A different type of engagement from our 30-day diagnostic - product and go-to-market advisory work for a professional services company building an AI product.
A professional services company wanted to turn their service into an AI product, but their customer base was broad enough that any product, messaging, or roadmap built for “everyone” risked landing with no one. We spoke to real users before a single feature was built.
A professional services company wanted to build their service into an AI product. Their core customer base was broad, spanning many types of clients with different needs, and there was no clarity yet on which of them the product should actually be built for, what problem mattered most to solve, or what would make someone pay for it. The risk wasn't a lack of ideas. It was building a product, messaging, and roadmap that tried to serve everyone at once, and landed with no one.
We spoke to 50+ potential users to understand who would actually pay for this, what their workflow looked like, what language would resonate with them, and what was holding them back. That research narrowed a broad, undefined customer base down to a specific type of user with a specific problem, described in their own words. Rather than starting with what to build, we started with who it was for, and shaped the UI direction, the marketing, and the roadmap around what we heard, before development went further.
Five of those conversations turned into paid pilots, each one agreeing to pay for the full product once it was built to reflect the tweaks and priorities they'd asked for. The company moved from a broad, undefined customer base to a validated product direction, a defined type of paying customer, and a roadmap built around real demand, before committing further investment in building the wrong thing for the wrong people.
The biggest product decisions happen before development begins. This company's risk was a lack of clarity on who the product was for, what they needed, and how to reach them. Validating that first meant that every feature, UX decision, and message that followed was built for customers who'd already shown their pain point was pressing enough that they'd pay for it.