ad-buyer-group-mapper

The saved excerpt is a snapshot from when this skill was listed. The external source remains the complete and most current version.

---
name: ad-buyer-group-mapper
description: "Map the likely buying committee for an offer, deal size, and industry, and give each role a messaging angle plus the ad-targeting proxy - job function and seniority, account list, account-level intent - that actually reaches them, sequenced by buying stage. Use whenever the user mentions a buying committee or buying group, decision makers, influencers or blockers, who signs off, targeting the economic buyer or a champion, per-role ad messaging, or whether one broad message beats per-role targeting - even if they never say 'buying committee'. Covers B2B committees and multi-decider household purchases. Do NOT use to size or build the audiences themselves - use mbfinotti/advertising-skills@ad-audience-targeting instead."
license: MIT
metadata:
  author: Maya-Beth Finotti
  version: "1.3.3"
---

# Buyer Group Mapper

Given a deal size, industry, and offer, identify the roles likely to sit on the buying committee, then pair each role with a messaging angle and the targeting proxy that actually reaches it on an ad platform. The output is a segment-level role map for campaign planning - role patterns for a market segment, not a named-contact map of one live deal, which is a different artifact with a stricter evidence standard.

Buying committees are B2B-native. The underlying model partially transfers to multi-decider consumer purchases (households) - see that section for what carries over and what does not.

This skill produces the role map. Turning it into sized, budgeted, sequenced audiences is mbfinotti/advertising-skills@ad-audience-targeting. Writing the ads themselves is mbfinotti/advertising-skills@ad-copy-variants.

## Clarifying questions

Ask once, briefly, before mapping; skip anything already answered.

1. What is the offer - and is this B2B, or a multi-decider consumer purchase?
2. What is the deal size / ACV band? (Drives committee size and whether per-role creative is affordable.)
3. What industry, and what buyer company size - SMB, mid-market, enterprise?
4. How large is the addressable market - hundreds of named accounts or tens of thousands?
5. What evidence about past buyers exists: closed-won/lost data, buyer interviews or call notes, review mining, account-level intent data?
6. Which platforms will run this, and at what monthly budget?
7. Is the purchase net-new for the category, a replacement, or an expansion? (Changes who is present.)
8. By what date must results land? A hard deadline promotes evidence you already own and reach you can buy this week; it demotes buyer interviews and anything needing a standing job to configure.
9. One-off campaign win, or a compounding asset the team re-uses each quarter? Compounding promotes closed-won analysis, buyer interviews and an owned account list; one-off promotes published bands and function-level reach.
10. What is the effort ceiling - research hours per account, creative variants you can actually produce, and how many roles you can coordinate across? A low ceiling promotes a merged map; a high one is what makes per-role creative affordable.

Every ranking in this skill is a default for a median team, not a law: it shifts with context and with who executes it. Re-rank each one against these answers and against what you already know about the user, then say in the output which answer moved which option. Signals worth weighing:

- An account list already owned.
- An in-house research function.
- An intent feed already licensed.
- A CRM too dirty to diff.

## Evidence gate

- Every role is a hypothesis until evidence supports it. Never assert a committee; propose one and mark each role's status.
- Pick evidence sources by efficiency - roles confirmed per hour spent - not by strength alone. The axes disagree:
  - efficiency: closed-won/lost diff > call notes > review mining > buyer interviews > published research > intent data > title inference
  - value: closed-won/lost diff > buyer interviews > call notes > review mining >