Excel's Remove Duplicates button only catches rows that match character for character. Real data is rarely that tidy: 'Acme Inc.' and 'ACME Inc' or an email with a trailing space are the same record to you but different to Excel. That is how double-counted customers and inflated totals slip into reports.
Plumb is built on a simple idea: the data your business runs on should be trustworthy before anyone draws conclusions from it. Cleaning, checking and reshaping data should not need macros, scripts or a weekend. Plumb keeps your files private, shows every change it proposes, and lets you approve fixes instead of hunting for problems by hand.
How Plumb helps: Duplicate detection
Plumb's duplicate detection finds both exact and near-duplicates. It normalizes case, spacing and punctuation, compares records on the columns that matter, and groups likely matches with a confidence score so you decide which record to keep.
How It Works
Start with Excel's built-in tools for exact matches, then look for near-duplicates.
- Select your table and go to Data > Remove Duplicates. Tick only the columns that define a unique record (for example, Email rather than every column).
- To review before deleting, add a helper column: =COUNTIFS(A:A, A2, B:B, B2)>1 and filter for TRUE.
- In Excel 365, =UNIQUE(A2:D500) returns a de-duplicated copy without touching the source.
- Normalize first to catch near-duplicates: =LOWER(TRIM(A2)) on key columns, then run Remove Duplicates on the normalized column.
- In Plumb: upload the file, pick the key columns, review grouped duplicates with match scores, and choose keep-first, keep-latest or merge.
Where This Helps
Customer lists
Merge 'J. Smith' and 'John Smith' at the same email so each customer is counted once.
Order logs
Catch orders imported twice from overlapping exports before they inflate revenue.
Inventory
Find SKUs entered with different spacing or case that are really the same product.
Try Plumb in early access
Plumb is in early access. Join the waitlist on tryplumb.pro to get an invite. Early access covers Excel (.xlsx), CSV and JSON files, and we are adding more sources as people ask for them. Your files are processed privately and are never used to train models.
Count every record once
Now you have a repeatable way to do it, by hand or with Plumb. Join the waitlist and tell us what your data looks like; we read every reply.
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