Your List Came Back Mostly Invalid: Is It the List or the Verifier?

When most of a list comes back invalid, look at the reasons before the percentage: they tell you whether the file was damaged, the list is old, or the check could not see the mailboxes. Each has a different fix, and only one of them means the list is bad.

Step 1: Open the file and look at ten rows

Before you read anything into the result, look at the addresses the tool checked. Many "mostly invalid" lists are file problems:

• Wrong column. The check read a name or a phone column as the address.
• Merged cells. Two addresses in one cell, so neither is valid on its own. Split multiple emails in one cell shows the fix.
• Broken characters. Encoding damage in a CSV opened and saved in the wrong program. Fix garbled characters in a CSV covers it.
• Trailing spaces or quotes around addresses.
• A header row counted as data, which is one invalid row, not a pattern.

If the file is damaged, fix it and run it again. Removing bad syntax, stray spaces and duplicates before you spend checks avoids paying to check rows that were never addresses.

Step 2: Read the reasons on the invalid rows

Count the invalid rows by reason. Each reason points somewhere different.

Reason	What it points to	What to do
Not a valid address (syntax)	A damaged or badly assembled file	Fix the file, run again
Typo domain	Sign-up slips such as gmial.com	Correct the obvious ones, check again
No mail server	Domains that no longer take mail: closed businesses, expired domains	The addresses are gone; remove them
Mailbox not found	People left, or the list is old	The list is stale; see below
Disposable address	Throwaway sign-ups	Remove from marketing sends

The send tier splitter will separate the rows that need a fix from the rest before you check. Valid, risky, invalid and catch-all: how to read the report explains the reasons in full.

Step 3: Think about where the list came from

A high invalid share is not surprising if the list is old, bought or scraped. It is surprising if you collected it last month.

• A list collected a long time ago. How fast B2B contact data decays explains why work addresses die fastest.
• A purchased or scraped list. Expect more invalid rows than on a list you built. Verify a purchased email list and verify scraped emails cover both.
• An inherited list. Verify an inherited or acquired database.
• A fresh list that is still mostly invalid. Look hard at the capture form. Something is letting junk in.

Writing the source down helps: the email list provenance log takes a few minutes and records it.

Step 4: Rule out a check problem

Sometimes the list is fine and the check is not. Signs to look for:

• All the invalid rows are on a few domains. Domains behind a security gateway, or that rate-limit checks, can be misread. Verify emails behind security gateways explains it.
• Large webmail providers. Some do not allow an honest check, so results are risky or unknown rather than invalid. If those rows came back invalid, treat the result with suspicion.
• The tool ran into a limit partway through. A run that stopped early can leave rows unchecked rather than invalid.

Why SMTP verification gets it wrong lists the ways a check can go wrong.

Step 5: Test a sample you can check yourself

Pick 50 to 100 invalid rows at random, from different domains. Pick a small test batch shows how. Then do at least one of these:

• Check them with a second verifier. If both agree, the result holds. If they disagree, the verifier results disagreement finder shows where.
• Look at a few by hand. A company site, or LinkedIn, will often show that the person left and the domain is gone.
• Send a very small test of a few of them from a domain you can afford to risk, and read the bounces. Do not send a large batch to rows you have been told are invalid.

If the sample confirms the result, trust it.

Step 6: Decide what to do with the list

• Remove the invalid rows from every send and put them on your suppression list. Remove bounced emails from a list covers keeping them off.
• Keep what is left. If 40% of a list is gone, 60% is still a list, and a smaller clean one sends better than a bigger bad one. Plan the send order for the remainder.
• Look for the source of the rot. If it is old data, schedule a re-check. How often to re-verify an email list gives a cadence.
• Do not buy a replacement list in a hurry. If a vendor's list was the problem, see how to verify a vendor's list before delivery and ask for credit under their terms.

If you have already sent

If the list was sent to before the check, read what to do after a high bounce rate first, and recover after sending to a purchased list if the list was bought.

Check the list

Run the list on the verify page and read the reasons: 100 free checks, Google sign-in, no card.