icp-personas

name

icp-personas

description

Define the ICP, size and tier an ABM target-account list, and map the buying committee — the strategy layer before list-building and enrichment. Use when defining an Ideal Customer Profile and scoring criteria, deciding how many accounts to target for a revenue goal, tiering accounts (A/B/C/D), mapping personas/buying committee (champion, economic buyer, end user, technical evaluator), or planning persona-based messaging. Triggers on "ICP", "ideal customer profile", "who to target", "scoring criteria", "ABM accounts", "how many accounts", "account tiering", "buying committee", "persona mapping", "champion", "economic buyer", "revenue reverse-engineering". Do NOT use for actually sourcing companies/contacts (see apollo-search / coldiq-search-enrich), scoring math on an export (see tam-scoring), or writing copy (see crawford-method / cold-email-copy).

ICP, Accounts & Personas

The strategy layer: decide WHO to target, HOW MANY, and WHICH people inside each account — before you spend credits sourcing and enriching. Mostly methodology; a few steps source data from ColdIQ.

ColdIQ Marketplace Endpoints (where strategy touches data)

Task	Method	Path	Credits	Endpoint ID	Notes
Validate filter values (ICP criteria)	POST	/v1/limadata/references/autocomplete	free	limadata.references.autocomplete	Confirm titles/industries exist
Size the addressable market	POST	/v1/ai-ark/companies	per result	ai_ark.companies.search	How many fit the ICP
Layer intent for prioritization	GET	/v1/signalbase/funding-signals	unknown	signalbase.funding_signals	Bump in-market accounts
Map the buying committee	POST	/v1/limadata/prospect/employees	25	limadata.prospect.employees	Find personas at an account

1. Define the ICP (3 layers + scoring)

• Firmographic: industry, employee size, revenue, geography, growth, funding stage.
• Technographic: tech stack, CRM, marketing automation, competitor tools.
• Behavioral/intent: hiring, funding, leadership changes, content engagement, website visits.

Reverse-engineer from your best 10–20 closed-won customers. Score 100 pts (example weights): industry 20 · size 15 · revenue 15 · geography 10 · tech fit 15 · growth 10 · intent 15. Tiers: A 90–100 (1:1 ABM) · B 70–89 (1:few) · C 50–69 (programmatic) · D <50 (exclude).

Validate your criteria translate to real filter values before sizing: → POST /v1/limadata/references/autocomplete · free · limadata.references.autocomplete

(Hand the scoring rules to tam-scoring to run on an actual export.)

2. Size & select the account list (ABM)

Revenue reverse-engineering — work backward from the target through funnel benchmarks: Identified→Aware 55% · Aware→Interested 32% · Interested→Considering 18%. (e.g. $1M ARR target ≈ ~3,367 accounts identified.)

Check how many companies actually fit before committing: → POST /v1/ai-ark/companies · per result · ai_ark.companies.search

4-layer selection: firmographic fit · technographic indicators · CRM intelligence (closed-lost, lost-to-competitor, churned) · lookalike modeling from best customers. Then prioritize the in-market ones: → GET /v1/signalbase/funding-signals · ? cr · signalbase.funding_signals (unverified)

Track stage progression: Identified → Aware → Interested (5+ clicks / 10+ engagements) → Considering (site visits, content, demo interest).

3. Map the buying committee

Role	Function	Budget priority
Champion	Internal advocate driving evaluation	40–50%
Economic Buyer	Signs the check; cares about ROI	20–30%
End User	Daily user; cares about UX/workflow	15–20%
Technical Evaluator	Integration, security, compliance	5–10%
Blocker/Gatekeeper	Can veto, rarely initiates	monitor

For each persona capture: title patterns + seniority, function, jobs-to-be-done, pains, success metrics, content preference, buying role. Find the actual people once you've defined the personas: → POST /v1/limadata/prospect/employees · 25 cr · limadata.prospect.employees

Messaging matrix: per persona, different JTBD + pain + stage-appropriate content + role-appropriate CTA (champion → demo/ROI, end user → trial/ease-of-use). Hand off to crawford-method / cold-email-copy to write it.

Where this hands off

ICP scoring rules → tam-scoring · sourcing companies/contacts → apollo-search / coldiq-search-enrich · personas-into-ads → ad-audiences · the full build order → campaign-delivery.