Customer List Health Checker for a Better Audience Match Rate

How to check your list's audience match rate before upload

Your audience match rate is decided by the list you upload. This checker reads the whole file, scores it out of 100, and shows every row that can't match, using the formatting rules from Google's Customer Match troubleshooting page, Meta's customer data guide and TikTok's customer file help.

1. Load the list. Any store, CRM or email-tool export. The sample shows typical problems.
2. Confirm the columns. Make sure every email and phone column you plan to upload is picked.
3. Pick the platform. Google, Meta and TikTok have different minimum sizes, and the score uses the one you choose.
4. Read the report card. The score, valid emails, phones with a country code, and rows with each problem.
5. Fix it. Download the corrected list, the rows with problems, or send the corrected list straight to the formatter for Google, Meta or TikTok.

Fix common email domain typos in bulk

Typos like gmial.com, hotmial.com or yahoo.con come from checkout and signup forms. They never match anyone. The checker lists each misspelled domain with its row numbers. Obvious ones are fixed in the corrected download; unsure ones (for example gmailll.com) are only flagged, so you can check them.

How the score works

The score is our own estimate, not a match rate from Google, Meta or TikTok. It starts at 100 and loses points for the share of rows with each problem — most for rows with no usable ID, then invalid emails and phones, then duplicates, typos, test, role and throwaway emails, broken characters, a missing country column and a list below the platform minimum. Hashed values count as usable but can't be checked.

What to do next

1. Click a Fix it button. The corrected list opens in the formatter for Google Customer Match, Meta or TikTok, which adds country codes, removes duplicates and builds the upload file.
2. Fix the source. Use the rows-with-problems download to correct emails and phones in your CRM or store, so the next export starts clean.
3. Stop typos at signup. Turn on email confirmation or a "did you mean" check in your forms, and ask for phone numbers with a country picker.
4. Re-check before every upload. Lists decay as people change email addresses.

Why audience match rates drop

Meta custom audience match rate is low

Meta's match score is matched rows divided by uploaded rows, so every dead row pulls it down. The biggest fixes are phone numbers with a country code, a country column, and more than one identifier per person. Meta suggests adding more emails, phone numbers and device IDs.

Google Customer Match list size is much smaller than the file

Google counts only matched people who are active on its services, so the list size is always smaller than your row count. A very large gap points to formatting problems: typos, phones without country codes, or a badly pre-hashed file.

Role-based email addresses

B2B lists are full of info@ and sales@ addresses. They belong to teams, so they rarely match a personal account. They are counted separately so you can decide.

Duplicate customers

Order exports repeat a customer once per order. Duplicates make the list look bigger than it is and hide how many real people you have. The formatters merge them for you.

Test rows and broken characters

Addresses like [email protected], names like "Test User", and text like Zoë instead of Zoë come from staging stores and wrong file encodings. Remove test rows and export the file again as CSV UTF-8.

Audience too small to use

Even a clean list can be too small. TikTok needs 1,000 matched users before an audience is available, and Google needs 100 active matched people. Combine customer and subscriber lists if you have both.