How to find someone's email address — 7 real methods
Finding an email address is half the job. The other half — the half most guides skip — is confirming the address is real before you send to it. A found-but-dead address still counts as a bounce, and bounces wreck the sender reputation that decides whether your future mail lands. So every method below ends the same way: verify what you find. Here are seven that actually work.
Google search operators (dorks) — practical examples
Search operators turn Google into a targeted email finder. They surface addresses that are published somewhere on the open web but not indexed under a tidy "contact" heading.
"john smith" "@company.com" "john smith" email site:linkedin.com "marketing manager" "@gmail.com" site:company.com intext:"@company.com" filetype:pdf
Put the exact phrase in quotes, combine a name with a known domain, and narrow by
site: or filetype:. Conference pages, team directories and PDF
attendee lists are rich sources that a plain search misses. This is method one because it costs
nothing and works for almost any target.
Check GitHub, LinkedIn and social profiles
Developers and technical people frequently expose a public email on GitHub — in the profile, or in the author field of their commits. LinkedIn rarely shows the address directly, but the person's role and company give you the domain and the naming pattern to work with. Twitter/X bios, personal sites and Behance portfolios round out the picture.
- GitHub — profile email, or
git logauthor addresses on their repos. - LinkedIn — confirms name, role and company (the inputs for a permutation guess).
- Personal site / portfolio — often a direct
hello@orcontact@.
Guess-and-verify permutations
Most companies use one predictable pattern. Once you know a person's name and the domain, you can generate the handful of likely addresses and test them:
[email protected] [email protected] [email protected] [email protected] [email protected]
Don't send to all of them to see which sticks — that's five potential bounces. Run each through a verifier instead, and mail only the one that comes back valid. This is where finding and checking become the same workflow.
Use an email finder tool
Dedicated finders (Hunter, Apollo and similar) automate the permutation-and-verify loop for a single contact, usually on a monthly subscription. They're convenient for one-at-a-time prospecting. The trade-off is cost per lookup and a plan you pay for whether or not you use it — which is exactly the gap a pay-per-use approach fills.
Collect in bulk by niche
Manual methods don't scale past a handful of contacts. When you need a segment — every developer in a country, every creator in a niche — you need bulk collection from public sources. CharlyMail pulls addresses from GitHub, npm, PyPI, Hacker News, Reddit, Instagram, TikTok, Behance and Google or Bing search-operator queries, filtered by country, provider, gender or keyword during collection so you spend only on the segment you want.
Find them in bulk, verified
Collect addresses by niche from 10+ public sources, filter as you go, and every result is validated in the same pipeline. $0.00049 per new address, duplicates free, 200 free tokens to start.
See how collection works →What the filters actually do
Raw scraping produces noise — disposable domains, role addresses like info@, people
in markets you can't service. Filtering during collection, not after, means you don't pay to
collect addresses you'll immediately discard:
- Country — 40+ regions, so you only pull the geography you can act on.
- Provider — Gmail, Outlook, corporate; exclude what your sending setup handles poorly.
- Domain type — corporate for B2B, personal for B2C.
- Keyword / niche — scope the search to the segment you actually want.
Because the parser skips duplicates you already own for free and keeps collecting until it hits the number of genuinely new addresses you asked for, you end up paying for fresh leads only.
Sign-up and outreach loops
The addresses people give you willingly are the highest-quality ones you'll ever have. A gated resource, a newsletter, or a simple "reply to connect" in existing outreach builds a list of people who chose to hear from you. It's slower than scraping, but these addresses bounce least and convert most — worth running alongside the faster methods.
Whichever mix of the seven methods you use, treat the output the same way: candidates first, confirmed addresses only after verification. The next section is why that step is non-negotiable.
Always verify what you find
Every method above produces candidates, not confirmed addresses. Before a single send, run the list through validation: syntax, MX record, disposable-domain and role-address checks, and an optional deep SMTP check that confirms the mailbox without delivering anything. Skipping this is how good outreach turns into a blocklisted domain — see how to check an email without sending for the full method.
| Method | Best for | Scales? |
|---|---|---|
| Google dorks | One target, open web | Manual |
| GitHub / social | Developers, creators | Manual |
| Permutation + verify | Known name + domain | Semi |
| Finder tools | One-at-a-time prospecting | Subscription |
| Bulk collection | Whole niche or segment | Yes |
Frequently asked questions
What is the easiest way to find someone's email address?
Search their name plus company domain, check GitHub or LinkedIn, and if that fails, guess the likely format ([email protected]) and verify it before sending.
Can I find an email address by name only?
A name alone rarely resolves to one address, but name plus company usually does. Combine the name with the company's pattern, generate the permutations, and verify each so you send only to the real one.
Is it legal to find and email someone's address?
Finding a publicly listed address is generally legal. Emailing it is regulated — GDPR, CAN-SPAM and CASL apply to the sender. Keep messages relevant, include an unsubscribe path, and follow the rules for your market.
How do I find many emails at once for a niche?
Collect in bulk from public sources like GitHub, Reddit and search-operator queries, filter by country or keyword, then validate the results in the same tool.