Build a list of companies in a specific geography

Built by: Lusha
Time to build: 1 min
Difficulty: Easy
Tools: Claude ▪ Lusha
Type: Prompt

A Claude prompt that returns verified companies and contacts inside a specific country, region, state, or metro — with regional accuracy bands and compliance footprint surfaced upfront so the list is safe to action.

Once Lusha is connected in Claude, the connector runs in the background — no special syntax needed. Just paste the prompt and run.

Images on this webpage are for illustrative purposes only. Any named individuals shown in live demo outputs are real, with last names abbreviated for privacy.

The prompt

Open in Claude Open in ChatGPT 
<context>
Build a verified prospect list in [GEOGRAPHY, e.g. DACH, UK, Texas, APAC].
Selling [PRODUCT] to [BUYER].
</context>

<task>
1. Find companies: geography [SPECIFIC REGION / COUNTRY / STATE / METRO],
   industry [INDUSTRY], headcount [RANGE].
2. For each, find contacts in [TITLE FAMILY].
3. Enrich with verified email, direct dial, country.
4. Return: Company | HQ city | Country | Contact | Title |
   Email | Direct dial | Compliance (GDPR / CCPA / both).
5. Group by country.
</task>

<constraints>
- Validated emails only.
- Header: regional accuracy (NA 98%, EMEA 97%, APAC 96%, LATAM 95%).
- Flag contacts in stricter consent regions.
</constraints>

What you'll get back

Input: Geography — DACH (Germany, Austria, Switzerland) · Industry — manufacturing · Headcount — 501–5,000 · Titles — Head of Procurement, COO, VP Procurement.

Output: 437 matching contacts identified in the first batch across DACH manufacturing. Below is a real slice of the live result — five verified procurement and operations leaders at named German manufacturers, all with validated work emails and phones. EMEA email accuracy published at 97%, processed under GDPR.

ContactTitleCompanyValidated emailPhone
Jan Henner T.Chief Procurement Officer[Shipbuilder, ~3,500 emp.]✓✓
Oliver F.Vice President of Procurement[Industrial systems, ~3,000 emp.]✓✓
Christian S.VP of Global Procurement[Plastics machinery, ~3,500 emp.]✓✓
Florian H.Chief Operating Officer[Medtech, ~2,500 emp.]✓✓
Norbert T.Chief Operating Officer[Valves & instrumentation, ~5,000 emp.]✓✓

Names and company identifiers abbreviated for privacy. Full records — including emails and direct dials — are returned inside your Claude session.

Why it works

Geographic prospecting fails when the data quality drops at the regional level. A list of EMEA contacts with NA-grade decay rates is not safe to send — and a list of APAC contacts pulled from a US-skewed database returns thin coverage with stale titles.

Lusha publishes accuracy bands by region — 98% in North America, 97% in EMEA, 96% in APAC, 95% in LATAM — and processes data under the relevant regional compliance frameworks. The prompt surfaces those bands inline, so the geography filter doesn’t silently degrade the output.

The prompt pulls from 300M+ verified contacts under GDPR, CCPA, SOC 2, ISO 27701, ISO 31700, and TRUSTe — safe to action across regions.

FAQ

  • Can I target a specific metro or state, not just a country?

    Yes. The prompt accepts metro-level inputs like “Greater London,” “Bay Area,” or “São Paulo.” Claude resolves the location against Lusha’s catalog before running the search.

  • Does the prompt handle multi-country territories?

    Yes. List each country in the geography variable — for example, DACH as Germany, Austria, Switzerland — and the output groups by country for clean territory work.

  • Are contacts in regulated regions flagged?

    The prompt is built to surface contacts where the compliance footprint requires opt-in or specific consent handling, so you can route to the right channel deliberately.

  • What's the email accuracy band by region?

    98% North America, 97% EMEA, 96% APAC, 95% LATAM. Published in the Lusha data documentation and refreshed continuously.

  • Does Lusha cover EMEA, APAC, and LATAM as deeply as North America?

    Coverage varies by region and industry. The prompt returns only verified rows — if a region or persona is thin in Lusha’s data, the search returns fewer rows rather than padding with low-confidence matches. Use the filter-relax suggestion at the bottom of the prompt if results come back light.

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