ICP score a new target list before the team works it

<context>
I have a new list of target accounts I want to score against our ICP before handing it to the team. I want to know which accounts are worth working, in what order, and why, based on verified firmographic data, not assumptions.

My list:
- Account list: [PASTE COMPANY NAMES OR DOMAINS, one per line]
- Our ICP criteria:
  - Industry: [LIST TARGET INDUSTRIES]
  - Company size: [HEADCOUNT RANGE. E.g., 100-1000 employees]
  - Geography: [REGION OR COUNTRY]
  - Function we sell into: [SALES / MARKETING / FINANCE / IT / OPS / OTHER]
  - Signals that indicate fit: [RECENT FUNDING / HEADCOUNT GROWTH / NEW EXEC / OTHER]
- Disqualifiers: [CRITERIA THAT RULE AN ACCOUNT OUT. E.g., too small, wrong industry, acquired]
</context>

<task>
1. For each account on the list, use Lusha to pull verified firmographic data:
   - Current headcount and headcount trend (growing, stable, contracting)
   - Industry and sub-industry
   - Geography and HQ location
   - Headcount in the function we sell into
   - Any active signals: recent funding, exec hire in the relevant function, M&A activity

2. Score each account against the ICP criteria:
   - STRONG FIT: meets all core ICP criteria and has at least one active signal
   - FIT: meets core ICP criteria, no active signal
   - PARTIAL FIT: meets some criteria, missing one or two. Flag which ones.
   - DISQUALIFIED: fails a disqualifier criterion. Flag why.

3. For each STRONG FIT and FIT account, identify the right first contact:
   - The person most likely to own the problem we solve, given the function we sell into
   - Verified title, work email, and direct phone where available
   - Flag if no verified contact found in the relevant function

4. Return a scored list:
   - STRONG FIT accounts first, ranked by signal recency within the tier
   - FIT accounts second
   - PARTIAL FIT accounts third. Include what's missing and whether it's worth a manual check.
   - DISQUALIFIED accounts at the bottom. One-line reason each.

5. Return a summary:
   - Total accounts scored
   - STRONG FIT / FIT / PARTIAL FIT / DISQUALIFIED counts
   - Top 5 accounts to work first and why
   - Any pattern in the disqualified accounts worth feeding back to whoever built the list
</task>

<constraints>
- Score only against the ICP criteria provided. Don't add criteria the rep didn't specify.
- DISQUALIFIED is a clean output. Don't soften it to PARTIAL FIT to avoid wasting the list. A disqualified account worked by a rep is wasted time.
- If Lusha can't find firmographic data for an account, flag it as UNVERIFIED. Don't score it.
- The top 5 recommendation must explain why each account ranks where it does, not just repeat the score.
</constraints>

The situation: A RevOps lead receives a list of 15 accounts from a recent industry conference. ICP: B2B SaaS or FinTech, 150–800 employees, North America, selling into Sales and Revenue Operations teams. Disqualifiers: under 100 employees, acquired as target entity, non-English-speaking markets.

Output: 4 STRONG FIT, 5 FIT, 3 PARTIAL FIT, 2 DISQUALIFIED, 1 UNVERIFIED. Top 5 identified with specific reasons. One pattern flagged in the disqualified accounts.

Summary

15 accounts scored · 4 STRONG FIT · 5 FIT · 3 PARTIAL FIT · 2 DISQUALIFIED · 1 UNVERIFIED

ICP: B2B SaaS / FinTech · 150–800 employees · North America · Sales and RevOps function. Run: May 19, 2025.

Top 5 accounts to work first

1. Halcyon Ventures — STRONG FIT 310 employees, SaaS, US. New CRO hired 18 days ago — strongest signal on the list and most recent. RevOps team of 12. First contact: J.K., CRO · j.k@[halcyon].com ✓ · mobile verified. Lead with the new CRO angle — 60-day audit window is open now.

2. Bright Arc Systems — STRONG FIT 420 employees, FinTech, US. Series B closed 6 weeks ago, sales headcount up 28% in Q1. RevOps team growing. First contact: M.T., CRO · m.t@[brightarc].com ✓ · mobile verified. Series B + headcount growth = budget unlocked and data layer under pressure.

3. Waverly Digital — STRONG FIT 190 employees, SaaS, Canada. New VP of Sales 22 days ago — first VP Sales hire, previously founder-led. First contact: S.R., VP Sales · s.r@[waverly].com ✓ · mobile verified. First VP Sales at a founder-led company is the highest-intent signal for sales tooling.

4. Kestrel Labs — STRONG FIT 155 employees, HR Tech (adjacent ICP — sales motion applies), US. New VP of Sales 27 days ago. First contact: D.P., VP Sales · d.p@[kestrel].com ✓ · email verified, mobile not found. Signal is fresh. HR Tech is adjacent — worth the outreach given the exec hire timing.

5. Finova Group — FIT 180 employees, FinTech, US. No active signal but strong ICP match — size, industry, function. First contact: A.M., VP Sales · a.m@[finova].com ✓ · mobile verified. No signal today — run this account again in 30 days or use the expansion signals scan to monitor.

STRONG FIT — work this week

FIT — work this week after STRONG FIT

PARTIAL FIT — manual check before working

DISQUALIFIED — do not assign

Cartway Technologies — acquired as target entity 9 weeks ago. Contracts under integration review. Remove from list.

Sola Systems — 41 employees. Below minimum headcount threshold. Remove from list.

UNVERIFIED

Meridian Co (not Meridian Logistics) — Lusha cannot confirm firmographic data for this entity. Two companies with similar names returned. Manual check required before scoring.

Pattern in disqualified accounts

Both disqualified accounts appear to have come from a conference list compiled by company name without size or status verification. Worth flagging to whoever sourced the list — adding a headcount filter and an M&A status check at the point of list creation would remove these before they reach RevOps.

All firmographic data and contacts validated via Lusha connector, May 19. Names masked to initials, emails abbreviated for privacy.