Find accounts hiring in a specific location in ChatGPT

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

Example outputs in this play are illustrative — they reflect the structure, fields, and format of real Lusha connector output, but were not pulled from a live session. Run the prompt with your own target location and ICP details to see live results.

When a company starts hiring in a specific location, something may be changing there.

It could be a new regional push, market expansion, local sales coverage, a support hub, a technical team, or operational growth. For sellers working by territory, region, or market, that location-level movement can be more useful than a generic company signal.

The problem is that most prospecting lists are built around where a company is headquartered, not where it is actively growing.

This prompt uses Lusha in ChatGPT to find companies with recent hiring surges in a specific country, region, or state, enrich the accounts, identify relevant contacts, and turn the location signal into a timely outreach angle. Instead of guessing which accounts are active in your market, you can start with companies showing real hiring movement there.

How to start

Open in Claude Open in ChatGPT
1

Open Lusha in ChatGPT

Go to Lusha in ChatGPT and click “Start chat.” Every conversation started this way is automatically Lusha-enabled.

2

Or invoke Lusha in any existing conversation

Type @Lusha in the prompt bar and select Lusha from the dropdown. Unlike Claude, Lusha does not activate automatically in every ChatGPT conversation. You must invoke it every time.

3

Add your location and ICP

Copy the prompt below, fill in your target country, region, or state, add your ICP and product context, and send. Lusha finds companies with location-based hiring surges and helps you prioritize who to contact first.

The prompt

Start from Lusha in ChatGPT or type @Lusha before sending.

@Lusha Find accounts with hiring surges in my target
location and help me prioritize who to contact.

TARGET LOCATION:
Country: [country]
State or region, if relevant: [state or region]
City, if relevant: [city]

TARGET MARKET:
Industries: [industries]
Company size: [employee range]
Target personas: [titles or personas]
Relevant departments: [Sales / Marketing / IT / RevOps /
Operations / Customer Success / Engineering / other]
Disqualifiers: [companies, industries, regions, or
segments to exclude]

TIME WINDOW:
Look for location-based hiring surge signals from the last
[30/60/90/180] days.

MY PRODUCT:
[One sentence describing what you sell and the problem
it solves]

Using Lusha, do the following:

1. FIND ACCOUNTS WITH LOCATION-BASED HIRING SURGES
   Search for companies that match the target market and
   have a recent hiring surge in the target location.

   Only include companies where Lusha can verify the
   company profile and location hiring signal.

2. ENRICH EACH ACCOUNT
   For each company, return:
   - Company name
   - Domain
   - Industry
   - Employee count
   - HQ location
   - Revenue range if available
   - Company LinkedIn if available

3. RETURN THE LOCATION HIRING SIGNAL
   For each account, return:
   - Hiring location
   - Signal date
   - New jobs posted in that location
   - Historical average, if available
   - Change rate percentage
   - Whether the signal is strong, medium, or weak

4. EXPLAIN WHY THE SIGNAL MAY MATTER
   Explain what the location-based hiring surge may suggest
   based on my product, target persona, and region.

   Keep the explanation grounded. Do not assume the company
   is opening a new office, expanding into a market, or
   buying my category unless Lusha returns a relevant
   supporting signal.

5. CHECK SUPPORTING SIGNALS
   Check whether the same company also has other recent
   signals from the last 6 months.

   Prioritize:
   - Overall hiring surge
   - Hiring surges by relevant department
   - Headcount increases or decreases
   - IT spend changes
   - Website traffic changes
   - Commercial activity news
   - Corporate strategy news
   - Financial events news
   - People news
   - Product activity news
   - Risk news
   - Promotion or company-change signals for relevant contacts

6. SCORE ICP FIT
   Score each account:
   - High fit
   - Medium fit
   - Low fit
   - Exclude

   Base the score on industry, company size, region,
   disqualifiers, location relevance, and fit with my product.

7. PRIORITIZE THE LIST
   Rank the companies:

   Tier 1:
   Strong ICP fit + recent hiring surge in the target
   location + clear persona relevance

   Tier 2:
   Strong ICP fit + location hiring surge, but weaker
   urgency or no supporting signal

   Tier 3:
   Medium fit or unclear urgency

   Exclude:
   Poor fit, disqualified, unmatched, or unclear signal

8. FIND STARTING CONTACTS
   For each Tier 1 account, find 1-2 relevant contacts
   matching the target persona or relevant department.

   Prioritize contacts in the target location when available.
   If no local contact is available, return the most relevant
   regional or functional owner.

   Return:
   - Name
   - Current title
   - Department
   - Seniority
   - Location
   - LinkedIn profile if available
   - Verified business email availability
   - Direct or mobile phone availability
   - DNC status if available

9. CREATE THE OUTREACH ANGLE
   For each Tier 1 account, write:
   - One subject line under 7 words
   - One opening line under 30 words
   - One discovery question tied to the location signal

   Do not:
   Say "I saw you are hiring in [location]" in a generic
   or awkward way.
   Overstate what the hiring signal proves.
   Invent office openings, market launches, projects,
   priorities, or internal initiatives that Lusha did not return.
   Make the message sound like a job-posting scrape.

10. OUTPUT FORMAT
   Return:
   - Account table
   - Location hiring signal
   - Supporting signals, if any
   - ICP fit score
   - Priority tier
   - Recommended contacts
   - Outreach angle
   - Discovery question

Do not invent companies, contacts, emails, phone numbers,
or signals. If Lusha cannot verify the location hiring
surge, do not include the account.

What you’ll get back

 

A prioritized list of accounts hiring in your target location, enriched company profiles, relevant contacts, and outreach angles. Here’s what the output looks like:

Location hiring surge accounts — Lusha

FieldValue
Signal typeHiring surge by location · Canada, Ontario
Best-fit account[Company A] · B2B SaaS · 1,000–5,000 employees · North America
Hiring signal52 new jobs in Ontario · 161% above historical average
Priority tierTier 1 · strong ICP fit + regional hiring movement
Recommended contactR.M. · Regional Sales Director · verified email available
Outreach angleRegional team growth may make local pipeline, onboarding, or operational workflows more timely

Example outputs in this play are illustrative — they reflect the structure, fields, and format of real Lusha connector output, but were not pulled from a live session. Run the prompt with your own target location and ICP details to see live results.

 

Why use Lusha in ChatGPT to find location-based hiring surges

 

Location-based hiring can reveal movement that a headquarters-based account list misses. A company may be headquartered in one country but actively growing teams in another. For territory sellers, regional campaigns, partner teams, or market expansion motions, that local activity can be the real signal.

Lusha helps turn that movement into a prioritized account list. The prompt finds companies hiring in your target location, enriches the company profile, checks for supporting signals, and identifies relevant contacts. When possible, it prioritizes contacts in the same location. If not, it finds the closest functional or regional owner.

The location context matters because local growth often creates local pressure. A team hiring in a new region may need better onboarding, routing, data, systems, enablement, or operational support. The prompt helps translate the hiring movement into a grounded outreach angle without assuming too much.

The result is prospecting based on where accounts are actively growing, not just where they are headquartered.

Lusha data is sourced and used in accordance with Lusha’s Privacy Policy and Terms of Use. Lusha is GDPR compliant and covers contacts across North America, EMEA, and APAC.

FAQ

  • Why is location-based hiring useful for prospecting?

    Location-based hiring can show where a company is actively growing, even if that location is different from its headquarters. This is useful for territory planning, regional campaigns, market expansion, and local sales motions.

  • Can I use this for country-level targeting?

    Yes. You can search by country, state, region, or city when relevant. The prompt asks Lusha to find location-based hiring surge signals and prioritize accounts that match your target market.

  • Should I mention the location hiring signal directly?

    Use it carefully. The prompt asks ChatGPT to turn the signal into a natural business angle instead of saying “I saw you are hiring in this region.” The message should focus on what regional growth may create for the buyer.

  • What if Lusha cannot find a contact in that location?

    The prompt asks Lusha to prioritize local contacts when available. If no local contact is found, it returns the most relevant regional or functional owner instead.

  • Can this help with territory planning?

    Yes. Sales and marketing teams can use this prompt to identify which accounts are actively growing in a specific territory, then prioritize outreach based on verified account movement and relevant contacts.

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