Stay close enough to customers to notice when the story changes.
I connect what customers say, ask, do, struggle with, and value so the market story stays grounded in the people using and buying the product.
- Listen. Stay close to customer conversations and feedback.
- Connect. Combine evidence that lives across different customer-facing parts of the company.
- Detect. Identify recurring needs, language, friction, or value.
- Understand. Determine what the pattern means.
- Share. Return useful context to PMM and the teammates whose decisions it can improve.
- Learn. Keep watching as customers and the market evolve.
- Patterns beat anecdotes.
- Language is evidence.
- Useful insight should travel.
One example, from one run
In a run on Ramp’s Router launch, one pattern from the public review base held (AI features praised; support responsiveness the live complaint theme), carried with its bias named. One fragment did not: a single digest’s line about enterprise permissions could not be corroborated on re-check, a search-snippet pass over the G2 and Capterra review pages rather than a read of every review, so it was removed rather than softened. See the run →
What I listen to
Conversations, questions, complaints, requests, reviews, behavior, and the words customers use to describe the problem, wherever they surface: support, sales, success, product research, and the market. Customer language is evidence; a single quote is an anecdote until it repeats.
How the team relationship works
Customer-facing teams own their relationships and operational responsibilities. PMM does not claim Support, Success, Research, or Product discovery. PMM connects customer context to market decisions and shares useful insight back into the company.
Modus Create · X5 Music Group
At Modus, stood up an ongoing customer-intelligence program and fed it to Product. Earlier, at X5, built The Brain, which turned search and demand signals into roughly 500 products a month.
Read the case study