When we build a form, we decide what to ask, what an answer means and what should happen next. Once people use it, those assumptions meet reality.
I think there is a business in making that learning useful. A form can reveal where an offer is unclear or which question helps someone explain what they need. That knowledge should improve the next thing we build.
Learn from the work
Take Handschriftpost. I can imagine combining knowledge about its technology with what we learn from enquiries and the work that follows. That could help us understand which questions matter and build better funnels over time.
The same thought applies to Konfigurator.io. The questions in a flow contain assumptions about the customer. Seeing where those assumptions hold up would give us something useful to carry into the next project.
Give the knowledge back
The customer should be able to use that knowledge too. I can imagine a paid API or a dataset that they work with using their own AI and software. It could contain explanations of the technology, observations from their own flow and what we have learned about improving it.
I would want the source and scope to stay visible. An observation from one project is not a universal rule. A useful recommendation should make clear what it is based on and which assumptions still need testing.
Become a knowledge partner
Alongside the technology, we could help interpret what happens and turn that understanding into better decisions. The relationship could continue even when the customer runs the form or software on their own infrastructure.
This is a direction I want to explore, rather than an API or data product we already sell. I want software to make its users more capable with every project. Part of its value would be the knowledge they take away.
Related: Deimann Exchange · Konfigurator.io · Company principles
