Clean Your Excel or CSV File Before Importing People and Organizations into Pipedrive

Before you upload contacts into Pipedrive, clean the messy people, organization names, emails, phone numbers, addresses, dates, and duplicate rows that can make mapping and importing harder.

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

Clean before the import

Standardize person names, organization names, emails, phone numbers, dates, and addresses before mapping them in Pipedrive.

Review suggested fixes

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

Export a Pipedrive-ready file

After cleaning, export your data in a format that is easier to map to Pipedrive people and organization fields.

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

Pipedrive imports rely on a structured spreadsheet where columns become fields and rows become records. If people, organizations, emails, phone numbers, and deal-related columns are mixed or inconsistent, the mapping step becomes harder and skipped entries are more likely.

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

People and organizations

Prepare person names, organization names, emails, phones, addresses, and related fields before upload.

Duplicate review

Find duplicate people or organizations before import by matching on email, phone, name, company, or any other column.

Cleaner mapping

Split and standardize columns so your spreadsheet is easier to match to Pipedrive person, organization, lead, or deal fields.

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 Pipedrive

Create a cleaner output file that is easier to upload and map in Pipedrive.

Pipedrive import prep checklist

  • Decide whether you are importing people, organizations, leads, deals, or a combination.
  • Make sure person names and organization names are in the right columns.
  • Clean primary email addresses and remove obvious fake or placeholder records.
  • Standardize phone numbers before import.
  • Review duplicate people by email or phone before uploading.
  • Review duplicate organizations by organization name or another identifier.
  • Split addresses into separate fields when possible.
  • Convert mixed date fields into one consistent format.
  • Check deal or lead fields such as value, stage, status, and expected close date if included.
  • Keep a clear header row so fields are easier to map in Pipedrive.

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
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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.

Pipedrive import cleaner FAQ

Can this prepare people and organization data for Pipedrive?▼
Yes. The tool is useful for cleaning contact and organization spreadsheets before you map them during a Pipedrive import.
Does it import directly into Pipedrive?▼
No. It prepares and exports a cleaner Excel or CSV file. You still upload that file through Pipedrive’s import process.
Can it help with leads or deals too?▼
Yes for cleanup. If your lead or deal data is in a spreadsheet, the cleaner can standardize dates, names, phone numbers, emails, and duplicate rows before import.
Does the free version include Pipedrive export?▼
The free version lets you try the cleaner and exporters on up to 100 records. Paid licenses remove the record limit.

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

Using a different CRM?

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

HubSpotSalesforceZohomonday
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