When customer signal is messy, I help turn it into a product decision that moves your team forward

When I'm most useful

I’m most useful when a team has plenty of customer information but no clean way to decide what it means for the next product, positioning, or service decision.

That might mean working through several plausible versions of the customer, conflicting interpretations of the same evidence, or a product team moving quickly without knowing whether the customer hypothesis still holds.

The work can take the shape of a Listening Cycle, a fuller featured Bullseye Customer Sprint, or a fractional engagement. The format and mode change but the job is the same: get closer to the evidence, make sense of it together, and turn it into a decision the team can act on.

I came into this through UX and service design, and that 100% shapes how I operate. I lean into the messy, complicated bits where several actors, channels, or teams are involved and the right response isn’t obvious. That can mean research and framing, journeys or service models, facilitated decisions, concepts and prototypes, and enough implementation thinking that the work doesn’t stop at the feel good vibes of a workshop.

AI helps me work across larger evidence sets and move faster through synthesis, but direct customer evidence and human judgment stay at the center.