The day job · Enterprise go-to-market
Practice
Enterprise GTM Practice
- The problem
- Revenue teams forecast against personas while the decision is being made by a group nobody has fully mapped.
- The approach
- Customer voice, technology intent, account intelligence, and the unglamorous work of figuring out who actually decides.
- Where it stands
- The day work, and the source of most of what I write. Client detail stays private.
This is the day job. Most of what I write starts in a forecast call where the number is wrong, everyone knows why, and nobody says it.
What I work on
Customer voice and how it survives the trip from a call recording to a strategy deck. Technology intent and what it actually predicts. Account intelligence at the level of a specific committee rather than a segment. Buying group mapping, which is the least glamorous and highest leverage work in enterprise sales.
What transfers
Most pipeline problems are trust problems with a spreadsheet in front of them. The best predictor of a closed deal is whether the buyer can explain your value to a colleague without you in the room.
Client work is confidential. The patterns are not.
The Evidence-to-Confidence Loop
Evidence shapes the story before a seller arrives. Judgment helps the decision survive after the conversation ends.
- 01Customer evidence
Reviews, calls, and what buyers actually say.
- 02AI representation
How that evidence is summarized into an answer.
- 03Buyer perception
The story a buying group inherits before contact.
- 04Human judgment
The seller helping the group weigh risk out loud.
- 05Decision confidence
A decision that survives the rooms that follow.
- 06New customer evidence
The outcome becomes the next round of evidence.
Selected public work
- IVRIS TechAugust 2026
B2B Buying Decisions: How Sellers Build Confidence
Why a seller's value is shifting from supplying information to helping a buying group build confidence, reduce risk, and carry the decision through the rooms that follow.
Read at IVRIS Tech - HG InsightsApril 2026
From Reviews to Representation: Customer Voice in the Age of AI
Why customer reviews are moving from late-stage validation to early-stage representation inside AI-generated answers.
Read at HG Insights
