Duplicate customer records look harmless until they change how people behave. A rep checks the CRM, sees an incomplete account, and keeps a private note. Finance has another version. Support has a third. Everyone believes their version is the safest one.
Why basic deduplication is not enough
Simple dedupe tools catch exact matches. Real duplicates are messier. Company names change. VAT numbers are missing. A parent company appears as several subsidiaries. A contact uses two emails. One record is correct on address and wrong on name.
The hard question is not whether two strings look similar. It is whether two records describe the same real-world customer.
The practical fix
- Map where customer records are created.
- Choose the fields that prove identity: domain, VAT number, address, phone, billing account, parent company.
- Use fuzzy matching and confidence scores.
- Send uncertain matches to review instead of guessing.
- Keep the matching rules running so the problem does not return.
Entity matching turns CRM cleanup from one-off admin work into a repeatable data process.
Lucendata helps companies merge duplicated customer records across CRM, finance, support, and spreadsheets without corrupting the source systems teams still rely on.