icp-scoring

name	icp-scoring
description	You are prospecting B2B SaaS companies and need to qualify leads against a defined ideal customer profile (ICP). Trigger this when: scoring a new l...

ICP Scoring

When to activate

You are prospecting B2B SaaS companies and need to qualify leads against a defined ideal customer profile (ICP). Trigger this when: scoring a new lead for outreach tier, prioritizing a prospect list, deciding contact depth for a company, or validating fit before sales handoff.

When NOT to use

• You already have a lead inside a customer success/retention workflow — use churn prevention frameworks instead.
• Prospect is already a customer or active opportunity in your CRM — this is for new prospecting only.
• You are doing lead generation sourcing (finding which companies to prospect) — this is for qualifying companies you've already identified.
• The target company has fewer than 10 employees or is in a hardline disqualifying vertical — scoring is pointless; mark as do-not-contact.

Instructions

3-Layer ICP Definition

Every ICP is defined across three orthogonal dimensions. Score each independently, then combine.

Layer 1: Firmographic Fit (0–40 points)

Objective company attributes that determine structural ability to buy.

Attribute	Target	Points
Industry vertical	Primary (e.g., SaaS, FinTech, Healthcare Tech)	20
Secondary fit (adjacent, proven use case)	10
Wrong vertical (disqualifier)	0
Company headcount	50–500	15
25–49 or 501–1,000	8
10–24 or 1,001+	2
Under 10	0 (hard disqualifier)
Annual Recurring Revenue (ARR)	$5M–$100M	5
$2M–$4.9M or $100M–$500M	3
Under $2M or over $500M	0
Geography	US, UK, Canada, Western Europe (primary)	Included above; secondary markets score at 80%

Firmographic ceiling: 40 points. A company perfect on all attributes scores 40.

Layer 2: Technographic Fit (0–30 points)

Tech stack and infrastructure signals that indicate product fit or disqualification.

Score based on presence of signals (not absence). Check: public tech stacks (StackShare, LinkedIn, job posts, funding decks), GitHub public repos, job postings for tech roles, founding/funding announcements.

Signal Type	Examples	Points
Core fit (your solution directly plugs into their stack)	Using Node.js, PostgreSQL, Kubernetes; hiring "DevOps Engineer"; publicly discussing microservices	15
Secondary fit (strong adjacency)	Cloud infrastructure (AWS, GCP, Azure); CI/CD mentions; data pipeline investments	10
Weak signal (general modern tech, not specific to your ICP)	Standard SaaS stack (React, Python, typical AWS); no red flags but no strong fit either	5
Hard disqualifier	Locked into competitor tech stack; legacy mainframe-only; using completely incompatible vendor	0

Select the highest-scoring signal category found. Technographic ceiling: 30 points.

Layer 3: Behavioural Signals (0–20 points)

Recent momentum and growth signals indicating buying intent and budget allocation.

Signal	Recency	Points
Funding round (Series A or later, not seed)	Last 12 months	8
13–24 months ago	5
Over 24 months	2
Hiring surge (publicly posted 5+ role openings in your target department: engineering, data, product)	Last 30 days	8
31–90 days ago	5
Over 90 days	2
Expansion signals (new office, new product launch, new market entry, new integration ecosystem)	Last 90 days	4

Behavioural ceiling: 20 points. Multiple signals are additive up to 20.

Recency Decay (0–10 points bonus/penalty)

All firmographic data becomes stale. Adjust final score based on data freshness.

Data freshness	Adjustment
All ICP attributes verified in last 30 days	+10
Verified 31–90 days ago	+5
Verified 91–180 days ago	0
Over 180 days old (no recent verification)	–5

Example: A 75-point lead with 6-month-old company size data becomes 70 points.

Complete Scoring Model: 0–100

Formula:

SCORE = Firmographic (0–40) + Technographic (0–30) + Behavioural (0–20) + Recency (–5 to +10)
RANGE: 0–100

Hard Disqualifiers (Score = 0, skip all tiers)

Even if other dimensions score high, mark the lead do-not-contact if any apply:

1. Competitor — They build/sell a competing product.
2. Existing customer — Already in your customer base or active trial.
3. Wrong industry vertical — Outside your defined primary/secondary verticals (e.g., government contractor when you target SaaS).
4. Headcount under 10 — Too small to have buying process or budget.
5. Explicit disqualification signals — Public statements against your category; using incompatible vendor exclusively; bankruptcy/layoff announcements indicating budget freeze.

Tier Definitions & Action Playbooks

After scoring (and confirming no hard disqualifiers), route to outreach tier:

Tier 1 (80–100 points)

Characteristics: Perfect or near-perfect fit. ICP match on 2+ dimensions. Recent signals.

Outreach playbook:

• Manual deep research: Read last 3 earnings calls (if public), recent blog posts, CEO Twitter, LinkedIn hiring posts, recent funding announcement.
• Identify 2–3 specific, personalized hooks (e.g., "I noticed you posted 7 engineering roles last month; we help teams like yours reduce onboarding time by 40%").
• Personalized email sequence: 5-touch, 21-day cadence. Custom hook in email 1. Reference specific company milestone in email 3. Social touch (LinkedIn comment on recent post) as touch 4.
• Sales involvement: Assign to named account executive. Use full sales development playbook.

Response rate benchmark: 8–12% reply rate (with personalization).

Tier 2 (50–79 points)

Characteristics: Strong fit on 1 dimension, adequate fit on others. Clear ICP match but may lack recent momentum.

Outreach playbook:

• Template email with 1 personalization hook (e.g., "Your team hired 6 engineers last quarter; we help teams like [similar company] reduce [outcome]").
• Standard 3-touch sequence over 14 days: Email → 5-day wait → LinkedIn message → 3-day wait → Final email.
• No manual deep research; use public signals only (LinkedIn, StackShare, funding announcements).
• Light sales involvement: SDR only, no AE assignment.

Response rate benchmark: 4–6% reply rate.

Tier 3 (20–49 points)

Characteristics: Partial fit. Matches ICP on one dimension only, or weak signals across multiple dimensions.

Outreach playbook:

• Template email (no personalization). Single touch only.
• Batch-and-blast: Send in bulk campaigns. No follow-up sequence.
• Use for list-building and brand awareness, not direct sales.
• No sales involvement.

Response rate benchmark: 1–2% reply rate (expect low engagement).

Below 20 points

Action: Do not contact. Move to "nurture" segment for future campaigns only. Re-score quarterly.

---

Scoring Prompt Template

Use this prompt structure to score a lead with Claude:

Score this company against our ICP using the attached 0–100 model.

COMPANY: [Company name]
INDUSTRY: [Industry]
HEADCOUNT: [Number] (source: [LinkedIn/PitchBook/etc])
ARR: [Estimated or public $] (source: [how you know])
GEOGRAPHY: [Country/region]

TECH STACK SIGNALS:
- [Tool/platform 1] (source: [job post/StackShare/GitHub])
- [Tool/platform 2]
- [Tool/platform 3]

BEHAVIOURAL SIGNALS:
- Funding: [Series X, $Y, date] (source: [Crunchbase/press release])
- Hiring: [Number of open roles in target department, dates posted] (source: [LinkedIn jobs])
- Expansion: [New market/office/product launch] (source: [announcement])

DATA FRESHNESS: All data verified [date range]

TASK:
1. Score each dimension independently (Firmographic, Technographic, Behavioural, Recency).
2. Identify any hard disqualifiers.
3. Return: TOTAL SCORE, TIER, RECOMMENDATION (contact depth + sequence type).
4. List the top 2 personalization hooks (if Tier 1 or 2).

Format response as:
---
**SCORE: [0-100]**
**TIER: [1/2/3/Do Not Contact]**
**DISQUALIFIERS:** [None / List any found]
**FIRMOGRAPHIC:** [X points] — [reasoning]
**TECHNOGRAPHIC:** [X points] — [reasoning]
**BEHAVIOURAL:** [X points] — [reasoning]
**RECENCY ADJUSTMENT:** [+/- X points]

**TOP PERSONALIZATION HOOKS:**
1. [Hook 1 — specific, time-bound]
2. [Hook 2 — specific, time-bound]

**RECOMMENDATION:** [Outreach playbook and next step]
---

---

Example

Scenario: Score TechVentures Inc. (Hypothetical FinTech SaaS)

Raw data collected:

Attribute	Value	Source
Company	TechVentures Inc.	Crunchbase
Industry	FinTech (payment processing)	Website, LinkedIn
Headcount	180	LinkedIn Company Page (updated 2 weeks ago)
ARR	$18M	Crunchbase funding + burn calc
Geography	San Francisco, CA (US)	Company website
Tech stack	Python, PostgreSQL, AWS, Kubernetes, Node.js microservices	Job postings (Aug 2026), GitHub public repos
Funding	Series B, $45M, raised Mar 2026	Crunchbase, TechCrunch
Hiring	12 open Engineering roles (posted last 30 days)	LinkedIn jobs page
Expansion	Announced UK expansion (Jul 2025)	Company blog
Data verified	Jun 2026	This scoring session

Scoring:

FIRMOGRAPHIC (40 max):

• Industry fit (FinTech primary vertical): 20 points
• Headcount (180, in 50–500 range): 15 points
• ARR ($18M, in $5M–$100M range): 5 points
• Subtotal: 40 points ✓

TECHNOGRAPHIC (30 max):

• Core fit: PostgreSQL + Python microservices on AWS/Kubernetes matches modern SaaS infrastructure (15 points).
• No disqualifying signals.
• Subtotal: 15 points ✓

BEHAVIOURAL (20 max):

• Funding (Series B, $45M, Mar 2026 = 3 months ago): 8 points
• Hiring surge (12 Engineering roles, posted <30 days): 8 points
• Expansion (UK office announced, but 11+ months ago): 2 points
• Subtotal: 18 points ✓

RECENCY (±10):

• All data verified in last 30 days: +10 points

---

FINAL SCORE: 40 + 15 + 18 + 10 = 83 points

TIER: Tier 1 (80–100)

DISQUALIFIERS: None

RECOMMENDATION:

Outreach Playbook — Tier 1:

Personalization Hooks:

1. "You raised $45M in Series B (Mar 2026) and are hiring aggressively (12 engineering roles open). We help FinTech platforms scaling on AWS/Kubernetes reduce infrastructure complexity by 35%—directly relevant as you expand into UK and add headcount."
2. "You built on PostgreSQL + microservices, which is exactly where [our solution] provides the most value. Teams like Stripe and Wise use us to accelerate deployment cycles when scaling across regions."

Email sequence (5 touches, 21 days):

• Day 1: Personalized email. Subject: "[CTO name], TechVentures' growth trajectory + microservices stack." Include funding announcement callout + 1 personalization hook.
• Day 6: Follow-up email. "Did my previous email on UK expansion challenges land?"
• Day 10: LinkedIn message to CTO/VP Engineering (different messaging angle).
• Day 14: Value-add touch: Share relevant case study (FinTech company, similar ARR, scaling scenario).
• Day 21: Final breakup email. "Last chance: Let's talk about your Q3 infrastructure goals."

Sales involvement: Assign to named AE. Book 30-min discovery call target.

Expected outcome: 8–12% reply rate. Target for immediate sales qualification.

---

End of scoring example. TechVentures Inc. is a go for outreach at Tier 1 intensity.