Use Case

Lead Generation Verification

Verify the lead before it reaches the CRM or a sales rep.

The Problem

Lead generation collects email addresses from the least trustworthy places on the internet and then feeds them straight into the system your revenue team depends on. Whatever gets past the form ends up in the CRM, in a sequence, and eventually on a rep's call list.

Every source fails in its own way

Web forms. People typo. People also lie deliberately, because they want the whitepaper and not the follow up, so they type a fake address or a disposable inbox that expires the same day.
Scrapers and enrichment guesses. A lot of prospecting data is not observed, it is inferred from a pattern like firstname.lastname@company.com. Some of those addresses are correct. Some of them never existed. They look identical in a spreadsheet.
Purchased and partner lists. You are buying somebody else's decay. Contacts who left the company, domains that lapsed, and in the worst case spam traps that will get your sending domain blocklisted the moment you mail them.
Events and webinars. Badge scans and quick registrations produce a lot of half-typed addresses and throwaway inboxes.

What happens once the bad lead is inside

Bad leads do not stay quietly in a table. They propagate.

The nurture sequence fires and bounces, against the same domain that sends your legitimate marketing and, quite often, your transactional mail. The MQL count inflates, so your funnel conversion rates are computed against a denominator full of records that were never people, and the forecast built on them is wrong. Lead scoring learns from noise. A rep spends the first ten minutes of their morning working a record that will never answer, and the second ten minutes logging the fact that it did not answer.

Then there is the cost you cannot easily see: if marketing is paying per lead, whether through ads or a lead vendor, you are paying full price for records that will never be contactable, and nobody has any evidence to renegotiate with.

The wrong place to catch it

The other half of the problem is that nobody owns it. Marketing counts the lead, sales works the lead, and operations is left to reconcile the two, so the record that was never real survives every review.

Most teams discover bad leads at the end, when the email bounces or the rep gives up. By then the record has already been created, routed, scored, sequenced and reported on. The cleanup is manual, it never finishes, and the reporting damage has already been done.

The Solution

Mailthentic sits between the lead source and the CRM, so the record that reaches your reps has already been checked.

At the form, in real time

Call the API from the form handler before you create the lead. The address is checked for syntax, for a domain that resolves and publishes MX records, and against over 800 disposable domains, which is exactly what the whitepaper downloader reaches for. Over 150 role-based prefixes such as info@, sales@ and admin@ are flagged, so a shared inbox does not get routed to a rep as if it were a named buyer. Catch-all and risky or invalid detection run as well, with a mailbox probe wherever the receiving server allows one. A typo can be corrected while the person is still on the page. A fake address never becomes a record.

In bulk, before you import

Scraped lists, purchased lists, partner lists and event exports go in as a CSV. Duplicates are removed before processing, so overlapping sources do not cost you twice. Every result returns the status, the reason, the SMTP response code and a confidence score. That gives you a routing rule rather than a coin flip: send the confirmed addresses to a rep, hold the unknowns in a lower priority nurture, discard the invalid and the disposable, and do it before any of them touch the CRM.

The honest limits, which are also the useful ones

Catch-all domains accept every address they are offered, so nobody can confirm an individual mailbox behind one. Mailthentic reports them as catch-all rather than counting them as valid, which matters most on inferred addresses, because a pattern-guessed address at a catch-all domain is exactly the record that looks safe and is not. Gmail, Google Workspace, Outlook and Microsoft 365 return 250 OK even for addresses that do not exist, as an anti-harvesting defence, so the mailbox cannot be confirmed by SMTP and we say so. Greylisting responses (421, 450, 451) are temporary deferrals, not rejections, so we retry with a backoff rather than throwing away a real lead.

Round trip through the CRM

Connect Brevo, HubSpot, Salesforce, Mailchimp or PlusVibe. Pull a list of existing leads, verify it, and push the verdicts back onto the records, so the state of the data lives in the system your team actually works in. Pay-as-you-go credits never expire, or run a monthly plan. Contact data is never sold, shared or reused, and the service is GDPR aligned.

Key Benefits

Check the lead at the form, in real time, so fake and disposable addresses never become CRM records at all
Reps stop spending their day on records that were never contactable, and lead scoring stops learning from noise
Funnel and MQL numbers are computed against a denominator of real people, so the forecast built on them means something
Verify scraped, purchased and partner lists before import, including the pattern-guessed addresses that look safe and are not
Catch-all domains are labelled honestly, which is where inferred addresses hide their biggest risk
CRM round trip with Brevo, HubSpot, Salesforce, Mailchimp and PlusVibe, so verdicts live on the record your team works from

Frequently asked questions

Where should verification sit in the lead flow?

Before the CRM record is created. Call the API from the form handler for inbound leads, and run bulk CSV verification on any scraped, purchased, partner or event list before you import it. Catching a bad lead after it has been routed, scored and sequenced means the reporting damage is already done.

Can you verify addresses that were guessed from a name pattern?

Yes, and this is where verification earns its keep. Pattern-guessed addresses like firstname.lastname@company.com look identical to real ones in a spreadsheet. Syntax, domain, MX and mailbox checks separate them, except on catch-all domains, where we tell you plainly that the mailbox cannot be confirmed by anyone.

Is it safe to mail a purchased list after verifying it?

Verification removes the invalid, disposable and dead-domain records, which reduces the technical risk of bouncing. It does not create consent, and it cannot certify that every trap is gone. Treat a purchased list carefully regardless, and make sure your use of it is lawful in your jurisdiction.

Should role-based leads like info@ go to a rep?

That is your call, and Mailthentic gives you the flag on over 150 role prefixes so you can make it. They are shared inboxes rather than named individuals, so most teams route them to nurture rather than to a rep expecting a person on the other end.

What about leads on Gmail or Microsoft 365?

Those servers return 250 OK even for addresses that do not exist, deliberately, so the mailbox cannot be confirmed by SMTP. We report it as unconfirmed rather than guessing. The syntax, domain, disposable and role checks still apply and still catch real problems on those addresses.

Can I clean the leads already in the CRM?

Yes. Connect Brevo, HubSpot, Salesforce, Mailchimp or PlusVibe, pull the list, verify it and push the verdicts back onto the records. Duplicates are removed before processing, which CRM exports tend to be full of.

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