Detect Duplicate Shopify Customer Accounts and Clean Up Your Data
Repeat customers who check out with a second email fragment your data — inflating customer counts and hiding their true lifetime value. This workflow finds likely duplicates by matching name, phone and address, and flags them for a one-click merge.
- 1
Pull all customers weekly
A
Schedule Triggerand aShopifynode fetch your full customer list with phone and default address. - 2
Fingerprint each customer
A
Codenode builds a normalized key from last name + phone + street, then groups customers sharing a key. - 3
Keep only real collisions
Output groups with two or more accounts that share a fingerprint but have different emails — your likely duplicates.
- 4
Write a review list
Append each suspected duplicate pair to a
Google Sheetwith both emails, order counts and combined spend. - 5
Nudge yourself to merge
A
Slackmessage summarizes how many duplicates were found so cleanup actually happens.
Frequently asked questions
Does it merge automatically?
No — merging is destructive, so this flow only detects and lists. You review the sheet and merge in Shopify with confidence. You can add an auto-tag step so both accounts are labelled 'possible-duplicate' for staff.
How does it avoid false matches?
It requires two independent signals to agree (e.g. phone + street), not just a shared surname. You can tighten or loosen the fingerprint in the Code node.