Merge Two Contact Lists Into One

Paste two lists together and you get a second header row, the same people twice, and records that disagree. This example works through a fictional merge and keeps every disagreement visible.

ℹ️ A worked example you can check. The before and after tables below were produced by the free tool on this site from a fictional sample file. Open the same file yourself and you will get the same result.

What Usually Goes Wrong

• The second list's header row sitting in the middle of the file
• The same person in both lists, identical
• The same person in both lists, with one list missing the phone number
• The same person with two different companies
• Different capitalization between the two sources

The Sample File, Before

10 rows of fictional data with the problems above. Every person and company is invented.

Open This File in the Workspace Download the CSV

Merge Two Contact Lists Into One sample before cleaning
Name	Email	Phone	Company
Amara Nwachukwu	amara@nwachukwu-example.com	+14045550121	Nwachukwu Example Co
Björn Sandvik	bjorn@sandvik-example.no	+4722555012	Sandvik Example AS
Clara Whitcombe	clara@whitcombe-example.co.uk		Whitcombe Example Ltd
Diego Fuentes	diego@fuentes-example.es	+34915550124	Fuentes Example SL
Name	Email	Phone	Company
Amara Nwachukwu	amara@nwachukwu-example.com	+14045550121	Nwachukwu Example Co
clara whitcombe	Clara@Whitcombe-Example.co.uk	+442079460125	Whitcombe Example Ltd
Diego Fuentes	diego@fuentes-example.es	+34915550124	Fuentes Holding Example SA
Esme Laurent	esme@laurent-example.fr	+33155550126	Laurent Example SARL
Björn Sandvik	BJORN@sandvik-example.no

How to Clean It

1. Paste the second list under the first in one sheet, with the same column order, and save as CSV. Keep both originals.
2. Run the combined file with duplicates, lowercase emails, Merge duplicate emails and name capitalization.
3. Read the review list for pairs that disagree.
4. Decide each pair in the workspace's Review step: keep one row, or keep both.
5. Export the cleaned file and the change log, and keep the log with the originals.

Prefer the command line or an AI agent? The same result comes from smartdata-clean clean merged-lists.csv --dedupe-rows --lower-emails --merge-duplicate-emails --names. See tools for agents.

The Result

10 rows in, 4 removed, 6 out. The stray header and the identical repeat are removed. Björn's second row is dropped because it only had an email, which the first row already has. Clara's first row is dropped in favour of the more complete one with her phone number. Diego stays twice: the two lists name different companies, and only you know which is right.

Merge Two Contact Lists Into One sample after cleaning
Name	Email	Phone	Company
Amara Nwachukwu	amara@nwachukwu-example.com	+14045550121	Nwachukwu Example Co
Björn Sandvik	bjorn@sandvik-example.no	+4722555012	Sandvik Example AS
Diego Fuentes	diego@fuentes-example.es	+34915550124	Fuentes Example SL
Clara Whitcombe	clara@whitcombe-example.co.uk	+442079460125	Whitcombe Example Ltd
Diego Fuentes	diego@fuentes-example.es	+34915550124	Fuentes Holding Example SA
Esme Laurent	esme@laurent-example.fr	+33155550126	Laurent Example SARL

What the tool left for you

The tool listed these 2 items for a person to check:

• Row 9 shares an email with row 5 but has different Company. Both rows were kept. Decide which is right.
• Name capitalization was applied to "Name". If that column holds company names or acronyms, check the changes in the log.

Checked, not just claimed

The original file, the cleaned file and the change log were run through the separate verifier. Result: PASS.

✓ Removed rows with a valid, verified reason: 4 of 4
✓ Rows: 10 in, 4 removed with a logged reason, 6 out
✓ Cells compared: 24; changed: 2; every change matched to the log: yes
✓ Log entries: 7; not matching the files: 0

The verifier confirms that the change log explains every difference between the two files. It does not judge whether each cleaning choice suits your situation; that part is yours.

The cleaning report

Report text for the sample file

SMARTDATAAI — CLEANING REPORT
Source: merged-lists.csv (fictional practice data)

SUMMARY
Rows in (excluding header): 10
Rows out: 6
Rows removed: 4
  Exact duplicates: 1
  Repeated header rows: 1
  Duplicate emails that added nothing new: 2
Cells changed: 3
  Emails normalized: 2
  Names re-cased: 1

COLUMNS DETECTED
Email: Email
Phone: Phone
Date: none
Name: Name

NEEDS REVIEW
- Row 9 shares an email with row 5 but has different Company. Both rows were kept. Decide which is right.
- Name capitalization was applied to "Name". If that column holds company names or acronyms, check the changes in the log.

SAMPLE OF CHANGES (first 3 of 3)
Row 8 · Email: "Clara@Whitcombe-Example.co.uk" → "clara@whitcombe-example.co.uk"  [email]
Row 8 · Name: "clara whitcombe" → "Clara Whitcombe"  [name case]
Row 11 · Email: "BJORN@sandvik-example.no" → "bjorn@sandvik-example.no"  [email]

Values the tool cannot settle are left as they were and listed above. Where the day/month order of a date was worked out from other dates in the same column, that is listed above too.
Row numbers refer to the original file (header = row 1). Email checks cover format only; they do not confirm that a mailbox exists.

Where a Tool Stops and a Person Starts

When lists have different columns, different ID schemes or thousands of conflicts, the merge needs rules agreed with you first and a review pass afterwards. That is the Complex Cleanup service.

See Service Levels From $19 How We Check Our Work

The tool never copies a value from one row into another. It removes a row only when everything in it is already in the row that stays.