How to Find LinkedIn Contacts for a Target Account List

A useful account list needs the right function as well as the right company. A founder may be relevant to a small partnership deal, while a larger account needs someone who owns partnerships.

The LinkedIn Decision Maker Finder searches Google for public LinkedIn profile matches at companies you supply. I maintain the Actor. This guide uses two companies and two role titles to build a contact shortlist that you can verify before adding it to a CRM.

Start with an account and a role

Provide company names, LinkedIn company slugs, or full company URLs. A URL avoids ambiguity between similarly named businesses. The Actor resolves company names through search, then searches for people with matching titles. It does not require a LinkedIn account or cookies.

Choose titles based on the function you need. The example uses VP Sales and Head of Partnerships. Leaving titles empty searches a broad default list including executives, directors, founders, and owners, which is less focused for this task.

country selects search locality using a Google domain suffix such as com, co.uk, or de. It does not restrict where the person lives. Company industry and size, person location, education, connections, and biography are currently null fields; this is not a full LinkedIn profile enrichment tool.

Budget for the sample

Pricing as of September 6, 2026. Each dataset result is $0.025. The Actor-start event is $0.00005 per GB of allocated memory, with a minimum of one event. Six returned people at 1 GB would cost about $0.15005. Check current Actor pricing and the run charge breakdown; these calculations describe Actor events, and separately billed platform or proxy resources may also apply.

Find three people per company

Open the Actor on Apify. In Input, switch to the JSON editor and paste:

{
  "companies": [
    "Apify",
    "https://www.linkedin.com/company/stripe"
  ],
  "titles": [
    "VP Sales",
    "Head of Partnerships"
  ],
  "maxPersonsPerCompany": 3,
  "country": "com"
}

Click Start, then open the completed run’s output dataset.

maxPersonsPerCompany: 3 permits up to three matches for each company, or six across this example. The permitted range is 1 to 50 and the default is five per company. The limit does not imply that three suitable people exist or are publicly discoverable.

After starting the run, inspect both the resolved company and the matching title. If the company is wrong, correct its input URL before spending time reviewing contacts.

Read the returned fields

personTitle and personCurrentCompany are extracted from search results. Search snippets can be incomplete or lag behind a job change. confidence is a high, medium, or low company/title match signal, not a measured probability that this person controls a budget.

Keep companyName beside personCurrentCompany. A contradiction is useful evidence to review rather than a field to silently overwrite.

Turn the matches into a reviewed contact list

Export CSV from the dataset. Keep companyName, personName, personTitle, personProfileUrl, personCurrentCompany, confidence, and scrapedAt. Add your own columns for target function, verification date, and review outcome.

First deduplicate by personProfileUrl; the same executive can match more than one title. Then review the high-confidence matches, followed by the remaining rows. Open each profile and confirm that the current role belongs to the intended company. If the title is too broad, use the public company site to understand the person's remit.

Mark each row as relevant, wrong company, former employee, or unclear. Keep unclear matches out of an outreach export until verified. A title alone does not establish buying authority, and this Actor does not supply a verified email address.

Import only reviewed rows into your CRM, using the profile URL as an external identifier. Preserve the date checked so that a future campaign can revalidate stale employment information. This turns search matches into a manageable research queue without presenting them as verified contacts.

Diagnose missing or weak matches

If one company returns nothing, confirm its name resolves to the intended LinkedIn company page. Try its exact URL and one broader functional title, such as Partnerships, instead of adding many unrelated titles. A small company may have a founder handling the function without an exact VP title.

If a match is low-confidence, compare the title and current-company text rather than raising the result limit. More results cannot correct stale search snippets. There is no location or email filter to add to this input; those require a separate verification step.

If you still need target companies, Clutch agency research can help build an account list; LinkedIn hiring data provides a separate signal to investigate.

For automating account-list research, see the Node.js example. Use the current input fields above if the example differs.

Frequently asked questions

Does this require a LinkedIn login?

No. It discovers public LinkedIn profile matches through Google search and does not request LinkedIn cookies.

Does country filter the person’s location?

No. It selects Google search locality, such as com or co.uk. Person location is currently returned as null.

Does a high confidence score establish buying authority?

No. It indicates a company and title match. Verify the person’s current role and responsibilities before outreach.