Clean Your Excel or CSV File Before Importing Contacts into HubSpot

Before you upload a contact list into HubSpot, clean the messy names, emails, phone numbers, addresses, dates, and duplicate rows that can turn into bad CRM records.

Free version available. Clean and export up to 100 records before you import into HubSpot.

Clean before the import

Standardize emails, phone numbers, names, dates, and addresses before they become part of your HubSpot CRM.

Review suggested fixes

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

Export a HubSpot-ready file

After cleaning, export your data in a format that is easier to map during the HubSpot import process.

CRM Data Cleaner runs in Excel. It is designed for businesses that already have contacts in spreadsheets and want cleaner data before moving it into HubSpot.

Why clean the spreadsheet before importing into HubSpot?

HubSpot imports work by uploading a spreadsheet and mapping your columns to HubSpot properties. If the spreadsheet already contains inconsistent emails, duplicate rows, mixed date formats, messy phone numbers, or combined address fields, those issues can follow the data into your CRM.

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

Email cleanup

Lowercase addresses, flag invalid emails, catch common domain typos, and separate extra email addresses for easier review.

Duplicate review

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

Cleaner mapping

Prepare columns like first name, last name, phone, address, city, state, ZIP, and dates before uploading.

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 HubSpot

Create a cleaner output file that is easier to upload and map in HubSpot’s import workflow.

HubSpot import prep checklist

  • Make sure each contact has a clean primary email address where available.
  • Separate multiple email addresses so you can decide how they should be mapped.
  • Split full names into first and last name columns if needed.
  • Standardize phone numbers before import.
  • Split addresses into street, city, state, and ZIP/postal code columns when possible.
  • Convert mixed date formats into one consistent format.
  • Review duplicate contacts before uploading the file.
  • Remove or fix obvious fake, test, or placeholder records.

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 full cleaner on a small HubSpot import file.
$0
no card needed

Includes

  • All cleaning tools
  • HubSpot exporter included
  • 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
Recommended for HubSpot
CRM Data Cleaner + HubSpot Exporter
Everything in Cleaner, plus a HubSpot-focused export option.
$128
pay once · 2 computers

Adds

  • HubSpot-ready export file
  • Cleaner mapping for contact imports
  • Skip manual reformatting before upload
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

  • Exporters for all 5 CRMs
  • HubSpot, Salesforce, Zoho, Pipedrive, Monday

Best value if you work with more than one CRM.

Buy $179

HubSpot import cleaner FAQ

Does this import directly into HubSpot?
No. CRM Data Cleaner prepares and exports a cleaner file. You still upload the finished file through HubSpot’s normal import process.
Can I use the free version for a HubSpot import?
Yes. The free version includes the cleaning tools and HubSpot exporter, but it is limited to 100 records.
Will this remove all duplicate contacts automatically?
It helps you find duplicate records by the field you choose, such as email, phone, name, or another column. You can review duplicate groups before removing rows.
Does this replace HubSpot’s own duplicate tools?
No. It is a pre-import cleanup tool. The goal is to reduce messy data before it reaches HubSpot, not replace HubSpot’s built-in import, mapping, validation, or duplicate management features.
What kinds of contact data can it clean?
It can clean or standardize emails, phone numbers, names, dates, addresses, and duplicate rows. It is especially useful when your contacts are coming from an old spreadsheet, exported CRM list, lead file, event list, or manually maintained contact sheet.

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

HubSpot is a trademark of HubSpot, Inc. ExcelGurus is not affiliated with or endorsed by HubSpot.

Using a different CRM?

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

See Excel Data Cleaner →
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