Outputs on this page come from a live run on September 10, 2026. Company names are masked to initials. No contacts were previewed or revealed.
Of the 24 company signals in the Lusha plugin for Claude, this is the one built for field teams and regional reps. The buyer is whoever is standing up or growing the local team, and the moment is while the roles are still open.
Find which of my target accounts are building a team in a specific region and rank who to approach.
Region: [CITY OR REGION, e.g. London]
Before anything else, run account_usage and tell me my remaining credits. Do not run any signal call if fewer than 60 credits remain; stop and tell me.
Here is my list (domain, one per line):
[PASTE UP TO 25 DOMAINS]
Customer domains (or write "none"):
[PASTE]
Steps:
1. Run signals_company_filters with filterType "hiringByLocations" and my region as the query. Show me the matching value (it will be a country and state, not a city) and use that exact value in the next step.
2. Run signals_companies_search on the list with signalTypes ["surgeInHiringByLocation"], filters.include.hiringByLocations set to the value from step 1, startDate 60 days ago, maxResultsPerSignal 2. This signal reads weekly, so 2 readings is enough to see direction. Batch in groups of 25 if the list is longer.
3. For every hit, pull new jobs posted in the last 4 weeks, the historical average, the change rate, and the reading date. Keep accounts with no signal in the output as "no signal."
4. Rank by jobs above average (new jobs minus historical average), not by percentage. Then break ties by whether the count rose between the two readings. Mark any account with fewer than 5 jobs above average as SMALL so I do not treat noise as a surge.
5. Classify each hit: NEW MARKET if the historical average is below 3 and new jobs are 5 or more (the company is standing up a presence), otherwise SCALING HUB (the company is growing an existing office). Tag customers as EXPANSION and everyone else as NEW LOGO.
6. For the top 5 NEW LOGO accounts that are not SMALL, write one opening line addressed to the leader building that team (country manager, regional VP, head of the local office) that references growing the team in the region without quoting a number.
Output: one table with columns Account | Jobs last 4 weeks vs average | Change | Reading dates | Type | Segment | Opening line. Then two lines: what the ranking is based on, and credits used. Do not preview or reveal any contacts in this run.The situation. A UK based rep with a list of 25 US headquartered software companies, 2,000 to 10,000 employees. Region: London. No customer domains supplied.
The run. account_usage first, at zero credits. The location lookup returned “United Kingdom, England” for London: the filter works at country and state level, not city. Then one batch call on 25 domains for surgeInHiringByLocation with a 90 day window and three readings per account. 19 of 25 fired, 41 signal events, 41 credits. Readings were weekly, the newest dated August 31.
What came back.
| Account | Jobs last 4 weeks vs average | Change | Reading dates | Type | Segment | Opening line |
|---|---|---|---|---|---|---|
| S.T. (payments, ~8,000 emp) | 66 vs 36 | +81%, rising 59 to 60 to 66 | Aug 17, 24, 31 | SCALING HUB | NEW LOGO | Growing a team that fast in one region means a lot of new reps starting with an empty book. We make sure the first week is not spent finding phone numbers. |
| D.L. (HR and payroll, ~4,000 emp) | 30 vs 9 | +233%, rising 10 to 17 to 30 | Aug 3, 10, 17 | SCALING HUB | NEW LOGO | The region is clearly getting real investment this quarter. Happy to share what teams do in the first ninety days so the new hires ramp on verified data. |
| C.F. (network security, ~4,000 emp) | 38 vs 19 | +99%, rising 30 to 38 | Aug 24, 31 | SCALING HUB | NEW LOGO | You are doubling down locally. The question new regional teams hit first is which accounts to work; we can answer that before they arrive. |
| M.D. (work management, ~2,000 emp) | 35 vs 17 | +108% | Jun 15 | SCALING HUB | NEW LOGO | Older reading; verify before outreach. Opening line if confirmed: building out a regional team is the moment to fix the data underneath it, before habits form. |
| Z.S. (cloud security, ~7,000 emp) | 15 vs 8 | +82%, rising 12 to 14 to 15 | Aug 10, 17, 31 | SCALING HUB | NEW LOGO | Steady growth in the local team, week after week. Worth ten minutes on how comparable teams equip new reps in this market. |
| S.F. (data cloud, ~7,000 emp) | 24 vs 17 | +44%, rising 22 to 23 to 24 | Jul 27, Aug 3, 17 | SCALING HUB | NEW LOGO | |
| O.K., E.L., M.G., P.L., H.S., V.N. | 5 to 8 jobs above average | +51% to +90% | Jun 22 to Aug 31 | SCALING HUB | NEW LOGO | Qualified; work after the top five. |
| 7 accounts | 2 to 4 jobs above average | +11% to +33% | Jun 15 to Aug 31 | SMALL | Below threshold. One shows +33% on 2 jobs against an average of 1.5. | |
| 6 accounts | no signal |
Ranking based on jobs above average, then direction across readings. No account met the NEW MARKET test; all 25 already have an England presence. Credits used: 41. Confirmed live via Lusha connector, September 10, 2026. Company names masked to initials.
What happens next. The top five go to the decision maker play with the regional leader as the target title, or to the buying group play if the account is large enough that the local leader is not the budget owner. For a field team, the same run sliced by each rep’s territory is the weekly brief: which accounts in my patch are investing this week.
A regional rep does not need to know that a company is growing. They need to know it is growing here, this month, and how much. This signal carries all three: the place, a weekly reading date, and the job count against the company’s own average. Running it inside Claude turns a territory review into one call per 25 accounts, keeps the accounts with nothing happening visible so the rep sees the whole patch, and stops before any contact is touched, so the ranking is decided before a credit is spent on a reveal. Every signal is sourced under Lusha’s data methodology and compliance framework.
More new job postings in a country or state over the last four weeks than the company’s historical average for that place. The signal carries the count, the average, the change rate, and a weekly reading date. It does not carry job titles; pair it with Surge in Hiring by Department for that.
No. The location filter resolves to country and state. Search “London” and you get England. Confirm the office before naming a city in outreach.
Because a company that goes from 1.5 to 2 postings shows +33% and means nothing, while one that goes from 36 to 66 shows +81% and means a hiring drive. The absolute gap is the size of the investment. The percentage is only useful once the base is big enough.
Weekly. In the live run the newest reading was 10 days old. This is the freshest signal in the set and the one where “this month” is a safe thing to say.
Signal reads cost 1 credit per event returned. Because readings are weekly, cost runs higher than monthly signals: 41 credits for 25 domains in the live run with three readings each. The prompt now caps at two readings over 60 days. account_usage runs first and the prompt stops under 60. No contact preview or reveal runs in this play.
Run it once per territory with the territory’s country or state as the region, weekly. Rank by jobs above average. The top five in each territory are that rep’s calls for the week, and the SMALL and no signal rows tell them what to leave alone.
One data connection. Works in Claude, ChatGPT, your CRM, or any agent you build.
