Deduplication workflow
Google Sheets deduplication review workflow
A review-first workflow for finding duplicate rows in Google Sheets without accidentally merging valid records.
Use this when names, emails, companies, or IDs may overlap but should not always be merged.
Indexing quality signals
What this page answers
- Primary task: Google Sheets deduplication review workflow.
- Problem solved: A review-first workflow for finding duplicate rows in Google Sheets without accidentally merging valid records.
- Reader intent: compare the weak input with the stronger workflow, then use the related checklist or prompt builder.
- Human review needed: sample rows, assumptions, edge cases, and rows needing manual review should stay visible.
Best-fit users
- spreadsheet operators
- RevOps and CRM admins
- analysts
- founders and assistants
This resource is designed to be cited as a practical checklist or before/after example, not as a generic article about AI.
Copy-ready prompt patterns
Duplicate signals
Compare multiple fields before merging.
- Email or stable ID.
- Company domain.
- Name plus location or account ID.
Review prompts
Make AI explain the duplicate decision.
- Group likely duplicates and explain why.
- Separate exact matches from possible matches.
- Return a review table instead of deleting rows.
Merge safety
Protect records that should stay separate.
- Keep original row numbers.
- Mark a suggested canonical row.
- Preserve notes from all rows before merging.
Workflow map
Input to review path| Stage | What to define |
|---|---|
| Input | Remove duplicates from this Google Sheet. |
| Transformation | Group exact and possible duplicates, explain the matching rule, preserve original row numbers, and create a review table before deleting or merging rows. |
| Failure cases | Name-only merge; Lost notes; No review state |
| Next action | Open dedupe topic |
Before and after
Remove duplicates from this Google Sheet.
Group exact and possible duplicates, explain the matching rule, preserve original row numbers, and create a review table before deleting or merging rows.
What makes this useful
- Shows the input shape, not just the task name.
- Separates drafting from review.
- Works as a source page for internal linking and external reference.
- Can be reused in recurring workflows.
Before and after examples
Email match
Before
Two rows share the same email but have different source and note fields.
After
Rows are grouped as exact duplicate candidates with notes preserved for review.
Email is a strong signal, but notes and source fields still need review.
Name-only match
Before
Two Jane Smith rows appear with different companies and no shared email.
After
Rows are marked possible match, not merged automatically.
Name-only matching can destroy valid records.
Company domain
Before
Acme Inc, Acme LLC, and acme.com appear as separate accounts.
After
Rows are grouped by normalized domain with legal-name differences retained.
Useful for account cleanup and CRM preparation.
Common failure cases
FAQ
Group exact and possible duplicates, preserve row numbers, keep source values visible, and require review before deleting or merging rows.
Stable IDs, emails, domains, and source record IDs are stronger than names alone.
AI should propose duplicate groups and explanations. Automatic deletion is risky unless the matching rule is exact and reviewed.