decision journey.
It involves borrowing capacity, financial position, risk tolerance, lifestyle, timing, confidence, trade-offs and sometimes emotional pressure. A dashboard can support that decision, but it does not automatically carry the customer across it.
This is where many product-led and technology-led businesses make a quiet mistake. They assume that if the information is useful, the value has been delivered.
But customers do not usually buy information for its own sake.
They buy progress.
They buy a reduction in uncertainty.
They buy the ability to act with more confidence.
That distinction changed how I thought about AbodeFinder.
Why AbodeFinder Had to Evolve
We had to move beyond the idea that the product was only an information tool.
The real customer journey was bigger than the original product boundary. People did not simply need more property data. They needed to understand what that data meant in relation to their budget, borrowing capacity, goals and risk. They needed a path from analysis to action.
That is why financial services and advisory support became part of the model.
Not because the original product was useless, but because the original product was incomplete. The data was part of the value, but it was not the whole value.
This changed how I think about business design more broadly.
A business can be technically correct and still fail to solve the full customer problem. A product can work and still leave the customer stuck. A report can be accurate and still not change the decision. An AI recommendation can be impressive and still not create trust.
The Better Question to Ask
The question is not only:
“What can we show the customer?”
The better question is:
“What can the customer now decide, avoid or achieve because this exists?”
That question forces the business to become more honest about value.
If the customer still cannot decide, the business may not have designed the value clearly enough. If the customer still feels exposed, the business may not have designed trust deeply enough. If the customer needs a human to explain every important step, the business may not have designed the system properly. If the product keeps producing information but the customer journey does not improve, the business may be measuring output instead of progress.
AI Makes This Problem Bigger
This is especially important now because AI makes it easier than ever to produce more.
More reports. More summaries. More recommendations. More dashboards. More content. More analysis. More personalised outputs.
But more output does not necessarily mean more value.
AI can accelerate the creation of information, but it does not automatically understand the customer’s decision context. It can make a product feel smarter, but that does not mean the customer feels more confident. It can produce a recommendation, but it cannot replace the need to design the path that makes that recommendation useful, trusted and actionable.
This is why I am cautious when companies begin with the question, “Where can we use AI?”
It is not a bad question, but it is often asked too early.
A better starting point is:
“Where is the customer currently stuck, and what kind of progress are we responsible for helping them make?”
Only after that question is clear does AI become a useful design choice.
Data Needs to Sit Inside Value Design
In the case of AbodeFinder, the lesson was not that data was unimportant. The lesson was that data needed to sit inside a more complete value design.
The product had to support a decision, not simply display information. The customer needed clarity, but also confidence. They needed insight, but also a way to act on it.
That lesson is not limited to property.
It applies to consulting, where clients often receive detailed recommendations but still struggle to make decisions internally. It applies to enterprise transformation, where dashboards can show performance without changing accountability. It applies to AI adoption, where organisations produce more automated output without redesigning the process around it. It applies to media and content, where publishing more information does not automatically build trust.
In each case, the same pattern appears.
The business believes it has delivered value because it has delivered information, analysis or output. But the customer is still carrying the harder part of the journey alone.
What This Taught Me About The Designed Business
This is one of the reasons I am writing The Designed Business.
The central idea of the book is that growth does not fix the business. It reveals what has already been built. If a business has not clearly designed the problem it solves, the value it creates, the trust it requires, the system that delivers it and the learning loop that improves it, growth will not quietly repair those gaps. It will expose them.
AbodeFinder exposed one of those gaps for me.
It showed me that the value of a business is not always where the founder first thinks it is. I thought the product was mainly about better property data. The customer showed me that the deeper value was confidence in a decision.
That shift matters.
When a business understands that shift, it designs differently. It sells differently. It uses technology differently. It decides what should be automated and what should remain human. It measures success differently. It stops asking only whether the product works and starts asking whether the customer has moved.
That is a much harder standard.
But it is also a more useful one.
The Real Destination Is Not the Dashboard
Better Data can make the world more visible. It can show patterns, risks and possibilities. It can help customers think more clearly than they could before.
But visibility is not the same as progress.
A customer can see more and still hesitate. They can understand more and still feel uncertain. They can receive better analysis and still not know what to do next.
That is the point where the real business design begins.
Not at the dashboard.
Not at the report.
Not at the AI output.
At the moment where the customer asks:
“So what should I do now?”
The businesses that answer that question well are not just providing information. They are designing confidence.