Find People
Find People searches professional profiles across the whole market and creates a row per person.
Filters work on two levels at once: the person (title, level, function, location, education) and the company they work at (industry, headcount, revenue, funding, HQ). “VP Sales at Series A SaaS companies in the US with 51–200 employees” is one search, not a company search followed by a people search.
- Action
- Find People
- Category
- Lead Sourcing — Search
- Limit
- Monthly Search People/Company allowance on your plan
- Required input
- At least one filter
- Returns
- People with title, location, LinkedIn URL and current company
Monthly limits
Every person returned counts against your plan’s Search People/Company per month allowance. The allowance is shared with Find Companies and resets each month.
| Plan | Search People/Company per month |
|---|---|
| Solo | 5,000 |
| Growth | 20,000 |
| Pro | 50,000 |
| Business | Unlimited |
| Enterprise | Unlimited |
Current plans and prices are on the pricing page .
What it does
- Searches people across all companies, not one company at a time
- All filters combine with AND. Multiple values inside one filter combine with OR.
job_level: [VP, Director]plushq.country_code: [US]means “VPs or Directors, at US-headquartered companies” - Most text filters take an include and an exclude list — exclusions are the cheapest way to keep a list clean
- Revenue and funding filters are ranges; a company matches when its band overlaps the range you set. Leave a bound at 0 to leave it open
To find people at companies you already have rows for, use Find People Within Company instead — that fills a column, this creates rows.
Person filters
| Filter | Type | What it matches |
|---|---|---|
| Job title — include / exclude | List | Keywords in the current title. Wrap a value in brackets ([CEO]) for an exact, case- and accent-insensitive match instead of a keyword match |
| Include LinkedIn headline | Toggle | Also match job title keywords against the LinkedIn headline |
| Job function | List | Exact function — e.g. Sales & Business Development, Advertising & Marketing, Engineering, Finance & Accounting, HR, IT, Legal |
| Job level | List | C-Team, VP, Director, Manager, Staff, Other |
| Minimum connections | Number | Minimum LinkedIn connections (0–500) |
| City — include / exclude | List | Keywords in the person’s city |
| Country | List | ISO country codes — US, GB, FR |
| Continent | List | Africa, Antarctica, Asia, Europe, North America, Oceania, South America |
| Sales region | List | NORAM, LATAM, EMEA, APAC |
| Education — include / exclude | List | School, degree or year keywords — Stanford, MBA, Bootcamp |
Company filters
Applied to the person’s current employer.
| Filter | Type | What it matches |
|---|---|---|
| Company LinkedIn URL | List | Exact LinkedIn company URLs — pin the search to named accounts |
| Company name — include / exclude | List | Keywords in the company name |
| Industry — include / exclude | List | Exact LinkedIn industries — e.g. Software Development, IT Services and IT Consulting |
| Company type — include / exclude | List | Privately Held, Public Company, Nonprofit, Partnership, Government Agency, Educational, Self-Employed, Sole Proprietorship |
| Employee range | List | 1-10, 11-50, 51-200, 201-500, 501-1000, 1001-5000, 5001-10000, 10001+ |
| Employee count | Min / max | Exact LinkedIn headcount range, when the brackets are too coarse |
| Minimum LinkedIn followers | Number | Company page followers |
| Revenue | Min / max (USD) | Annual revenue band |
| Keywords — include / exclude | List | Searched across company description, specialties, NAICS/SIC descriptions and Crunchbase categories |
| NAICS code — include / exclude | List | e.g. 541511 |
| SIC code — include / exclude | List | e.g. 7372 |
| Web traffic | Min / max | Monthly site visits |
| Ad spend | Min / max (USD) | Monthly Google Ads spend |
| Total funding | Min / max (USD) | Total raised |
| Last funding amount | Min / max (USD) | Size of the latest round |
| Last funding year | Min / max | Year of the latest round |
| Last funding type — include / exclude | List | Pre seed, Seed, Series A–J, Angel, Private equity, Debt financing, Grant and more |
| Lead investors — include / exclude | List | Investor name keywords — Sequoia |
| Founded year | Min / max | Year founded |
| HQ city — include / exclude | List | Keywords in the HQ city |
| HQ state — include / exclude | List | Keywords in the HQ state or province |
| HQ country | List | ISO country codes |
| HQ continent | List | Continent of the headquarters |
| HQ sales region | List | NORAM, LATAM, EMEA, APAC |
How to use it
- Open the table and click Table → Import → Find People
- Set the person filters — title or level plus function is usually enough
- Narrow on the company — headcount, industry, HQ country
- Add exclusions (titles like
Assistant,Intern; industries like Staffing and Recruiting) - Set a result count, run it, map the output fields to columns, and click Create Rows
Schedule Auto Import
Turn on Enable Auto Import to re-run the search on a frequency with the same filters and column mapping. Every scheduled run counts against the monthly allowance exactly as a manual one does — cap the result count before you turn it on, and dedupe on LinkedIn URL so repeat runs do not duplicate people. Schedules live under Manage scheduled imports.
Common use cases
- Build a persona list in one pass. Title + level + company size + HQ country is a complete ICP search.
- Target recently funded companies. Last funding year and type put you in front of teams with fresh budget.
- Pin to named accounts. Paste company LinkedIn URLs to pull the buying committee at a target list.
- Alumni plays. Education filters surface people who share a school with your rep or founder.
Best practices
- Search first, enrich second — narrow the list before spending credits on emails and phones
- Use bracketed exact titles (
[Head of Sales]) when keyword matching pulls in near-misses - Prefer job level + function over a long list of title variants
- Start with a small result count, check the columns, then scale — every row counts toward the monthly limit
- Dedupe on LinkedIn URL across runs
Where to next
- Find Companies — search accounts instead of people, same filters
- Find Work Email — turn each person into a contact
find_people— run a people search from an AI client over MCP- Credits — how enrichment on these rows is billed