sheetcheck

Customer import check

Check customer imports for missing email columns, duplicate customer IDs, invalid country codes, and row count format issues.

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required
unique
required
allowedValues
pattern

Expected format 999-999-9999 — A = letter, 9 = digit, * = any character.

dateRange
rowCount

Customer ID column missing or renamed

Customer exports may use 'Account Number', 'CustomerNo', or 'ID' instead of 'Customer ID'. Without a stable customer identifier, duplicate checks and row matching cannot run reliably. The header must be present and consistent before checking.

Email column missing or blank

Some rows have no email address, or the email header is missing. A required check flags those rows so you can complete contact details before importing the customer list. If email is optional, edit the rule to reduce errors.

Duplicate customer ID values

The same customer ID appears more than once, often when a CRM export combines records from multiple sources. Duplicate rows make it difficult to know which record is current. Keep only one row per customer ID.

Country code values vary

One row uses 'US', another 'USA', and a third 'United States'. Inconsistent country codes cause downstream validation issues. Allowed value checks highlight values that fall outside the expected code set. Map all codes to a single two-letter list.

How to fix

FAQ

What columns are checked by default?

The default rules check Customer ID, Email, Country Code, Phone and Customer Since Date. The rules run against exact headers, so check that those exist and use consistent names. Customer Name is not checked by default, because a missing name is usually a record to review rather than a failed import.

Why is a missing email address flagged?

Email is a required field in the default check. If your import does not require email, edit the rule to a warning or remove it. Missing emails can otherwise cause avoidable errors before import.

Can I use full country names instead of codes?

The default allowed values use two-letter country codes such as US, CA, GB, and AU. If your file uses full names, update the allowed value list to match your import format. Consistency helps downstream validation.

What date format should I use for customer since dates?

Use ISO yyyy-mm-dd values for customer since dates. That avoids regional ambiguity and lets date range checks compare values correctly. Convert text or regional dates before running the checker.

What phone number format is expected?

The default pattern expects digits and dashes only, such as 555-123-4567. Remove spaces, parentheses, and letters before running the check. Consistent phone formats help keep customer contact data uniform.

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