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SKILL DETAIL
ad-buyer-group-mapper
mbfinotti/advertising-skills/ad-buyer-group-mapper
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.
安裝量 · 177查看來源
Installation
npx skills add https://github.com/mbfinotti/advertising-skills --skill ad-buyer-group-mapper
技能檔案
SKILL.md
最近同步 · 2026年9月24日
evals/evals.json›
{
"skill_name": "ad-buyer-group-mapper",
"evals": [
{
"id": 1,
"prompt": "I run demand gen at Kindra Systems - workforce-analytics platform, $90K ACV, selling to mid-market healthcare (500-2,000 employees). We're building an ABM program and I need to figure out who is actually on the buying committee so we can run ads per role. My plan: kick off 15 buyer interviews next quarter to map the committee properly, and we just licensed a third-party account-intent feed - I'm hoping it can show us who at each account is involved in the purchase. What we have today: 42 closed-won and 30 closed-lost deals in the CRM with clean stage history, and call recordings on most of them. The campaign has to launch in 6 weeks. How should we build the committee map?",
"expected_output": "A committee-mapping plan that starts from the won/lost diff plus existing call notes, defers the interviews, restricts the intent feed to account ranking, and delivers roles as evidence-graded hypotheses with disproof tests.",
"files": [],
"expectations": [
"Recommends diffing which roles appear in closed-won deals against closed-lost deals as the first evidence step, before any new data collection",
"Uses the existing call recordings to fill gaps left by the won/lost diff rather than commissioning new research",
"Does not endorse running the 15 buyer interviews as the first step; interviews are deferred until a specific role's presence remains ambiguous after the diff and the call notes",
"States that the 6-week deadline demotes buyer interviews (about a week of scheduling) in favor of evidence the team already owns",
"States that the intent feed resolves to accounts, not people, and therefore cannot confirm which roles sit on the committee",
"Restricts the intent feed to ranking which accounts to cover, never to confirming roles or identifying committee members",
"Quantifies intent-data limits: roughly 81% account-level accuracy, or equivalently that about one in five surging accounts has no genuine near-term intent",
"Labels every proposed committee role as evidenced or hypothesis instead of asserting the committee as fact",
"Attaches a concrete disproof test to at least one hypothesis role, such as cutting it if absent from a stated number of upcoming won-deal notes",
"Identifies title inference as the weakest evidence source, a floor never to stop on",
"Gives effort in orders of magnitude: the won/lost diff about a day per deal-size segment, buyer interviews about a week of scheduling",
"Flags a compliance cost on at least one source: per-participant recording consent for interviews, or a licensing and privacy review before first use of the intent feed"
]
},
{
"id": 2,
"prompt": "We sell Denticor, a $7K/year scheduling and recall tool for independent dental clinics (1-3 locations). Our new VP of marketing read that B2B purchases involve 6 to 10 decision makers, so she wants ad campaigns built for eight personas: practice owner, office manager, lead dentist, IT consultant, procurement, compliance, finance, and front-desk staff. Looking at our CRM notes from the last 40 wins, it's almost always just the practice owner and the office manager on the calls. Can you map the buying committee and the campaigns per role?",
"expected_output": "A two-role map derived from the user's own win notes that rejects the eight-persona plan, explains why the 6-10 figure does not apply, and recommends one consolidated campaign.",
"files": [],
"expectations": [
"Rejects the 6-to-10 decision makers figure as universal, stating it describes complex purchases only",
"States that primary committee-size studies disagree by roughly a factor of two because each defines involvement differently and samples different deal sizes",
"Derives committee size from the user's own CRM win notes (about two people) rather than from published figures",
"Cites the SMB band of 2-3 committee members as consistent with the user's own data",
"Recommends a two-role map - a champion-who-is-the-user (practice owner or office manager) plus an economic buyer - instead of eight personas",
"Cuts procurement, compliance, and finance as separate roles, noting those stages do not exist in a $7K purchase, and refuses to fill empty role slots for completeness",
"States that no published data segments committee composition by industry or purchase type, rather than extrapolating a dental-specific composition",
"Treats the published committee-size figures as a sanity band without ranking the studies against each other",
"Deletes any proposed role that changes no targeting, creative, or offer decision",
"The committee summary names the evidence source behind the size estimate (the user's own win notes)",
"Recommends one consolidated campaign or merged map rather than per-role campaigns, since the case sits below both the roughly 500 named-account and roughly $100K ACV thresholds"
]
},
{
"id": 3,
"prompt": "Planning our LinkedIn ads for Loopwell (revenue-intelligence platform, $45K ACV, mid-market B2B). We mapped five committee roles and I want one campaign per role, targeting exact job titles - 'Head of Revenue Operations', 'Director of Sales Enablement', 'VP Revenue Operations' - stacked with seniority filters to keep it tight. Each audience comes out around 2,500-3,500 members, which feels nicely focused. Budget is $9K/month. We also uploaded our 900-account ABM list, so those people already know who we are - I figure we can go straight to demo-request ads for them. Can you sanity-check the targeting plan and give me the messaging per role?",
"expected_output": "A corrected targeting plan that replaces exact titles with function plus seniority on the account list, merges sub-floor audiences, treats the list as cold, and holds demo asks until warmth is earned.",
"files": [],
"expectations": [
"Rejects exact job-title targeting as the primary proxy and recommends job function plus seniority instead",
"States platforms understand only roughly 30-50% of job titles, so every title variant not listed is simply missed",
"States function plus seniority roughly triples the addressable audience at similar engagement",
"States that on professional networks title targeting and seniority targeting are mutually exclusive and cannot be stacked",
"Flags the 2,500-3,500-member audiences as below the roughly 5,000 significance floor and far below the 20,000-50,000 practical floor",
"States the audience floor before splitting roles, and merges roles whose proxy audiences collide or undershoot rather than shipping five sub-floor audiences",
"Notes each member gets exactly one job function on professional networks, so a cross-functional role like Revenue Operations straddles cells and requires targeting two functions to cover one role",
"Warns that stacking AND conditions below roughly 50,000 members degrades delivery",
"Recommends account list plus function plus seniority as the default proxy given the enumerable 900-account market",
"Notes function and seniority derive from self-reported profiles with no inference, inheriting stale or inflated titles",
"Corrects the claim that the ABM list means people know the brand: list membership is an account signal and every individual on it is still cold",
"Does not endorse demo-request ads as the first touch to the cold list audience",
"Warns that a narrow audience all seeing one generic ad is worse than a broader audience seeing role variants - creative variants first, filters second"
]
},
{
"id": 4,
"prompt": "I'm the only marketer at Corvine Data (data-quality monitoring, $30K ACV). Our market is huge - something like 40,000 companies fit the ICP. I just read a piece on buying committees and I'm sold: I want six separate campaigns, one per committee role, each with its own creative. Monthly budget is $15K, and realistically I can produce about one ad concept per month by myself. Draw up the six-role campaign plan?",
"expected_output": "A refusal of the six-campaign plan on threshold and capacity grounds, replaced by a merged map (one primary angle plus role-aware proof points) to a broad audience, with the precision-vs-reach dispute stated honestly.",
"files": [],
"expectations": [
"Tests both precision thresholds explicitly - roughly 500 named accounts and roughly $100K ACV - and states this case clears neither",
"Recommends the merged map, one primary angle plus role-aware proof points in a single campaign, shipped to a 20,000-50,000-sized audience, instead of six per-role campaigns",
"Cites the out-market argument: roughly 95% of B2B buyers are out-market at any time, so hyper-narrow targeting wastes the reach that builds future demand",
"Deletes per-role campaigns from the menu by name because a single generalist marketer cannot run six campaigns, rather than ranking them last as a stretch goal",
"States the precision-versus-reach dispute is unresolved: no controlled test compares role-differentiated creative against a single strong message",
"Steelmans the precision side (bounded reach in small named-account markets, high-ACV economics, activation for the in-market share) instead of dismissing it",
"Gives effort in orders of magnitude: per-role campaigns about a quarter, the merged map about a week",
"Includes the flip check: tightening further is justified only if CPM inflation and frequency on the narrow audiences are not degrading cost per opportunity",
"Deletes both list-based targeting rungs for the roughly 40,000-company market and plans on function plus seniority",
"Directs the role knowledge into proof-point variants inside the single campaign rather than into audience splits",
"The committee summary states which precision-vs-reach posture the map takes and why",
"The output carries a named list of every option a stated constraint deleted from a menu",
"States as a caveat that per-role creative outperforming a single strong message is unproven, framing the campaign KPIs as the test of which side of the dispute this market is on"
]
},
{
"id": 5,
"prompt": "Metriq Systems sells a $150K ACV supply-chain planning suite to enterprise manufacturers; about 300 named target accounts. Two problems: deals keep dying late when the security review shows up in month five and reopens everything, and an embarrassing share just fizzle out with no decision at all. Leadership wants an ad push that creates urgency - countdown-style 'cost of waiting' messaging aimed at CFOs and security reviewers - with everything gated behind forms so sales gets the leads. We have call recordings and win/loss notes from about 30 deals. Build the committee map and the campaign sequencing.",
"expected_output": "A committee map with sequencing that replaces urgency with risk-reduction messaging for economic buyers and gatekeepers, reaches security before validation, and runs ungated content instead of form-gated capture.",
"files": [],
"expectations": [
"Rejects urgency and countdown-style messaging for the economic buyer and gatekeepers, recommending risk-reduction and proof instead",
"States 40-60% of deals end in no-decision and about 56% of those are lost to indecision (fear of messing up) rather than status-quo preference, which is why amplifying urgency backfires",
"Recommends reaching security, legal, and procurement before the validation stage, noting a security reviewer added late can reopen requirements and reset agreed work",
"Calls reaching validation-stage roles before validation the cheapest insurance in the map",
"Models the journey as six looping buying jobs that roughly 90% of buyers revisit, not a linear funnel",
"Rejects gating the content behind forms, citing that fewer than 30% of eventual buyers ever fill a form on the winning vendor's site",
"Cites that roughly 70% of the journey completes before any seller contact and/or that 81-84% of deals go to the first vendor contacted, so ungated content and paid reach must carry the pre-contact phase",
"Maps arrival order: end users and the initiator at problem identification, the economic buyer at the business case, gatekeepers at validation",
"Cites that 79% of purchases require CFO approval when placing the economic buyer",
"Assigns the security gatekeeper an ungated compliance/security documentation pack, delivered before the validation stage",
"Judges per-role creative defensible under the thresholds, since about 300 named accounts and $150K ACV clear both",
"Gates committee-wide multi-role targeting on account-level intent or engagement (surging or engaged accounts), not a cold industry-wide list",
"Includes a sequencing-notes section mapping which roles to reach at which buying job and where risk reduction replaces urgency"
]
},
{
"id": 6,
"prompt": "I do marketing for Hearthside Climate, a regional HVAC installer. An average full-system replacement runs $14K. From our reviews it's clear one partner does all the research and the other one mostly worries about getting locked into a bad contract. Two questions: first, can we target each spouse separately with different ads - I heard connected-TV household graphs can do that; second, should we build the same decision-maker mapping for our $89 duct-cleaning tune-up offer? We have about 220 customer reviews to work from.",
"expected_output": "A household map using the consumer role model, role-differentiated creative to one shared household audience instead of per-member isolation, and a refusal to apply committee mapping to the routine $89 offer.",
"files": [],
"expectations": [
"Uses the consumer five-role vocabulary (initiator, influencer, decider, buyer, user) or an explicit subset of it for the household map",
"States what carries over from organizational buying: the user often is not the approver, each decider needs a different message, and one unconvinced member can veto",
"States at least two things that do not transfer: no procurement, legal, or security review; no career risk (the fear is personal and financial); personal money rather than company money; reviews and peers instead of RFPs",
"Recommends role-differentiated creative shown to one shared household audience instead of trying to isolate each partner",
"States household-graph and shared-device targeting is imprecise and unquantified",
"Declines to build a decision-maker map for the $89 tune-up offer, stating routine purchases have one decider and the mapping is overhead",
"Confirms the $14K system replacement qualifies as a high-consideration category with a genuine second decider",
"Grounds the roles in the 220 reviews and labels each role evidenced or hypothesis",
"Gives the researcher partner and the contract-worried partner distinct messaging angles, neither of which could run unchanged against the other role",
"Does not import B2B committee statistics (such as 6-10 decision makers or CFO-approval rates) into the household map",
"Weights the contract-worried partner's angle toward risk reduction, such as warranty terms or contract safeguards, drawn from the stated fear of lock-in",
"Fills per-role fields including a messaging angle and a proof/offer type for each surviving household role"
]
},
{
"id": 7,
"prompt": "Freightlane, $60K ACV logistics-visibility platform, mid-market shippers. Our champions love us but deals stall in committee - our main contact can't seem to get the rest of the group moving. Sales wants ad campaigns aimed at 'influencers' inside the target accounts, and our CEO insists every ad ends with 'Book a demo'. We hold SOC 2 Type II already. Someone also floated producing a big industry benchmark report, though we don't have any proprietary data. We've got two years of call recordings. Map the committee with messaging and offers per role.",
"expected_output": "A role map that rejects the influencer label, reframes the stuck-champion problem as needing a consensus-driver, replaces demo-everywhere with friction-matched offers led by the compliance pack, and deletes the benchmark report.",
"files": [],
"expectations": [
"Rejects 'influencers' as a role label, stating it yields no targeting attribute and no messaging angle",
"Distinguishes champion, coach, and mobilizer, and states a champion who cannot move the group calls for a consensus-driver, not a louder champion",
"Rejects ending every ad with a demo CTA and matches offer friction to role warmth instead",
"Cites the conversion bands: low-friction offers around 10-15% versus cold demo or trial requests around 1.5-4%",
"States cold gatekeepers do not book demos at all",
"Sets the default offer rung per role to an ungated low-friction asset, escalating only after that role's proxy audience engages twice, never on the first touch",
"Promotes the compliance/security pack given the SOC 2 Type II already held (about an hour to assemble), noting it removes a validation-stage veto",
"Deletes the benchmark report from the offer menu because no proprietary data exists, rather than ranking it last",
"Notes a demo or trial is a standing job because each one spends sales capacity again",
"Runs the swap test on angles: flags, rewrites, or merges any angle that could run unchanged against another role",
"Sources verbatim customer language from the two years of call recordings for the messaging angles, stating exact phrases beat polished descriptions",
"Fills all six per-role fields: measured on, personal risk, likely objection, messaging angle, proof/offer type, targeting proxy",
"Marks any role or objection seeded from generic patterns as a hypothesis to verify against the user's own call notes, noting fine-grained per-role objection maps are weakly evidenced in published research"
]
}
],
"trigger_queries": [
{ "query": "Map the buying committee for our $80K ACV compliance platform selling to mid-market fintech", "should_trigger": true },
{ "query": "Who's actually involved in the decision when a hospital buys scheduling software, and what do we say to each of them?", "should_trigger": true },
{ "query": "who signs off on a $200k security tool purchase and how do I reach them with ads", "should_trigger": true },
{ "query": "We need different LinkedIn ad messaging for the CFO vs the end users - help me structure it", "should_trigger": true },
{ "query": "who else decides when a family buys solar panels and what do we say to each", "should_trigger": true },
{ "query": "My champion is sold but the deal is stuck - who else do I need to be advertising to?", "should_trigger": true },
{ "query": "build me a buying group map for our HR software", "should_trigger": true },
{ "query": "Which job functions and seniorities should we target for each member of the buying committee?", "should_trigger": true },
{ "query": "our ads only reach end users but finance keeps killing the deals - how do we get in front of the budget owner", "should_trigger": true },
{ "query": "decision makers vs influencers vs blockers in enterprise deals - how do I target each on paid social?", "should_trigger": true },
{ "query": "Should we run one broad ad campaign or separate campaigns per stakeholder role?", "should_trigger": true },
{ "query": "What's the right messaging angle for procurement and security reviewers in our ad campaigns?", "should_trigger": true },
{ "query": "husband researches the car, wife has the final say - how should our dealership ads handle that", "should_trigger": true },
{ "query": "I keep hearing B2B purchases involve 6-10 people. How do I figure out who they are for my product and reach them with ads?", "should_trigger": true },
{ "query": "map out who's in the room when a mid-market company buys payroll software", "should_trigger": true },
{ "query": "per-role ad creative for an ABM campaign - which roles and what does each need to hear", "should_trigger": true },
{ "query": "we're launching ABM ads - help me figure out which personas at each account need which message", "should_trigger": true },
{ "query": "who do I target ads at for a $500k ERP deal besides the CIO", "should_trigger": true },
{ "query": "Economic buyer vs champion - how should our ad targeting treat them differently?", "should_trigger": true },
{ "query": "how do committees buy martech and when does each stakeholder show up in the deal", "should_trigger": true },
{ "query": "what ad audiences reach a VP of Engineering vs their security team for the same account list", "should_trigger": true },
{ "query": "the IT guy loves our product but someone above him keeps blocking the purchase - how do we advertise to whoever that is", "should_trigger": true },
{ "query": "stakeholder mapping for paid media - our deals involve like 5 different people", "should_trigger": true },
{ "query": "when in the buying process should our ads hit legal and procurement?", "should_trigger": true },
{ "query": "Give each buying role its own message and tell me how to actually target them on ad platforms", "should_trigger": true },
{ "query": "how do families decide on private school and how should our ads speak to each parent", "should_trigger": true },
{ "query": "I need an ad plan that covers everyone involved in the purchase, not just our main contact", "should_trigger": true },
{ "query": "our product is used by analysts but bought by their directors - how should the ads differ", "should_trigger": true },
{ "query": "buying group targeting on LinkedIn - which functions and seniority per role?", "should_trigger": true },
{ "query": "Who are the hidden stakeholders killing our deals at the end, and can ads pre-empt them?", "should_trigger": true },
{ "query": "one message for the whole committee or tailored ads per role - what's right for a $40k ACV product?", "should_trigger": true },
{ "query": "help me identify the decision making unit for our fleet management software and craft ads for each member", "should_trigger": true },
{ "query": "DMU mapping for B2B ads", "should_trigger": true },
{ "query": "what does the CFO need to see in an ad before approving a six-figure software purchase, vs what the daily user needs", "should_trigger": true },
{ "query": "we sell to schools - superintendent, principal, IT director all weigh in. How do we split the ad messaging?", "should_trigger": true },
{ "query": "sequence ads to different committee members across the buying journey for our cybersecurity platform", "should_trigger": true },
{ "query": "my ACV is $8k - do I even need to worry about a buying committee in my ads?", "should_trigger": true },
{ "query": "targeting the economic buyer on paid social without wasting spend on everyone else", "should_trigger": true },
{ "query": "couples shopping for kitchen remodels - who do we aim ads at and with what message", "should_trigger": true },
{ "query": "roles and messaging matrix for our enterprise ABM ads, deal size $250k", "should_trigger": true },
{ "query": "Build our layered ad audience plan - cold, lookalike, retargeting tiers with budgets per tier", "should_trigger": false },
{ "query": "Which customers should we upload as the seed list for a lookalike audience?", "should_trigger": false },
{ "query": "Design a retargeting sequence for cart abandoners with frequency caps", "should_trigger": false },
{ "query": "Write 10 headline variants for our LinkedIn ads targeting CFOs", "should_trigger": false },
{ "query": "We want to promote our CEO's LinkedIn posts as paid ads - set up the campaign", "should_trigger": false },
{ "query": "Our CPA doubled last month and I don't know why - audit the ad account", "should_trigger": false },
{ "query": "Is a 3.2 ROAS good for B2B SaaS? What CAC can we afford?", "should_trigger": false },
{ "query": "Should we advertise on LinkedIn or Google Ads with our $20k budget?", "should_trigger": false },
{ "query": "How do I split $50k a month across our search, social, and retargeting campaigns?", "should_trigger": false },
{ "query": "Write a creative brief our designer can execute for the new brand campaign", "should_trigger": false },
{ "query": "Find micro-influencers to promote our skincare brand", "should_trigger": false },
{ "query": "How much should we pay an Instagram influencer for a sponsored post?", "should_trigger": false },
{ "query": "Map the org chart at this account so our AE knows who to call about the open deal", "should_trigger": false },
{ "query": "Build a battlecard on who our main competitor sells to and how they position", "should_trigger": false },
{ "query": "Which conversion events should fire before we launch the campaign?", "should_trigger": false },
{ "query": "Our ad platform reports 300 conversions but the CRM shows 90 - reconcile the gap", "should_trigger": false },
{ "query": "Define our ICP - firmographics, company size, industry filters", "should_trigger": false },
{ "query": "Write cold email sequences for the different personas at our target accounts", "should_trigger": false },
{ "query": "Score which of these five video hooks deserves test budget", "should_trigger": false },
{ "query": "Our ad sets are stuck in learning limited - should we consolidate campaigns?", "should_trigger": false },
{ "query": "Set our maximum allowable CAC and a kill-switch threshold for paid spend", "should_trigger": false },
{ "query": "When can we scale the winning campaign from $5k to $20k a month?", "should_trigger": false },
{ "query": "Build a negative keyword list from this search terms report", "should_trigger": false },
{ "query": "Which ad format should we use for a brand awareness push - carousel or video?", "should_trigger": false },
{ "query": "Write a UGC script for a customer testimonial ad", "should_trigger": false },
{ "query": "Plan the A/B test cells and budget for our new creative batch", "should_trigger": false },
{ "query": "The landing page gets clicks but no conversions - audit it", "should_trigger": false },
{ "query": "Track whether we're on pace to spend our Q4 media budget", "should_trigger": false },
{ "query": "Should we pick target CPA or maximize conversions for the new campaign?", "should_trigger": false },
{ "query": "What ads are our competitors running right now - build a swipe file", "should_trigger": false },
{ "query": "How do I get hired as a media buyer at an agency?", "should_trigger": false },
{ "query": "Interview questions for hiring our first performance marketer", "should_trigger": false },
{ "query": "Which PPC newsletters and podcasts should I follow to stay current?", "should_trigger": false },
{ "query": "Create buyer personas for our website messaging and brand voice", "should_trigger": false },
{ "query": "Who at our company should approve ad spend increases?", "should_trigger": false },
{ "query": "Segment our email list by job title for the newsletter", "should_trigger": false },
{ "query": "Help me respond to an RFP from a hospital procurement team", "should_trigger": false },
{ "query": "Build lead scoring rules so sales knows which contacts to call first", "should_trigger": false },
{ "query": "My champion at the account went silent - draft a re-engagement email", "should_trigger": false },
{ "query": "Set up sponsored answers inside AI chat assistants for our product", "should_trigger": false }
]
}
references/worked-example.md›
# Worked Examples
Filled-in outputs in the shape defined by SKILL.md's Output shape section, plus starter per-role patterns. All angles below are illustrations of the method, not benchmarks - verify every pattern against the user's own closed-won data, call notes, and reviews before use.
## Starter per-role patterns (defaults to verify)
Practitioner-claimed defaults, not controlled evidence. Use them to seed the map when the user's own evidence is thin, and mark every row built from them as `hypothesis`.
Read the `Proof / offer type` column against the offer-type ranking in SKILL.md § Per-role output: this table says which offer fits a role, that ranking says which one to build first when you cannot build them all.
| Role | Measured on | Personal risk | Proof / offer type that fits |
| ------------------- | ---------------------------------------------------------- | --------------------------------------------------------------- | ----------------------------------------------------------------------- |
| Champion | The pain metric the offer fixes | Sponsored a failed project; spent political capital for nothing | Comparison guides, business-case builders they can circulate internally |
| End user | Daily throughput / quality of their own work | Forced onto a tool that makes their job worse | Demo, free trial, hands-on content - no sales gate |
| Economic buyer | Budget efficiency, ROI of the line item | Approved spend that produced no return; CFO scrutiny | ROI calculators, benchmark reports, customer proof with numbers |
| Technical evaluator | System reliability, integration cost | Owning the integration when it breaks | Technical docs, architecture pages, security whitepapers |
| Gatekeeper-blocker | Risk avoided: breaches, compliance findings, bad contracts | Being the one who signed off before an incident | Compliance certifications, audit reports, security documentation |
## Example 1 - B2B, per-role map justified
**Input:** compliance-automation SaaS, $85K ACV, selling to mid-market fintech (200-1,000 employees), ~350 named target accounts, closed-won notes from 22 deals available, professional network + broad social, $18K/month.
**Committee summary.**
- Committee size: closed-won notes show a median of 4 distinct roles per deal (range 3-6), consistent with the TrustRadius mid-market band, well under the "6 to 10" complex-purchase figure.
- Purchase type: mostly net-new category.
- Precision verdict: 350 named accounts and $85K ACV clear both thresholds (<500 accounts, approaching $100K ACV); per-role creative is defensible.
- Trade-off declared: this map takes the precision side, since the 95-5 objection applies less when reach is already bounded at 350 accounts.
**Role map.**
| Role | Evidence | Measured on | Personal risk | Likely objection | Messaging angle | Proof/offer | Targeting proxy | Proxy size vs. floor |
| ----------------------------------------- | ---------------------------------------------------------------------------------------- | -------------------------------------------- | ----------------------------------------------------------- | -------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Champion (Head of Compliance) | Evidenced - present in 22/22 won deals | Findings closed per audit cycle | Sponsoring a tool that fails the next audit | "We already handle this in spreadsheets" | "Your next audit prep in days, not quarters - without adding headcount" (verbatim from 3 call notes: "audit prep eats my quarter") | Audit-readiness checklist, ungated | Account list + function: Legal & Compliance, seniority: Director+ | ~2,100 - below practical floor; acceptable only because account-list ABM campaigns run on engagement objectives, flagged for mbfinotti/advertising-skills@ad-audience-targeting |
| Economic buyer (CFO / VP Finance) | Evidenced - 18/22 won deals show finance sign-off | Cost of compliance program vs. fine exposure | Approving a five-figure line that duplicates existing spend | "What does this replace?" | "One line item that retires three tools and caps fine exposure" | ROI model comparing tool consolidation + penalty avoidance | Account list + function: Finance, seniority: VP+ | ~1,400 - same flag as above |
| Technical evaluator (Head of Engineering) | Hypothesis - appears in 9/22 notes; disproof: cut if absent from next 10 wins | Integration and maintenance load | Owning a brittle integration | "Another vendor API to babysit" | "Read-only connectors, no schema changes, sandboxed in an afternoon" | Architecture doc + sandbox access | Account list + functions: Engineering AND Information Technology (cross-functional role straddles both), seniority: Director+ | ~3,800 |
| Gatekeeper (Security review) | Evidenced - validation-stage security review in 14/22 notes, reopened requirements twice | Vendor risk accepted on their signature | "New vendor, new attack surface" | "The vendor assessment is pre-filled - SOC 2 Type II, pen-test report, DPA on request" | Security documentation pack, ungated | Same account list + function: Information Technology, seniority: Manager+, reached from supplier-selection stage onward - before validation | ~2,900 |
**Sequencing notes.**
- Champion and end users (merged into champion here, same people in this segment per call notes): problem identification.
- Economic buyer: business-case content engagement.
- Security pack: delivered during supplier selection, not validation, because two deals stalled when security arrived late.
- Economic-buyer and gatekeeper angles weight risk reduction over urgency: 15/22 lost-deal notes cite "decided to wait", matching the indecision pattern.
**Handoffs.** Audience construction, floors resolution, and budget: mbfinotti/advertising-skills@ad-audience-targeting. Copy per angle: mbfinotti/advertising-skills@ad-copy-variants.
## Example 2 - multi-decider household purchase
**Input:** residential solar installation, $22K average ticket, metro region, no platform decided, review mining of 180 installer reviews available.
**Committee summary.**
- Household type: two-decider (typically both partners), occasional third voice (adult child or contractor friend advising).
- Purchase characteristics: high-consideration, personal money, no formal review stages.
- Precision verdict: household-graph isolation is imprecise; run role-differentiated creative on one shared household audience instead of trying to target each member.
**Role map.**
| Role | Evidence | Measured on (cares about) | Personal risk | Likely objection | Messaging angle | Proof/offer | Targeting proxy |
| -------------------------------- | --------------------------------------------------------------------------------------------------------------- | ------------------------------------------------ | --------------------------------------------------- | --------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------- |
| Initiator-researcher (partner A) | Evidenced - 130/180 reviews name one partner as the researcher | Monthly bill reduction, doing the homework right | Championing a purchase the household regrets | "Payback math never works out" | "See your actual payback year from your last three bills" (verbatim review language: "the calculator matched our real bills") | Bill-based savings calculator, ungated | Geo + homeowner signals + category in-market behavior; retargeting pool from calculator use |
| Co-decider (partner B) | Evidenced - reviews repeatedly cite "my wife/husband was worried about..." | Not being locked into a bad contract | "20-year contract with a company that might vanish" | "Rated installers, transferable warranty, no lien on the house" | Warranty terms one-pager, third-party review scores | Same household audience - connected-TV and shared-device placements carry the risk-reduction creative to the second decider |
| User (whole household) | Hypothesis - reviews rarely mention post-install experience; disproof: cut if next review pass confirms silence | Nothing changes day-to-day | (none - merged into co-decider's risk frame) | - | - | - |
The user row is cut at the structural pass: no evidence, and its concerns are absorbed by the co-decider. Final map: two roles, two creative variants, one shared audience.
## Negative example - what not to ship
**Input:** $6K ACV email-deliverability tool, SMB buyers, no closed-won analysis, professional network, $3K/month.
**The bad map:** eight roles (CEO, CMO, VP Marketing, Marketing Ops, IT, Procurement, Legal, "Influencers") copied from a committee framework, each with its own campaign at ~$375/month, titles targeted exactly ("Director of Email Marketing"), each audience 800-3,000 people.
Why it fails every gate:
- No evidence: all eight roles are title-based inference - the weakest source - asserted, not hypothesized, with no disproof tests. TrustRadius's SMB band (2-3 people) and the ACV both predict a two-role committee.
- "Influencers" is not a role: it maps to no attribute and no angle.
- Every audience is below the ~5,000 significance floor and the 20,000-50,000 practical floor; $375/month cannot fund a learning phase anywhere.
- Exact-title targeting misses every variant of "Director of Email Marketing" the platform doesn't recognize.
- Procurement and legal do not exist as stages in a $6K self-serve purchase - they were imported from an enterprise framework, not from evidence.
- The precision thresholds point the other way: neither <500 named accounts nor >$100K ACV - one strong message to a broad marketing-function audience wins on economics.
**The fix:** two roles: champion-user in marketing, and economic buyer only as a proof point in the creative, not a separate audience. One consolidated campaign, function + seniority targeting, and a disproof test on the economic buyer ("add a finance-facing variant only if call notes show finance blocking deals").
SKILL.md›
---
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 > published research > intent data > title inference
- effort: buyer interviews > intent data > closed-won/lost diff > review mining > call notes == published research > title inference
- compliance cost: intent data > buyer interviews > all others == none
- Effort in orders of magnitude:
- Buyer interviews: a week of scheduling across roles.
- Intent data: a standing job to configure and re-tune topics.
- Closed-won/lost diff: a day per deal-size segment.
- Review mining: a few hours.
- Call notes or published research: an hour to read what already exists.
- Title inference: near-zero.
- Call notes and published research tie on effort because both are an hour of reading a document someone else already produced; neither buys any new collection. They do not tie on value - notes are about your buyers, the bands are about somebody else's.
- Act on the two places the axes disagree. Call notes carry nearly the value of buyer interviews at a fraction of the effort, because the recordings already exist. Intent data sits high on effort and low on value here, because it resolves to accounts and so never confirms a role.
- Compliance cost, where it applies. A third-party intent feed needs a licensing and privacy review before first use, and its terms constrain re-use once the data is inside your targeting stack. Recorded interviews need per-participant recording consent, and a call recorded without it cannot be cited as evidence later.
- Default rung: diff which roles appear in won deals against lost deals, filling gaps from call notes that already exist - the strongest derivation available to most teams. Move up to buyer interviews when the diff leaves a role's presence ambiguous across segments; add intent data only when the unknown is which accounts to cover, never which roles exist.
- What the efficiency order starves: buyer interviews, second on value and first on effort, lose every round to sources that already exist. Promote them the moment a role's presence stays ambiguous after the diff and the notes - that ambiguity is the one thing no existing document can resolve.
- Re-rank this order against the user: clean CRM stage history makes the diff near-free, no CRM hygiene drops it below review mining, an in-house research function makes interviews cheap, and an already-licensed intent feed makes intent near-zero effort.
- Delete, don't demote: a team that cannot obtain per-participant recording consent deletes buyer interviews from the menu and says so in the output; a team with no licensing route for third-party intent deletes intent data. A ruled-out source parked at the bottom of the ladder reappears later as scope nobody budgeted.
- Title inference is the only free source and the weakest one - it is the floor of the ladder, never a rung to stop on.
- Never invent an org chart from a title. Classify a role from seniority plus how close its function sits to the product category - nothing else. When title and department contradict each other, output "unknown", not a guess.
- A role with no evidence survives only as a labelled hypothesis with a stated disproof test (e.g. "cut security review if it appears in none of the next ten closed-won notes"). A role with no evidence and no disproof test gets cut.
- Apply the working test from persona research: if a role changes no targeting, creative, or offer decision, delete it. Roles that survive because they sound plausible are liabilities, not audiences.
## Committee sizing
Derive committee size from the user's own closed-won data first. Published figures are a sanity band only - primary studies disagree by a factor of two because each defines "involved" differently and samples different deal sizes.
| Source | Size | Qualifier to keep attached |
| ------------------------------- | ---------------------------------------------------------- | --------------------------------------------------------------------------- |
| Gartner | 6-10 decision makers | complex solutions only - the qualifier is almost always dropped in citation |
| TrustRadius 2024 (2,164 buyers) | 96% of groups have ≤5; SMB peaks at 2-3, enterprise at 4-5 | tech purchases, self-report |
| 6sense | ~10.6 (North America) | behaviorally captured active participants |
| Forrester 2024 (>16,000 buyers) | 13 internal stakeholders | broadest definition of "involved" |
- Do not rank these four sources against each other: they sample different populations under different definitions of "involved", so any ordering would read as a quality ranking the disagreement does not support. Use them as a band and let the user's own closed-won data pick the number inside it.
- Seniority rises with deal size: 79% of purchases require CFO approval; 52% of groups include VP+ and 53% a C-suite executive (TrustRadius 2024).
- No primary study segments committee composition by industry or by purchase type (net-new vs. replacement vs. expansion). Say "no published data" instead of extrapolating.
- Sanity check both directions: a $6K ACV offer whose closed-won notes show two people does not get an eight-role matrix; a $500K enterprise deal mapped as champion-only is equally wrong.
## Role model
Use this six-slot vocabulary and define it inline in the output - no canonical role list exists, and the frameworks in circulation genuinely disagree.
| Role | Definition | Typically arrives at |
| ------------------- | ------------------------------------------------------------------------ | ----------------------------------- |
| Initiator | Surfaces the problem and starts the search | problem identification |
| Champion | Feels the pain, drives the evaluation, spends political capital publicly | problem identification → throughout |
| End user | Hands-on daily; judges impact on their own job | problem identification |
| Economic buyer | Owns the budget line; can approve or veto the spend | business-case stage |
| Technical evaluator | Screens against specs and architecture; veto power, no approval power | requirements building |
| Gatekeeper-blocker | Procurement, security, legal, compliance - substantive veto holders | validation |
Vocabulary flags to carry into the output:
- Champion, mobilizer, and coach are not synonyms:
- Coach: feeds intelligence, may stay hidden.
- Champion: advocates publicly.
- Mobilizer: coined because traditional champions are often friendly contacts who cannot drive consensus.
- When evidence shows your champion can't move the group, the map needs a consensus-driver, not a louder champion.
- "Gatekeeper" has two meanings: the classic administrative information filter, and the modern procurement/security/compliance functions holding substantive vetoes. This skill means the second; say which you mean.
- Never use "influencer" as a role label. It covers anyone whose opinion is sought, so it yields no targeting attribute and no messaging angle.
- Merge slots freely downward: SMB committees of 2-3 typically collapse to champion-who-is-the-user plus economic buyer. Do not fill empty slots for completeness.
## Per-role output
For each surviving role, fill all six fields - the angle is the deliverable; the first three are its inputs, and the proxy is what makes it operational:
| Field | Answers |
| ------------------ | ------------------------------------------------------------------------------ |
| Measured on | What number or outcome is this role's job judged by? |
| Personal risk | What happens to them if this purchase goes wrong? |
| Likely objection | The first reason they'd say no, in their own words |
| Messaging angle | The one framing that connects the offer to their metric and defuses their risk |
| Proof / offer type | Evidence format and CTA weight this role will accept |
| Targeting proxy | The platform attribute combination that actually reaches this person |
- Fine-grained per-role objection maps are weakly evidenced in published research - seniority-level content behavior is well evidenced, per-role objections mostly are not. Treat the starter patterns in [references/worked-example.md](references/worked-example.md) as defaults to verify against the user's own call notes and reviews, not as facts.
Offer types are a menu, and its axes disagree sharply - the cheapest asset to produce is not the one to build first:
- efficiency: compliance/security pack > ROI or savings calculator > ungated guide or checklist > demo or trial request > sandbox access > benchmark report
- value: demo or trial request > sandbox access > ROI or savings calculator > compliance/security pack > benchmark report > ungated guide or checklist
- effort: benchmark report > sandbox access > ROI or savings calculator > demo or trial request > compliance/security pack > ungated guide or checklist
- compliance cost: compliance/security pack > sandbox access > all others == none
- Effort in orders of magnitude:
- Benchmark report: a quarter to collect data nobody else holds.
- Sandbox access: a quarter of engineering.
- ROI or savings calculator: a week to build.
- Demo or trial request: a standing job, since each one spends sales capacity again.
- Compliance/security pack: an hour to assemble from certifications already held, a quarter if none exist.
- Ungated guide or checklist: near-zero.
- The pack leads because it is nearly free when the certifications exist and it is the only asset that removes a validation-stage veto - the highest-value outcome any single offer buys in this map.
- The demo does not lead despite the best per-person value: match offer friction to role warmth, because low-friction offers (guides, calculators, benchmarks) convert around 10-15% and high-friction offers (cold demo or trial requests) around 1.5-4%. Cold gatekeepers do not book demos at all.
- Compliance cost, where it applies: publishing a pen-test report or audit letter ungated needs security and legal sign-off, and a document published ungated cannot be recalled; a sandbox touching real data pulls in a data-processing review.
- Default rung per role: the ungated low-friction offer. Move up one rung once a role's proxy audience engages twice, never on the first touch.
- Re-rank against what the user owns: an existing SOC 2 pack promotes the compliance rung, and a proprietary data set already in hand promotes the benchmark report from last to first.
- Delete, don't demote: with no sales capacity to staff them, demos and trials leave the menu entirely - say "deleted: no sales capacity" rather than ranking them last, where they read as a stretch goal and quietly become one. Same for the sandbox with no engineering quarter to spend, and for the benchmark report when no proprietary data exists.
- Write angles in verbatim customer language wherever review mining or call notes supply it - exact phrases beat polished descriptions because they are how the buyer actually thinks.
- Every angle must be distinct. Run the swap test: if a role's angle could run unchanged against another role, rewrite one or merge the roles.
## Platform reality
A role list is worthless if no targeting attribute reaches it. Choose the proxy by efficiency - mapped roles reached per hour of setup - then check it against the floors below:
- efficiency: account list + function + seniority > function + seniority alone > intent-ranked account list + function + seniority > exact job title
- value: intent-ranked account list + function + seniority > account list + function + seniority > function + seniority alone > exact job title
- effort: intent-ranked account list > account list > exact job title > function + seniority
- compliance cost: intent-ranked account list > account list > all others == none
- Effort in orders of magnitude:
- Intent-ranked account list: a standing job to configure and re-tune topics.
- Account list: a week to build, then continuous maintenance.
- Exact job title: a day enumerating variants, and you still miss the ones the platform never learned.
- Function + seniority: an hour.
- Compliance cost, where it applies: uploading a matched audience triggers a data-processing review and the platform's own matched-audience policy, and a list does not unwind from the platform once matched; a licensed intent feed layers its own re-use restrictions on top.
- Default rung: account list + function + seniority whenever the addressable market is small enough to enumerate; fall back to function + seniority alone when it is not. Move up to intent ranking only when the list is larger than the budget can cover.
- Re-rank against what the user owns: an account list already built and maintained makes the top rung near-free, and a licensed intent feed already in the stack moves intent ranking up two places.
- Delete, don't demote: in a market of tens of thousands of accounts, both list-based rungs leave the menu. Name them deleted and plan on function + seniority, instead of leaving a list the team will never finish sitting at the bottom of the order.
- Exact-title targeting ranks worst on every axis: more setup effort than function + seniority for less reach, and it survives only where no function cell exists for the role. Platforms understand roughly 30-50% of job titles, each variant you didn't list is missed, and function + seniority roughly triples the addressable audience at similar engagement. On professional networks, title and seniority targeting are mutually exclusive: they cannot be stacked.
- Professional networks assign each person exactly one job function - a "Marketing Operations Manager" lands in Marketing or Operations, never both. Cross-functional roles, precisely the ones committees care about, straddle cells; expect to target two functions to cover one role.
- Function and seniority derive from self-reported profiles with no inference, so they inherit every stale and inflated title on the platform.
- Audience floors gate everything: the technical floor for matched audiences is around 300 members (about 1,000 for consumer-keyed matches), but the practitioner floor is 20,000-50,000 for typical budgets - below ~5,000 results rarely reach significance, and stacking AND conditions below ~50,000 degrades delivery. State the floor before splitting roles, not after.
- Intent data resolves to accounts, not people, at roughly 81% account-level accuracy - about one in five surging accounts has no genuine near-term intent, and narrow, well-configured topics reach only 60-70%. It ranks which accounts to cover, never who is inside them; a surge is never a committee member.
- An account list is an account signal, not familiarity - every individual on it is still cold from a messaging standpoint.
- Gate committee-wide coverage on account-level intent or engagement: run full multi-role targeting against a mini account list distilled from inbound leads or surging accounts, not against a cold industry-wide list. Cold committee-wide coverage burns budget on stakeholders with no reason to care yet.
## Precision vs. reach: an unresolved dispute
Three postures buy committee coverage. Rank them, state which one the map takes and why, and never pretend the dispute behind them is settled.
- efficiency: merged map (one primary angle + role-aware proof points) > one strong broad message > full per-role campaigns
- value: full per-role campaigns > merged map > one strong broad message - but per-role value only materializes above the thresholds below; under them it inverts
- effort: full per-role campaigns > merged map > one strong broad message
- Effort in orders of magnitude:
- Per-role campaigns: a quarter, one creative set and one campaign per role, plus coordination across every role's reviewer.
- Merged map: a week, one campaign and a handful of proof variants.
- Single broad message: a week, then near-zero for each further role it happens to reach.
- What the efficiency order starves: per-role creative. It leads on value and leads on effort, so a ratio never selects it, and a skill that only computes efficiency will ship one generic asset against a six-role committee every single time. The two thresholds below exist to promote it anyway - say explicitly in the output which of them you tested and what the answer was, so the starved option gets refused on evidence rather than by default.
- **Against narrow role targeting:** the Ehrenberg-Bass 95-5 rule - roughly 95% of B2B buyers are out-market at any time - implies hyper-narrow targeting wastes exactly the reach that builds future mental availability. The proposed alternative is linking the brand to category entry points broadly.
- **For it, steelmanned:**
- In a market of a few hundred named accounts, reach is bounded anyway and precision becomes affordable.
- At high ACV, the economics support bespoke per-role creative even at inflated CPM.
- The 95-5 argument itself concedes the in-market 5% should get activation.
- **Thresholds that move the default:** per-role campaigns are defensible below roughly 500 named accounts or above roughly $100K ACV. Below those, ship the merged map to a 20,000-50,000 audience - one primary angle plus role-aware proof points, not six campaigns.
- **Flip check:** if CPM inflation and frequency on the narrow audiences are not degrading cost per opportunity, tightening further is justified.
- Re-rank against what the user owns: an in-house creative team promotes per-role campaigns by cutting their effort, and a brand with no existing reach promotes the broad message, because a committee that has never heard of you converts on nothing.
- Delete, don't demote: one generalist marketer producing everything alone cannot run six campaigns whatever the thresholds say - delete per-role campaigns from that user's menu by name, and spend the role map on proof variants inside the merged map instead. Ranked last, they return in three months as an unfunded plan.
- Nobody has resolved this: no controlled test compares role-differentiated creative against a single strong message in matched programs, so the ordering above is an argued default, not a measured one.
## Sequencing: which role matters when
- The journey loops through six buying jobs, and 90% of buyers revisit at least one. Do not map roles to a linear funnel. The six jobs:
- Problem identification.
- Solution exploration.
- Requirements building.
- Supplier selection.
- Validation.
- Consensus creation.
- Arrival order:
- End users and the initiator: surface at problem identification.
- The economic buyer: engages with the business case (79% of purchases need CFO approval).
- Security, legal, and procurement: arrive at validation, and a security reviewer added late can reopen requirements and reset agreed work.
- Reaching validation-stage roles _before_ validation is the cheapest insurance in the map.
- About 70% of the journey completes before any seller contact, 81-84% of deals go to the first vendor contacted, and fewer than 30% of eventual buyers ever fill out a form on the winning vendor's site. Committee reach therefore cannot be gated on form fills - ungated, role-relevant content and paid reach carry the pre-contact phase.
- No-decision is the real competitor: 40-60% of deals end in no-decision, and 56% of those are lost to indecision (fear of messing up) rather than status-quo preference. Amplifying urgency backfires on indecision - for economic buyers and gatekeepers especially, weight angles toward risk reduction and proof, not pressure.
## Multi-decider consumer purchases
The role vocabulary transfers. The consumer five-role model descends directly from the same organizational buying-center research. Its five roles:
- Initiator.
- Influencer.
- Decider.
- Buyer.
- User.
What genuinely carries over:
- The user often isn't the person approving the spend.
- Each decider needs a different message.
- One unconvinced member can veto the purchase.
What does not transfer:
- No procurement, legal, or security review.
- No career risk: the fear of a bad call is personal and financial, never professional.
- Personal money, not company money.
- Emotional and relational dynamics dominate over functional-role conflict.
- The unit pre-exists the purchase.
- The process runs on reviews and peers, not RFPs.
Apply this model only to high-consideration categories with a genuine second decider - vehicles, home improvement, family travel, insurance, private education, major appliances. Routine purchases have one decider, and this whole skill is overhead. Household-level targeting (connected-TV household graphs, shared devices) is real but imprecise and unquantified: prefer role-differentiated creative shown to a shared household audience over trying to isolate each member.
## Output shape
Deliver the map as one document:
1. Committee summary: estimated size with its evidence source, purchase type, the precision-vs-reach posture chosen with the thresholds applied, which interview answer moved any ranking off its default, and a named list of every option a stated constraint deleted from a menu.
2. Role map table, one row per surviving role: role | evidence (source + status: evidenced / hypothesis + disproof test) | measured on | personal risk | likely objection | messaging angle | proof/offer type | targeting proxy | estimated proxy audience vs. floor.
3. Sequencing notes: which roles to reach at which buying job, and where risk-reduction messaging replaces urgency.
4. Handoffs: which neighboring skill takes each next step (see References).
Short invocation examples: "Map the buying committee for our $80K ACV compliance platform selling to mid-market fintech" or "Who else decides when a family buys solar panels, and what do we say to each?"
See [references/worked-example.md](references/worked-example.md) for a filled-in B2B map, a household example, and a negative example.
## Failure modes
- Asserting the committee instead of hypothesizing it: every role ships with an evidence status or it doesn't ship.
- Inventing an org chart from a title: classify from seniority + functional distance; output "unknown" on contradiction.
- Over-splitting into per-role audiences below platform floors: merge roles whose proxies collide or undershoot.
- Filter stacking on generic creative: a narrow audience all seeing one unchanged ad is worse than a broad audience seeing role variants. Rich role knowledge should buy creative variants first, filters second.
- Running committee-wide targeting cold: gate it on account-level intent.
- Treating an account list as a warm audience: list membership is an account signal; the person is still cold.
- Letting the segment map impersonate a deal map: segment-level role patterns never substitute for evidence-graded work on named contacts in one live deal.
- Quoting "6 to 10 decision makers" as universal: it describes complex purchases only, and primary studies disagree by 2x.
- Keeping decorative roles: a role that changes no targeting, creative, or offer decision gets deleted.
## Objective and measurement
- Structural pass (before handoff): every surviving role has (a) an evidence source or a labelled hypothesis with a disproof test, (b) a targeting proxy whose estimated audience clears the practical floor, and (c) an angle that survives the swap test against every other role. Merge roles failing (b), cut roles failing (a), rewrite angles failing (c). Iterate until 100% of surviving roles pass all three - do not hand off a map that fails structurally.
- Outcome KPIs (after campaigns run, read with mbfinotti/advertising-skills@ad-audience-targeting's measurement):
- Account penetration: distinct roles reached per target account vs. the map's role count.
- Per-role engagement spread: a role whose proxy audience never engages is evidence against the hypothesis, so revisit its disproof test.
- Downstream opportunity or meeting rate: on accounts where 2+ mapped roles were reached vs. one.
- Caveat to state in the map: per-role creative outperforming a single strong message is not proven by controlled evidence. The map is a testable structure, not a guaranteed lift - the KPIs above are how the user finds out which side of the precision-vs-reach dispute their market is on.
## References
- mbfinotti/advertising-skills@ad-audience-targeting - audience tiers, sizing, budgets, and test sequencing.
- mbfinotti/advertising-skills@lookalike-audience-seeds - seed list selection.
- mbfinotti/advertising-skills@retargeting-funnel - retargeting sequence design.
- mbfinotti/advertising-skills@ad-copy-variants - ad copy variants per angle.