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Prompt

Build a lookalike prospect list from a best customer

Built by: Lusha
Time to build: 4 min
Difficulty: Easy
Tools: Claude ▪ Lusha ▪ Slack

Images on this page are for illustrative purposes only. Example outputs in this play are illustrative — the structure, fields, and format reflect real Lusha connector output, but were not pulled from a live session. Run the prompt with your own reference customer to see live results. Personal details in any live examples are masked or abbreviated for privacy.

A lookalike prospect list built from a best customer uses the firmographic profile of a closed-won account — industry, size, sub-industry, tech stack, and buying signals — to find companies that match rather than building a list from scratch against a generic ICP. This Claude prompt pulls the reference company’s full profile via Lusha, runs the lookalike search, maps a verified contact at each match, scores every account Priority A through C, and posts the call list to Slack before the prospecting sprint starts.

The prompt

Open in Claude Open in ChatGPT 
<context>
I want to find more companies like my best closed-won account — companies that match the same firmographic profile, industry, size, and buying signals. Instead of starting from a blank ICP, I want to clone the profile of a customer that already works.

My best customer to clone:
- Company name: [COMPANY NAME OR DOMAIN]
- Why it's a good fit: [WHAT MAKES IT A GREAT CUSTOMER — e.g. "fast close, no technical debt, champion was RevOps VP, expanded within 6 months"]
- Function I sell into: [e.g. "Sales, RevOps, Finance"]
- Seniority floor: [e.g. "VP and above"]
- Geography: [e.g. "US" / "EMEA" / "Global"]
- Number of lookalike companies to find: [e.g. "20"]
- Slack channel: [CHANNEL NAME OR "skip"]
</context>

<task>
1. Use Lusha to pull the full firmographic profile of the reference company:
   - Industry, sub-industry
   - Employee headcount range
   - Revenue range
   - HQ geography
   - Technology stack signals (if available)
   - Any current buying signals

2. Use Lusha's lookalike search to find companies that match this profile:
   - Same industry and sub-industry
   - Similar headcount range (+/- 30%)
   - Same geography unless specified otherwise
   - Prioritize companies with a live signal in the last 30 days

3. For each lookalike company, find the right contact:
   - Most senior verified contact in the target function at or above the seniority floor
   - Verified work email and direct mobile

4. Score each lookalike:
   - A: profile match + live signal + verified contact
   - B: profile match + verified contact, no signal
   - C: profile match, no verified contact at required seniority

5. Return:
   - Reference company profile used for matching
   - Lookalike list sorted by score: company, size, industry, signal (if any), primary contact, email, mobile
   - Priority A accounts to call first
   - Any accounts where no verified contact was found
   - Slack post of Priority A list if channel specified
</task>

<constraints>
- Match on firmographic profile, not just industry label — size range matters as much as sector.
- Priority A requires a live signal AND a verified contact.
- Verified contacts only — no format guesses.
- Reference company profile must be explicitly stated before the lookalike list.
</constraints>

What you'll get back

The situation: An AE uses Ashford Platforms — a $95K ACV closed-won account, VP RevOps champion, 420 employees, B2B SaaS — as the reference to build a new prospecting list.

Reference company profile (Ashford Platforms)

Industry: B2B SaaS · Sub-industry: Sales Enablement Headcount: 420 employees · Headcount range used for matching: 294–546 Revenue range: $20–50M (estimated) HQ: US · Technology stack signal: HubSpot, Salesforce, Outreach Current signal: Headcount up 18% in last 30 days

Lookalike list — 6 results

Priority A — signal + verified contact

Dunmore Analytics · 580 employees · B2B SaaS Signal: Series B closed 18 days ago Contact: T.K., VP of Sales ✓ · t.k@[dunmore].com · direct mobile available

Crestline Software · 340 employees · B2B SaaS Signal: New CRO hired 12 days ago Contact: R.V., VP Revenue Operations ✓ · r.v@[crestline].com · direct mobile available

Priority B — verified contact, no signal

Greenway Cloud · 510 employees · SaaS / Cloud Infrastructure Contact: J.A., SVP of Sales ✓ · j.a@[greenway].com · direct mobile available

Briarway SaaS · 290 employees · B2B SaaS Contact: P.O., VP of Sales ✓ · p.o@[briarway].com · direct mobile available

Halcyon Data · 470 employees · B2B SaaS Contact: S.P., VP Revenue Operations ✓ · s.p@[halcyon].com · direct mobile available

Priority C — no verified contact at VP floor

Elmont Systems · 610 employees · B2B SaaS Director-level contact found but below VP threshold. Use the find DM play before calling.

Slack alert posted to #prospecting · Priority A: Dunmore + Crestline — signal windows open now

Illustrative example — fictional company names used. Run with your own best customer to see live results.

Why use Lusha in Claude

Lusha in Claude converts a single closed-won account into a prospecting strategy in one pass. The reference profile — Ashford Platforms: 420 employees, B2B SaaS, HubSpot + Salesforce stack, RevOps-led buying motion — is more specific than any ICP definition built in a boardroom. The companies that match this profile are ones where the same buying motion has already been proven. The signal layer on top is what separates Priority A from Priority B: Dunmore’s Series B and Crestline’s new CRO are the two accounts where the window is open right now. Priority B accounts are valid targets — the signal just hasn’t fired yet. The list is ready to work on day one of the sprint.

Data drawn from 300M+ verified contacts under GDPR, CCPA, SOC 2, ISO 27701, ISO 31700, and TRUSTe.

FAQ

  • How is this different from building an ICP-scored list?

    The ICP score play scores a list you already have against a defined ICP. This play builds the list from scratch by cloning the exact firmographic profile of a specific closed-won account. The difference is the starting point: a defined ICP is a hypothesis; a closed-won account is a proof point.

  • What if the reference company is too small or too unique?

    Lusha’s lookalike search uses industry, sub-industry, and headcount range — not an exact copy. If the reference company is an outlier (unusually small, niche sub-industry), the match set will be smaller. The prompt flags if fewer than 10 companies are found and suggests relaxing one filter (e.g. widening the headcount range or including adjacent sub-industries).

  • Should I use my largest customer or my best-fit customer as the reference?

    Best-fit. Largest ACV often means an unusual buying process with stakeholders and timeline that can’t be replicated at scale. Best-fit means fast close, clean champion, expanded — the companies that match that profile are the ones worth prospecting into.

  • How often should I rebuild the lookalike list?

    At the start of each prospecting sprint — monthly or quarterly. The signal layer changes month to month, so a list that was Priority B in April may have Priority A accounts in May after a round of funding events.

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