Submit up to 1,000 domains and get one clean row per company - name, industry, headcount, founded year, revenue, funding raised, full address, phone, and the LinkedIn, Facebook and Twitter accounts. Twenty columns, flat, ready to segment.
Two services here accept a domain and return company information. The difference is what sits at the centre of the row.
Leads & Contacts Enrichment is people-first. Its job is to hand you named individuals with titles and email addresses; company details come along as a supporting block. Use it when the output you need is a person to contact.
This service is company-first, and it goes considerably deeper on the company itself. One flat row per domain with twenty columns - including several the enrichment service doesn't carry at all: a written description, the LinkedIn bio and company page, Facebook and Twitter accounts, a phone number, revenue, total money raised and the company's timezone.
So: scoring, segmenting and sizing a market is this page. Finding someone to email is the other one. They compose well - qualify the accounts here, then go find the people.
A domain is the only required input. There's no query syntax to learn.
A bare domain works - example.com. You don't need a company name or an ID.
No nesting to unpack on this one - every field is a top-level column, which is why it drops straight into a spreadsheet or a CRM import.
3.3B.America/Los_Angeles.20 fields per domain - every column above on every plan, including the free tier.
The columns are stable. Their contents need a little care, and it's cheaper to know now.
We've seen employees return an absolute count and a band - a number like 100000 for one company, a range like 50-100 for another. Parse for both rather than assuming an integer.
industry arrives normalised - the documented example is COMPUTER_SOFTWARE. Ideal for grouping and filtering; you'll want a display mapping before it goes in front of anyone.
A large public company fills nearly every column; a small private one fills a subset. Nothing is wrong when revenue or total_money_raised is empty - treat blanks as normal, not as failures.
Company Insights accepts optional enrichments, so a single run can go further than firmographics.
The documented enrichment options cover contact discovery and email validation - the same ground as Leads & Contacts Enrichment and the Email Address Verifier. Layering them here means one job instead of three, and one export instead of three joins.
Which route is better depends on what you're doing. If you want a qualified account list with contacts attached, enrich in place. If you're running the steps at different times - qualify this week, prospect next month, verify the morning you send - the dedicated services give you that control, and verification in particular is worth doing as late as possible.
Where twenty firmographic columns change a decision.
A rep's time is the expensive input. Enriching a raw domain list with headcount, industry, revenue and funding lets you sort it against your ICP first, so the accounts that get worked are the ones worth working - and the rest are archived rather than dialled.
Total addressable market arguments usually rest on a number nobody can source. Running every domain in a category and grouping by headcount band, industry token and country turns that into a figure you can defend line by line.
Most CRM records were created from a form that asked for an email and nothing else. Because the output is one flat row per domain, it maps cleanly onto existing account records - industry, size, location and socials backfilled without a migration project.
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, all twenty columns included - enough to enrich a real slice of your list and see how well your market is covered.
Roughly $2 per 1,000 companies. One row per domain makes this the most predictable service to budget in the catalogue - a thousand domains is a thousand rows, every time.
Volume pricing, SLAs, dedicated workers and bespoke onboarding for teams keeping a large account database current. Tell us your numbers and we'll quote.
LIVESCRAPER10 at checkout.Qualify the account here, then work down the list. Each step is a separate service so you can run them on your own schedule.
Once an account is qualified, this returns the named people at it - job titles, email addresses and the source each came from. The natural next step after scoring.
The last step before you send: checks each address against the mail server so a qualified, well-researched list doesn't bounce on arrival.
Facts about a business are not, for the most part, personal data - which makes this the least fraught service in the catalogue.
A company's industry, headcount, founding year, revenue band and registered address are facts about an organisation. Organisations don't have privacy rights in the way people do, and this information is published precisely so that customers, investors and partners can find it. Collecting publicly available business information is long-established practice.
Two honest caveats. First, a phone number or a company description can relate to an identifiable individual when the company is an individual - a sole trader or a one-person consultancy. Treat those rows with the same care you'd give contact-level data. Second, using firmographics to decide who to contact doesn't change your obligations for the contacting itself.
On our side: publicly available sources only, nothing behind a login, no third-party trackers on the data layer, and your exports auto-delete after 30 days.
The questions we hear most. Anything else? Talk to us - humans, not bots, write the answers.
example.com is enough. No company name, no registration number, no internal ID. Up to 1,000 per run, so a whole account list goes through as one job.revenue and total_money_raised are the usual blanks. Build your import so an empty column is normal.100000 for one company and a range like 50-100 for another. Parse for both. Similarly, values arrive as strings, so is_public reads as text rather than a native boolean.industry comes back as a normalised token - the documented example is COMPUTER_SOFTWARE - so grouping and filtering are reliable in a way free-text industry labels never are. You'll want a display mapping before showing it to anyone outside the team.Paste your domains and get twenty firmographic columns per company - enough to sort a raw list into the accounts worth working. Your first 500 rows are free, no card required.
A list of domains is not a list of prospects. It becomes one the moment you know how big each company is, what industry it sits in, where it operates and how much revenue it turns over - which is the gap Company Insights closes. Submit up to 1,000 domains in a single run and each comes back as one flat row carrying twenty columns: the company name, a written description, a normalised industry token, headcount, founding year, whether it is publicly traded, revenue, total money raised, a phone number, the full split address of street, city, state, postal code and country, the timezone, and the LinkedIn company page and bio alongside Facebook and Twitter accounts. Because the output is genuinely flat, with no nested arrays to unpack, it drops straight into a spreadsheet or a CRM import without transformation.
It is worth understanding how this differs from Leads & Contacts Enrichment, because both services accept a domain and the choice determines whether a run answers your question. Leads & Contacts Enrichment is people-first: its purpose is to return named individuals with job titles and email addresses, and it carries company details as a supporting block. Company Insights is company-first and goes considerably deeper on the organisation, including several fields the enrichment service does not carry at all - the description, the LinkedIn bio and company page, Facebook and Twitter accounts, a phone number, revenue, total money raised and timezone. In practice the two compose: qualify and score accounts here, then go and find the people at the ones that survive the filter, and verify their addresses immediately before you send.
Three things are worth knowing before someone writes the importer. Headcount arrives in two shapes - an absolute count for some companies and a band for others, so parse for both rather than assuming an integer. Values come back as strings, which means a field like is_public reads as text rather than a native boolean. And the industry field is a normalised token rather than a human-readable label, which is exactly what you want for grouping and filtering but does need a display mapping before it appears in front of anyone outside the team. Coverage also tracks how much a company publishes about itself: a large public company fills nearly every column while a small private one fills a subset, so an empty revenue or funding column should be treated as normal rather than as a failed lookup.
Typical uses fall into three shapes. Sales and revenue-operations teams enrich a raw domain list before anyone works it, sorting against an ideal customer profile so that expensive rep time goes to accounts worth the call. Strategy and finance teams run every domain in a category and group by headcount band, industry and country to produce a market-size figure that can be defended line by line rather than asserted. Marketing operations teams backfill CRM records that were originally created from a form asking for nothing but an email address, which the flat one-row-per-domain output makes straightforward. On the legal side this is the lightest-touch service in the catalogue: facts about an organisation are largely not personal data, and this information is published so that customers and partners can find it. The exceptions worth care are sole traders and one-person consultancies, where company details and an individual overlap. We use publicly available sources only, touch nothing behind a login, and your exports auto-delete after 30 days. Start free: your first 500 rows cost nothing and need no credit card.