kenny589/gtm-flywheel/icp-matrix-builder

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Build comprehensive Ideal Customer Profile matrices that define exactly who to target. Tiering frameworks, scoring models, and segmentation strategies for precision outbound.

Install

npx vskill@latest install kenny589/gtm-flywheel/icp-matrix-builder

SKILL.md

ICP Matrix Builder

When to Use

  • Launching outbound for a new company or product line
  • Refining targeting after initial campaign data comes in
  • Expanding into new verticals or market segments
  • Building the foundation for any lead generation or ABM campaign

Framework

What an ICP Matrix Is (And Isn't)

An ICP Matrix is a structured scoring document that ranks and segments your ideal buyers across multiple dimensions. It's the bridge between "we sell to B2B companies" and "we target Series B SaaS companies with 100-500 employees who just hired their first VP of Sales."

It IS:

  • A living document that evolves with campaign data
  • A scoring framework that makes targeting decisions objective
  • A segmentation tool that enables personalized outreach at scale

It is NOT:

  • A one-time exercise you do during onboarding and forget
  • A single persona description
  • A firmographic filter (company size + industry alone is not an ICP)

The 5 Dimensions of an ICP Matrix

Every complete ICP Matrix scores prospects across five dimensions:

Dimension 1: Firmographic Fit

Does the company match your ideal customer profile structurally?

AttributeTier 1 (Best)Tier 2 (Good)Tier 3 (Acceptable)Disqualified
Company sizeDefine rangeDefine rangeDefine rangeToo small/large
RevenueDefine rangeDefine rangeDefine rangeOutside range
IndustryPrimary verticalsAdjacent verticalsEmerging fitNo fit
GeographyPrimary marketsSecondary marketsExpansion marketsRestricted
Business modelExact matchSimilarAdaptableIncompatible
Growth stageIdeal stageAdjacent stagesPossible fitWrong stage

How to fill this in:

  1. Start with your best 10 customers — what do they have in common?
  2. Look at your worst 10 customers — what disqualified them (in hindsight)?
  3. The patterns that appear in your best but NOT your worst = your Tier 1 criteria
Dimension 2: Technographic Fit

Does their tech stack indicate they're a good fit?

AttributeSignal StrengthWhy It Matters
Uses your integration partnersStrongLower friction to adopt
Uses a competitorStrongActive buyer, proven budget
Tech stack complexity matchesMediumRight sophistication level
Recently adopted adjacent toolsMediumActive buying cycle
No relevant tech stackWeakMay not understand the category
Dimension 3: Buying Intent Signals

Is this company likely to be in-market right now?

SignalIntent LevelScoring Weight
Hiring for the role your product servesVery High5x
Recent funding roundHigh4x
Competitor evaluation (G2, review sites)Very High5x
Content consumption (webinars, guides)Medium-High3x
Website visits (if tracking available)High4x
Leadership change in relevant deptMedium2x
No detectable intentLow1x
Dimension 4: Persona Mapping

Who within the company should you target?

For each ICP tier, define 2-3 target personas:

Persona AttributeWhat to Define
Title patternsVP Sales, Director of Revenue, Head of Growth (include variants)
DepartmentSales, Marketing, RevOps, Growth
Seniority levelC-Suite, VP, Director, Manager
Decision roleEconomic buyer, Champion, Influencer, Blocker
Pain points3-5 specific, measurable pains this persona faces
Buying triggersWhat events push them to evaluate solutions
Success metricsWhat KPIs they're measured on
Common objectionsTop 3-5 reasons they say no
Dimension 5: Engagement Readiness

How likely is this company to respond to outbound?

FactorHigh ReadinessLow Readiness
Previous interactionsEngaged before (event, content, trial)Cold — no prior touchpoint
Outbound receptivenessSMB/mid-market, growth-stageEnterprise, heavily gatekept
Channel preferenceActive on LinkedIn, responsive to emailDark social, unreachable online
Sales cycle length< 60 days6+ months
Committee size1-3 decision makers5+ stakeholders

The Tiering Framework

After scoring all five dimensions, segment accounts into tiers:

TierCriteriaOutreach StrategyVolume
Tier 1: Bullseye4-5 dimensions score "Strong"Hyper-personalized, multi-channel, 8+ touches5-10% of list
Tier 2: Strong Fit3-4 dimensions score "Strong"Signal-based personalization, email-first20-30% of list
Tier 3: Good Fit2-3 dimensions score "Strong"Bucket personalization, email-only40-50% of list
Tier 4: Stretch1-2 dimensions score "Strong"Test with small batch, generic angle10-20% of list
Disqualified0 dimensions score "Strong" OR has a DQ flagDo not contactRemove from list

Disqualification triggers (immediate removal regardless of other scores):

  • Company too small to have budget
  • Industry you can't serve
  • Already a customer
  • Competitor or partner (unless intentional)
  • Bad data (no valid email, wrong person)

Building the Matrix: 6-Step Process
Step 1: Analyze Your Best Customers

Pull your top 10-20 customers by: revenue, retention, NPS, speed-to-close, or expansion rate.

For each, document:

  • Firmographics (size, revenue, industry, geo)
  • What triggered them to buy
  • Who the champion was (title, seniority)
  • How long the sales cycle took
  • What their tech stack looked like at purchase
Step 2: Analyze Your Worst Customers

Pull 10-20 churned or low-value customers. Document the same attributes.

The gap between best and worst = your ICP definition.

Step 3: Identify Scoring Patterns

Look for attributes that appear in 70%+ of your best customers but less than 30% of your worst:

Best Customers Pattern Analysis:
- 80% were Series A-B stage → Weight: High
- 75% had 50-200 employees → Weight: High
- 70% were hiring SDRs when they bought → Weight: Very High
- 60% were in B2B SaaS → Weight: Medium-High
- 50% had a VP Sales title as buyer → Weight: Medium
Step 4: Build the Scoring Model

Assign point values to each attribute:

DimensionAttributeTier 1 PointsTier 2 PointsTier 3 Points
Firmographic50-200 employees1052
FirmographicB2B SaaS842
TechnographicUses Salesforce631
IntentHiring SDRs1052
IntentRecent funding842
PersonaVP Sales title631

Total possible: Sum of all Tier 1 points Tier thresholds: Tier 1 = 80%+, Tier 2 = 60-79%, Tier 3 = 40-59%, Below 40% = DQ

Step 5: Validate with Campaign Data

After running your first campaigns, compare:

  • Positive reply rate by ICP tier
  • Meeting rate by ICP tier
  • Close rate by ICP tier

If Tier 2 accounts are outperforming Tier 1, your scoring model needs adjustment. The data will tell you which attributes actually predict buying behavior vs. which ones you assumed would.

Step 6: Iterate Quarterly

Every quarter, re-run the analysis:

  • Which attributes correlated with closed deals?
  • Which new signals appeared in your best customers?
  • Has your product evolved to serve a different segment better?

Update the matrix. Adjust scoring weights. Re-tier your target accounts.


Multiple ICP Segments

Most companies have 2-4 distinct ICP segments. Each needs its own matrix:

ICP Segment Map:
├── Segment A: "Growth-Stage SaaS" (Primary)
│ ├── Company: 50-500 employees, Series A-C, B2B SaaS
│ ├── Buyer: VP Sales / Head of Growth
│ └── Trigger: Hiring SDRs or scaling outbound
│
├── Segment B: "Agency Scaling" (Secondary)
│ ├── Company: 10-50 employees, digital agency, $2M-$10M revenue
│ ├── Buyer: Founder / CEO
│ └── Trigger: Hit referral ceiling, need predictable pipeline
│
└── Segment C: "Enterprise RevOps" (Emerging)
├── Company: 500-5000 employees, tech or professional services
├── Buyer: Director of RevOps / VP Sales Operations
└── Trigger: Tech consolidation or efficiency mandate

Rule: Each segment gets its own campaigns, its own copy, and its own personalization strategy. Never blend segments in a single campaign.

Templates

ICP Matrix Template
# ICP Matrix: {{Company/Product Name}}
# Version: {{version}} | Last Updated: {{date}}
## Segment: {{segment_name}}
### Firmographic Profile
| Attribute | Tier 1 | Tier 2 | Tier 3 | DQ |
|-----------|--------|--------|--------|----|
| Company size | ___ | ___ | ___ | ___ |
| Revenue | ___ | ___ | ___ | ___ |
| Industry | ___ | ___ | ___ | ___ |
| Geography | ___ | ___ | ___ | ___ |
| Business model | ___ | ___ | ___ | ___ |
| Growth stage | ___ | ___ | ___ | ___ |
### Target Personas (Ranked by Priority)
| Rank | Title Pattern | Seniority | Decision Role | Key Pain |
|------|--------------|-----------|---------------|----------|
| P1 | ___ | ___ | ___ | ___ |
| P2 | ___ | ___ | ___ | ___ |
| P3 | ___ | ___ | ___ | ___ |
### Intent Signals (Ranked by Weight)
| Signal | Weight (1-5) | Detection Source |
|--------|-------------|-----------------|
| ___ | ___ | ___ |
| ___ | ___ | ___ |
| ___ | ___ | ___ |
### Scoring Thresholds
| Tier | Min Score | Outreach Strategy |
|------|-----------|-------------------|
| Tier 1 | ___ | ___ |
| Tier 2 | ___ | ___ |
| Tier 3 | ___ | ___ |
| DQ | Below ___ | Do not contact |
### Validation Metrics (Update Quarterly)
| Metric | Tier 1 | Tier 2 | Tier 3 |
|--------|--------|--------|--------|
| Positive reply rate | ___ | ___ | ___ |
| Meeting rate | ___ | ___ | ___ |
| Close rate | ___ | ___ | ___ |
| Avg deal size | ___ | ___ | ___ |

Tips

  • Your ICP is not who you CAN sell to — it's who you SHOULD sell to. The narrower your ICP, the higher your conversion rates.
  • Start with 1 segment, not 4. Validate one ICP completely before expanding to adjacent segments.
  • The #1 mistake in ICP development: using only firmographic data. A 100-person SaaS company that just raised Series B and is hiring 5 SDRs is a completely different prospect than a 100-person SaaS company that's been flat for 3 years. Same firmographics, wildly different intent.
  • Interview your sales team. They know which deals close fast and which are painful — that pattern recognition is your ICP definition.
  • If you don't have 10 customers to analyze yet, start with competitor customer analysis. Who are THEIR best customers? That's your starting ICP.
  • Update your matrix every time you close (or lose) a significant deal. What did you learn? Did it match your scoring model?

Progressive disclosure: load industry-specific ICP templates and scoring benchmarks only when building a matrix for a specific vertical.

Security

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Source

Popularity

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