Submit a list of company domains and get named contacts back - full name, their email with its source, and their social handles - alongside the company's own firmographics, phone numbers and social profiles. One call turns a list of websites into a list of humans.
We ship two services that both take domains. They answer different questions, and picking the wrong one wastes a run.
The Email & Contact Scraper answers "how do I reach this company?" - it returns the organisation's own contact surface: the addresses and phone numbers published on the site, the contact page, the social accounts, the tech stack. Excellent for reaching a business. It does not tell you who works there.
This service answers "who do I talk to?" It returns a contacts array: named individuals, with an email address where one is found, the source each address came from, social handles and category tags. Alongside them you get the company's firmographics - industry, size, employee band, founded year, revenue band and location.
So: prospecting a named decision-maker is this page. Reaching a company's general inbox is the other one. Plenty of teams run both, in that order.
A domain is the only input. Everything else is how much you want back per company.
A domain or a full link both work as input - example.com or a page URL on it.
Each domain you submit comes back as one record, built from these:
contacts is the one that makes this service what it is - an array of people rather
than a single row of company data. details carries the firmographics,
socials the company's accounts, site_data the website's own metadata,
and phones the numbers found with the page each came from. Every record keeps the
query you submitted, so a 1,000-domain run stays traceable.
The export is one flat row per contact, not a nested record - and being straight with you about it: outside the domain itself, most columns are sparse. The percentages below are measured, not estimated.
Two things you should know before you build on this. First, title - the job title - was empty on every row we measured, and so were contact_phone, contact_linkedin, contact_facebook, contact_instagram, contact_x and website_generator. A named person arrived on 36% of rows and an email on 55%. Second, this is measured over 11 rows from 6 runs, which is a small sample - treat the percentages as an order of magnitude rather than a guarantee, and run your own list on the free tier before you size a campaign around it.
The input is just domains. These settings decide how deep the enrichment goes - and what a run costs.
How many people to return for each domain. The default is three - enough to reach someone without paying for a whole org chart.
How many addresses to return for each person. Defaults to one - the rest are usually variants of the same mailbox.
Choose whether generic addresses like info@ and support@ are included, or only addresses belonging to named people.
Ask for the kinds of contact you care about - the documentation gives technical and influencers as examples - and more than one category at a time.
Skip a number of contacts per company, so a second run can reach further into a company you've already touched instead of repeating it.
Batch a whole target list in one job rather than trickling domains through one at a time.
None of these are dealbreakers. All three are cheaper to learn now than after you've built a pipeline.
Contact records vary. A contact always has a name and at least one address, but the job title column was empty on every row we measured, and contact-level social handles were too. Write your importer so a missing title is normal rather than an error.
Firmographics are aggregated from public sources. Industry, headcount, revenue band and location come from what companies and directories publish about themselves. Treat them as strong signals for segmenting a list - not as audited figures. Where two fields describe the same thing in different units, expect them to disagree occasionally.
Finding an address is not the same as validating it. Each address carries the source it was found through, which tells you how it was discovered - not whether it will land today. If deliverability matters before you send, that's a verification step - run the results through the Email Address Verifier before your first send.
Where domain-to-contact enrichment earns its keep.
Most account lists are company names and websites - which nobody can email. Running the domains through this returns named contacts with titles, so a list of accounts becomes a list of conversations. Ask for the categories that match who actually signs off on your product.
Old CRM rows rot: people move on, titles change, firmographics drift. Re-running your existing domains returns current contacts plus industry, size and revenue band, which lets you re-segment a stale database without buying a new one.
Partnership and hiring outreach fails at the general inbox. A named person with an address gets you past it, which is what this returns where it can - a name on 36% of rows and an email on 55%. Worth setting expectations honestly: the job title column came back empty on every row we measured, so route by the company signals instead and confirm the role yourself.
No subscription, no minimum, no per-seat licence. Your first 500 rows are on us - after that, pay-as-you-go.
Every new account, one-time. No credit card required. All scrapers unlocked - enough to enrich a real slice of your target list and see how well-covered your market is before committing.
Roughly $2 per 1,000 rows. Because contacts-per-company is yours to set, the cost of a run is something you control directly - the estimator prices it before you start.
Volume pricing, SLAs, dedicated workers and bespoke onboarding for teams keeping a large CRM enriched on a schedule. Tell us your numbers and we'll quote.
LIVESCRAPER10 at checkout.This service enriches a list you already have. These two are how teams build the list in the first place.
The company-level counterpart: site-wide emails and phones, the contact page, socials and tech stack as flat columns. Run it when you need to reach the organisation rather than a person.
Start from an industry and a location instead of a domain list, and get the companies themselves. The natural upstream step when you don't yet have accounts to enrich.
This page returns information about identifiable people, so it deserves a straighter answer than most.
Collecting business contact information that has been published publicly is long-established practice, and as long as the data is publicly available and the process doesn't disrupt the source there are no federal laws prohibiting it. That covers the collection.
What it does not cover is what you do next. A person's name and work email is personal data under GDPR and comparable regimes, and the obligations attach to you as the sender: you need a lawful basis for contacting them, you must say where you got their details if asked, and you must honour objection and erasure requests. CAN-SPAM and ePrivacy add their own rules on top depending on where they are.
We won't pretend a tool can grant you that basis - it can't, and any vendor saying otherwise is selling you a risk. What we do is keep the collection side clean: nothing behind a login, nothing bought, no third-party trackers on the data layer, and exports that auto-delete after 30 days.
The questions we hear most. Anything else? Talk to us - humans, not bots, write the answers.
example.com or a page URL on that site. Up to 1,000 per run, so a whole target list goes in as one job. You don't need a person's name; finding the people is the service's job.source telling you how it was discovered, and some carry first-seen and last-seen timestamps, which together tell you a lot about how current it is. What none of that tells you is whether it will accept mail today. If deliverability matters before you send, treat verification as a separate step - the Email Address Verifier is built for exactly that.info@ and support@ are a setting: include them, or restrict the run to addresses belonging to named individuals. For prospecting a person, personal-only is usually what you want.title column was empty on every row, along with the contact-level social handles. A name arrived on 36% of rows and an email on 55%. Build your import so a missing title is the normal case rather than a failure, and if the role matters to your outreach, plan to confirm it yourself.Paste your domains and get named contacts with titles, addresses and sources - plus the firmographics to segment them. Your first 500 rows are free, no card required.
Almost every B2B target list starts in the wrong shape. You have companies: names, websites, maybe an industry tag. What you need is people - someone with a name, a role and an address who can actually reply. Leads & Contacts Enrichment, also known as Contacts Finder, closes that gap. Submit up to 1,000 company domains in a single run and each one comes back enriched with flat rows built around a named individual where one is found, carrying an email address, the source it was discovered through, social handles and category tags. Alongside the people you get the company itself: industry classifications, founded year, headcount range, employee and revenue bands, company type and full location fields.
It is worth being clear about how this differs from the Email & Contact Scraper, because both services accept a domain and the choice between them decides whether a run is useful. The Email & Contact Scraper reads a company's own contact surface and returns it as flat columns - the addresses and phone numbers published on the site, the contact page, social accounts, the technologies the site is built with. That is the right tool for reaching an organisation. It does not identify who works there. This service does the opposite: it resolves a domain into individual humans, which is what prospecting, partnership outreach and recruiting all actually require. Teams frequently run both, using the company-level pull to reach a general inbox and the contact-level pull to reach a named decision-maker.
How deep each run goes is yours to set, and it maps directly onto cost. Contacts per company defaults to three, which is usually enough to reach someone without paying for an entire org chart, and emails per contact defaults to one, since additional addresses are often variants of the same mailbox. Generic inboxes such as info@ and support@ can be included or excluded, so a prospecting run can be restricted to addresses belonging to named people. Preferred contact categories let you ask for the kinds of contact that matter to you - the documentation gives technical and influencers as examples - and a skip setting pages further into companies you have already enriched rather than returning the same names twice.
Three caveats are worth absorbing before you build a pipeline on it. Contact records vary: a name and an address are dependable, while titles, socials and categories appear where they are found, so a missing title should be normal in your importer rather than an error. Firmographics are aggregated from what companies and directories publish about themselves, which makes them strong signals for segmentation rather than audited figures. And discovering an address is not the same as validating it - the source field tells you how an address was found, not whether it will accept mail today, so deliverability checking remains a separate step. Finally, remember that a named person's work email is personal data: collecting public business contact information is lawful, but the lawful basis for contacting someone sits with you as the sender, along with transparency and erasure obligations. We keep the collection side clean - nothing behind a login, no purchased data, exports auto-deleting after 30 days - and leave the outreach in your hands. Start free: your first 500 rows cost nothing and need no credit card.