Find LinkedIn From Personal Email
/find-linkedin-from-personal-emailResolves a personal Gmail or Outlook address to that person's LinkedIn profile URL, turning signup and webinar rows into leads you can qualify.
Overview
find-linkedin-from-personal-email takes a personal email address — gmail.com, outlook.com and similar — and returns that person's LinkedIn profile URL. It drives the SyncGTM MCP tool find_linkedin_from_personal_email, which waterfalls across Apollo, RocketReach, Datagma, LeadMagic and Icypeas and stops at the first provider that matches, for a flat 2 credits per lookup. Use it on the rows where a private address is all you captured: consumer signup forms, waitlists and webinar registrations.
What it does
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Takes one personal email address per call in the `email` parameter and returns `linkedin_url`, the email you sent, and a `status` field
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Accepts an optional `work_email` on the same call. It costs nothing extra, and with only two parameters on the tool it is the single lever you have on match accuracy for common names
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Runs the waterfall — Apollo, RocketReach, Datagma, LeadMagic, Icypeas — in sequence and stops at the first hit, so you pay once per lookup, not once per provider tried
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Returns a profile URL and nothing else: no name, job title, company, phone or work email. The skill chains `enrich_person` or `linkedin_profile_enrich` when you need those
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Has no batch parameter. The skill deduplicates your list, caps the run, and makes one call per address
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Costs 2 credits per lookup, flat, charged whether or not a match comes back — the skill states the total before it spends anything
How to use it
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Download the skill file — it saves as find-linkedin-from-personal-email.zip.
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In Claude, open Settings → Capabilities → Skills and upload the .zip (or unzip the find-linkedin-from-personal-email/ folder into .claude/skills/ for Claude Code).
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Connect the SyncGTM MCP server first (browser sign-in, no API key), then split your list by address type — company addresses belong to find_linkedin_from_work_email, not here.
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Type /find-linkedin-from-personal-email, paste the personal addresses, and state a cap: 'stop after 40 and report credits used, do not guess a profile URL'.
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The one setting worth tuning: pass `work_email` alongside the personal address on every row where you hold both. It is free and it lifts the match rate on common names.
Use cases
Webinar signup backfill
Half a webinar registration list arrives on gmail addresses with no company attached. Resolve those rows to profiles so an SDR can see who actually turned up before writing a follow-up.
Free-trial PLG qualification
A self-serve trial user signed up with a private address. Get the profile URL so you can tell a buying-committee VP apart from an end user evaluating for fun.
Churned champion win-back
Your CRM has bounced contacts whose only live address is personal because they left the company. Resolve the profile, find where they landed, and re-open the account there.
Inbound routing by seniority
Newsletter and waitlist forms capture nothing but an email. Attach a LinkedIn URL so enterprise-shaped signups route to AEs instead of sitting in a nurture drip.
GTM workflow examples
Monday morning: turn a webinar export into a sequence-ready list
- 1Run `check_credits` (free), then split the 100-row webinar export by address type — the 60 gmail and outlook rows stay here, the 40 company addresses go to `find_linkedin_from_work_email`.
- 2Call `find_linkedin_from_personal_email` on the 60 personal addresses at 2 credits each — 120 credits — passing `work_email` on any row where the registration form also captured a company address.
- 3Run `enrich_person` (1 credit) with `linkedin_url` set to each resolved profile. It returns `first_name`, `last_name`, `job_title` and `organization_name` — drop every row whose title sits outside the buying committee.
- 4Resolve each surviving `organization_name` to its website domain, then run `enrich_organization` (2 credits) on that domain — the tool takes `domain` only — and cut anything below your headcount or industry floor.
- 5Run `find_work_email` (1 credit) on the kept profile URLs, passing `organization_name` to disambiguate common names, then `verify_email` (0.3 credits) so the follow-up lands in a company inbox rather than a personal one.
Outcome: A CSV of qualified attendees with name, title, company, LinkedIn URL and a verified work email, built from nothing but a gmail address on a registration form.
PQL brief before the first call with a self-serve trial user
- 1Call `find_linkedin_from_personal_email` on the trial signup's private address (2 credits) to get the profile URL.
- 2Run `linkedin_profile_enrich` (1 credit) on that URL for the `experience`, `education` and `skills` arrays — the titles and companies inside `experience` are what tell you whether the trial user holds budget or is an end user.
- 3Resolve their current employer to a website domain and run `enrich_organization` (2 credits) on it for industry, size, funding and technologies, then score account fit against your ICP.
- 4Run `linkedin_profile_reactions` (0.2 credits, 3 posts by default) and `linkedin_profile_posts` (0.3 credits, 10 posts by default) to pull two recent things they engaged with for the opener.
Outcome: A one-page brief per trial user — who they are, whether the account is worth an AE, and two specific hooks — for about 5.5 credits.
Win back champions who left the account
- 1Pull the CRM contacts marked bounced or 'no longer at company' where the only live address on file is a personal one, and cap the run at 25 rows.
- 2Call `find_linkedin_from_personal_email` on those 25 addresses (50 credits) to get current profile URLs — the private address usually survives the job change, the work one never does.
- 3Run `check_job_change` (2 credits) on each resolved URL. It returns `job_change`, `new_company` and `new_title`, so the move and the new role land in one call.
- 4Run `find_work_email` (1 credit) on that same profile URL with `organization_name` set to `new_company`, then `verify_email` (0.3 credits) before anything is sequenced.
- 5Resolve `new_company` to its website domain and run `enrich_organization` (2 credits) on it to check the new account is even in territory before an AE claims it.
Outcome: A ranked win-back list of former champions with their new company, new title and a verified work email at the new employer.
Prompts
Paste any of these into Claude once the skill is installed and the SyncGTM MCP is connected.
Find the LinkedIn profile for jane.doe@gmail.com.Find the LinkedIn profile for jane.doe@gmail.com — her work email is jane@stripe.com, use it to improve the match.Here are 40 personal emails from our webinar export. Resolve LinkedIn URLs for all 40, stop there, do not guess a profile URL, and report credits used.Split this CSV into work and personal addresses. Run find_linkedin_from_personal_email on the personal ones only, max 30 lookups, and list the work addresses separately for find_linkedin_from_work_email.Take the first 25 gmail signups in this list, resolve LinkedIn URLs, then run enrich_person on the ones that matched to get title and company. Cap it at 25 lookups and show total credits spent.Best practices
Say "personal email" in the prompt. Naming the address type keeps Claude on this tool instead of the work-email variant, which is priced the same but built for company domains.
Split the list by address type before you spend anything. Free-mailbox domains come here; company domains go to find_linkedin_from_work_email — sending a row to the wrong tool wastes 2 credits and returns a blank.
Pass `work_email` on every row where you hold both addresses. It is free, and with only `email` and `work_email` on the tool it is the only accuracy lever available for common names.
Always add "do not guess a profile URL" to batch prompts. jane.doe@gmail.com does not become linkedin.com/in/janedoe, and a fabricated URL poisons every downstream enrichment.
Cap the batch and expect blanks. A miss bills the full 2 credits, so a 100-address run costs 200 credits regardless of hit rate — filter to ICP-shaped signups first rather than resolving the whole export.
Treat a blank as "not on file", not "no profile". Personal addresses match less reliably than work ones because many people never attach a private address to LinkedIn — retrying the same address a minute later returns the same nothing and bills again.