Clean Your Excel or CSV File Before Importing Contacts into monday CRM

Before you import contacts or leads into monday CRM, clean the messy names, emails, phone numbers, addresses, dates, and duplicate rows that can make board mapping and matching harder.

Free version available. Clean and export up to 100 records before you import into monday CRM.
Download free View paid options

Clean before the import

Standardize emails, phone numbers, names, dates, and addresses before mapping them to monday CRM columns.

Review suggested fixes

The tool suggests corrections where possible, then lets you review the results instead of blindly changing your data.

Export a monday-ready file

After cleaning, export your data in a format that is easier to map into monday CRM.

CRM Data Cleaner runs in Excel. It is designed for businesses that already have contacts in spreadsheets and want cleaner data before importing into monday CRM.
Excel Data Cleaner home page explaining how it standardises contact data, removes duplicates and exports CRM-ready files
Excel Data Cleaner workflow showing the eleven numbered steps with mapped, staged and approved progress for each one
Name cleaning options in Excel Data Cleaner, including proper casing and splitting titles and suffixes into their own columns
Review screen in Excel Data Cleaner comparing original emails and phone numbers with suggested corrections, flagged as typo, invalid, fake or valid
Exporting from Excel Data Cleaner, choosing CSV or XLSX format, an output folder and which columns to include
Before and after in Excel Data Cleaner, with the messy original contact sheet beside the standardised finalised data

Why clean the spreadsheet before importing into monday CRM?

monday CRM lets you import contacts and leads from Excel or CSV, then map spreadsheet columns to board columns and decide how to handle matches. If emails, phone numbers, dates, statuses, and names are inconsistent, it becomes harder to map the file cleanly or use matching rules confidently.

CRM Data Cleaner helps you clean the file first, then export a cleaner file that is easier to review and map during the monday CRM import process.

Cleaner contact columns

Prepare names, emails, phone numbers, dates, addresses, and notes before mapping them to monday CRM columns.

Duplicate review

Find duplicate contacts before import by matching on email, phone, name, or any other column in your file.

Cleaner board mapping

Standardize values before mapping to monday columns such as Email, Phone, Date, Text, Status, or Dropdown.

1

Open your current file

Start with your existing Excel or CSV contact list from an old CRM, spreadsheet, website form, or lead source.

2

Clean and review

Run cleanup tools for emails, names, phones, addresses, dates, and duplicates. Review suggestions before exporting.

3

Export for monday CRM

Create a cleaner output file that is easier to upload and map into monday CRM.

monday CRM import prep checklist

  • Make sure your file has a clear header row for mapping.
  • Clean primary email addresses and remove obvious fake or placeholder records.
  • Standardize phone numbers before import.
  • Split full names into first and last name columns if needed.
  • Split addresses into street, city, state, and ZIP/postal code columns when possible.
  • Convert date fields into a consistent format before import.
  • Review duplicate contacts by email or phone before uploading.
  • Standardize status, dropdown, source, or stage values before mapping.
  • Decide whether matching rows should be added, skipped, or updated during import.
  • Test with a small file first before importing a large list.

Every version cleans

Click any type for the full detail. The tool auto-suggests fixes wherever it can — you review and approve each one.

Emailscase, typos, validation, fakes▼
Far more than lowercasing. Each address gets a status (Valid, Typo, Invalid, Fake, Disposable, Multiple, Empty) with a suggested fix when possible:
  • Case & whitespace — lowercases and trims stray spaces.
  • Typo correction — 59 common domain misspellings across Gmail, Yahoo, Outlook, Hotmail, AOL, and iCloud.
  • Validation — flags malformed addresses (missing @, no domain, bad structure).
  • Fake detection — catches placeholder junk like test@test.com, asdf@asdf.com.
  • Disposable detection — flags throwaway inbox domains.
  • Multiple emails — keeps the first, moves extras to their own column for review.
JOHN@GMAIL.COM → john@gmail.com
dg@gmial.com → dg@gmail.com  (Typo)
sue@hotmial.com → sue@hotmail.com  (Typo)
test@test.com → flagged Fake
bob@x.com; sue@y.com → bob@x.com + 1 more
Phone numbers10-country formatting▼
Standardizes numbers to the format you choose, with country-aware detection for US, UK, Germany, France, Mexico, Brazil, India, Japan, China, and Australia.
  • Format styles — (555) 123-4567, 555-123-4567, 555.123.4567, or +15551234567.
  • Default country — fallback for numbers with no prefix; a Country column takes priority if present.
  • Country code column — optionally split the detected code into its own column.
5551234567 → (555) 123-4567
5551234567 → 555.123.4567
5551234567 → +15551234567
+44 20 7946 0958 → CC: +44 | 020 7946 0958
Namescase, split, merge, titles, suffixes▼
Handles names in whatever shape your data arrives — one full-name column or separate first/last.
  • Proper casing — fixes ALL CAPS or lowercase.
  • Split full names — break “Dr. Jane Smith III” into Title / First / Last / Suffix columns.
  • Merge — combine First + Last into one Full Name column when your destination needs it.
  • Titles — Dr., Mr., Mrs., Ms., Miss, Prof., Rev., Hon., Sgt., Capt., and more.
  • Suffixes — Jr., Sr., II, III, IV, Esq., PhD, MD, DDS, CPA, and more.
john SMITH → John Smith
Dr. Jane Smith → Dr. | Jane | Smith
James Wilson III → James | Wilson | III
First: john + Last: SMITH → Full: John Smith
Datesauto-detect, reformat, time handling▼
Turns a column of inconsistent dates into one uniform format.
  • Auto-detection — reads mixed input formats automatically.
  • Ambiguity resolution — set MDY / DMY / YMD so 03/04/2024 is never guessed wrong.
  • Target formats — YYYY-MM-DD, MM/DD/YYYY, DD/MM/YYYY, MM-DD-YYYY, or “March 15, 2024”.
  • Time handling — strip the time, move it to its own column, or keep it inline.
03/15/2024 → 2024-03-15
March 15, 2024 → 2024-03-15
15/03/2024 (DMY) → 2024-03-15
2024-03-15 14:30:00 → Date: 2024-03-15 | Time: 14:30:00
Addressesparse, split, multiple formats▼
Parses free-form addresses and outputs them the way your destination needs.
  • Output formats — separate Street/City/State/ZIP columns; Street + combined City-State-ZIP; a single full-address column; or normalize-only.
  • Apt/unit splitting — pulls Apt, Unit, Suite, Ste, #, Bldg, Floor, Rm, Dept, and more into a separate column.
  • ZIP handling — keep as 5-digit ZIP or preserve ZIP+4.
123 Main St Apt 4B, Springfield IL 62704-1234
 → Street: 123 Main St  Apt: 4B
 → City: Springfield  State: IL
 → ZIP: 62704  (or 62704-1234)
 or → single: 123 Main St Apt 4B, Springfield, IL 62704
Duplicatesfind & remove by any field▼
Find and remove duplicate records based on whichever field matters to you.
  • Match on any column — email, phone, name, or any field in your data.
  • Review groups — see matched records grouped together before anything is removed.
  • Keep one, remove the rest — clear out the extras based on your chosen match column.
3 rows with john@gmail.com → review group, keep 1, remove 2
match on Phone → same number across rows grouped & deduped
Free
Try the whole thing on small data.
$0
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Includes

  • ✓ All cleaning tools
  • ✓ All 5 CRM exporters
  • ✓ Find & remove dupes

Limited to 100 records.

Download free
CRM Data Cleaner
Clean and dedupe unlimited data. Export your cleaned file and import it wherever you need.
$99
pay once · 2 computers

Unlimited

  • ✓ Email, phone, name, date, address cleaning
  • ✓ Find & remove duplicates
  • ✓ Export your cleaned data as Excel or CSV
Buy $99
Most popular
CRM Data Cleaner + 1 Exporter
Everything in Cleaner, plus import-ready files for your CRM.
$128
pay once · 2 computers

Adds

  • ✓ Validated, CRM-spec-matched export file
  • ✓ Skip the manual reformatting and failed imports
Buy $128
CRM Data Cleaner Complete
Everything in Cleaner, plus import-ready files for any of the 5 CRMs.
$179
pay once · save $65

Adds

  • ✓ Validated import-ready files for all 5 CRMs
  • ✓ HubSpot, Salesforce, Zoho, Pipedrive, Monday

Best value if you work with more than one CRM.

Buy $179

Already own the CRM Data Cleaner? Add more exporters from inside the app.

monday CRM import cleaner FAQ

Can this prepare contacts for monday CRM?▼
Yes. The tool cleans your spreadsheet first, then lets you export a cleaner Excel or CSV file that is easier to map into monday CRM.
Does it import directly into monday CRM?▼
No. It prepares and exports a cleaner file. You still upload that file through monday CRM’s import process.
Can it help with matching and duplicates?▼
Yes. You can find duplicates before import by matching on email, phone, name, or any other column, then decide what to keep before uploading.
Does the free version include monday CRM export?▼
The free version lets you try the cleaner and exporters on up to 100 records. Paid licenses remove the record limit.

monday.com and monday CRM are trademarks of monday.com Ltd. ExcelGurus is not affiliated with or endorsed by monday.com.

Using a different CRM?

The same tool exports for all five. These guides cover what each importer expects.

HubSpotSalesforceZohoPipedrive
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