Importing Data

Bring your data into Twenty

Import data from CSV files, spreadsheets, or other CRMs to get started quickly with Twenty.

Import Overview

Twenty’s import tool helps you:

• Import CSV files - From Excel, Google Sheets, or exports
• Map fields - Match your columns to Twenty fields
• Handle duplicates - Skip, update, or create new records
• Preview data - Review before importing
• Track progress - Monitor import status

Preparing Your Data

Before importing, prepare your CSV file:

CSV File Requirements

File Format

• UTF-8 encoding
• Comma-separated (,)
• First row contains headers
• Max file size: 100 MB

Data Quality

• Clean data (remove formatting)
• Consistent date formats
• Valid email addresses
• Remove duplicate rows

Data Cleaning Tips

1. Remove unnecessary columns

   Delete columns you don’t need in Twenty.

2. Standardize formats

   Ensure consistency:

   Dates: YYYY-MM-DD (2026-03-15)
   Phone: [phone]
   Currency: 50000 (no $ or commas)
   Boolean: true/false or 1/0
   
3. Clean text fields

   Remove:

   • Extra spaces
   • Line breaks (unless intended)
   • Special characters that cause issues
4. Handle empty values

   Decide how to handle:

   • Leave blank or use default
   • “N/A” or actual empty

Importing Data

Step-by-Step Import

1. Navigate to import

   Go to the object you want to import to:

   • Companies, People, Opportunities, or custom object
   • Click Options (···) → Import
2. Upload CSV file

   • Click Upload CSV or drag and drop
   • File uploads and parses
   • See column preview
3. Map fields

   Match CSV columns to Twenty fields:

   CSV Column → Twenty Field
   "Company Name" → Name
   "Website URL" → Website
   "Industry" → Industry
   "Annual Sales" → Annual Revenue
   "Contact Email" → Email
   "Phone" → Phone Number
   

   • Auto-mapping suggests matches
   • Manually adjust as needed
   • Unmapped columns are skipped
4. Set duplicate handling

   Choose what to do with duplicates:

   Match by: Email, Name, or custom field

   When match found:

   • Skip - Don’t import duplicate
   • Update - Overwrite existing record
   • Create - Add as new record
5. Preview import

   Review sample records:

   • See how data will import
   • Check field mappings
   • Verify values look correct
6. Start import

   Click Import to begin.

   • Progress bar shows status
   • See success/error counts
   • Import runs in background
7. Review results

   Check import summary:

   Total rows: 1,000
   Successfully imported: 950
   Updated: 30
   Skipped (duplicates): 15
   Failed: 5
   

   Download error report for failed rows.

Field Mapping

Auto-Mapping

Twenty automatically suggests mappings based on:

• Column name similarity
• Data type compatibility
• Common field names

Example auto-mapping:

"Company" → Name
"Email" → Email Address
"Phone" → Phone Number
"City" → City
"State" → State

Manual Mapping

Adjust mappings when auto-mapping is wrong:

1. Click the dropdown for a CSV column
2. Select the correct Twenty field
3. Or choose Don’t import to skip

Field Type Compatibility

Text Fields

Accept any value:

CSV: "Acme Corporation"
Twenty: Name field (Text)

Number Fields

Require numeric values:

✅ Valid: 50000, 1234.56
❌ Invalid: "$50,000", "N/A"

Remove currency symbols and commas before importing.

Date Fields

Support multiple formats:

Supported:
- 2026-03-15
- 03/15/2026
- March 15, 2026

Time (Date/Time fields):
- 2026-03-15 14:30:00
- 2026-03-15T14:30:00Z

Boolean Fields

Accept various formats:

True: true, TRUE, 1, yes, YES, Y
False: false, FALSE, 0, no, NO, N
Empty: blank (no value)

Select Fields

Must match existing options exactly:

Field: Status
Options: Active, Inactive, Prospect

✅ CSV Value: "Active"
❌ CSV Value: "active" (wrong case)
❌ CSV Value: "In Progress" (doesn't exist)

Add new options before importing or they’ll fail.

Multi-Select Fields

Use semicolons to separate:

CSV: "High Priority;Client-Facing;Urgent"
Twenty: Tags field (Multi-Select)
Result: 3 tags applied

Relation Fields

Match by identifier:

CSV Column: "Company Name"
Twenty Field: Company (Relation)
Matching: By company name

If match found: Links to existing company
If not found: Can create new company or skip

Handling Duplicates

Duplicate Detection

Twenty identifies duplicates by comparing:

Primary matching fields:

• Email - For People
• Domain - For Companies
• Name - For any object
• Custom field - You specify

Duplicate Strategies

Skip Duplicates

Leave existing records unchanged:

Strategy: Skip

Existing: John Doe ([e-mail])
Import: John Smith ([e-mail])
Result: Import skipped, John Doe unchanged

Use when: Existing data is more accurate

Update Duplicates

Overwrite existing records:

Strategy: Update

Existing: 
  Name: Acme Corp
  Phone: [phone]
  Revenue: 1000000

Import:
  Name: Acme Corporation
  Phone: [phone]
  Revenue: 1500000

Result:
  Name: Acme Corporation (updated)
  Phone: [phone] (updated)
  Revenue: 1500000 (updated)

Use when: Import has newer/better data

Create Anyway

Allow duplicate records:

Strategy: Create Anyway

Existing: John Doe ([e-mail])
Import: John Doe ([e-mail])
Result: Second "John Doe" created

Use when: Duplicates are intentional (e.g., different roles)

This creates duplicate data. Clean up duplicates later if needed.

Import Examples

Example 1: Importing Companies

CSV File:

Company Name,Website,Industry,Employees,Annual Revenue
Acme Corp,acme.com,Technology,500,5000000
Global Inc,globalinc.com,Finance,1200,15000000
Startup LLC,startup.io,Technology,25,500000

Field Mapping:

"Company Name" → Name
"Website" → Website
"Industry" → Industry
"Employees" → Employee Count
"Annual Revenue" → Annual Revenue

Settings:

Duplicate Detection: By Website domain
On Duplicate: Update

Result:

• 3 companies imported
• If acme.com exists, it’s updated
• New companies created for others

Example 2: Importing People with Relations

CSV File:

First Name,Last Name,Email,Job Title,Company,Phone
John,Doe,[e-mail],CEO,Acme Corp,555-1234
Jane,Smith,[e-mail],CTO,Acme Corp,555-5678
Bob,Jones,[e-mail],Founder,Startup LLC,555-9999

Field Mapping:

"First Name" → First Name
"Last Name" → Last Name
"Email" → Email
"Job Title" → Job Title
"Company" → Company (Relation, match by name)
"Phone" → Phone Number

Settings:

Duplicate Detection: By Email
On Duplicate: Update
Relation Handling:
  Company not found: Create new company

Result:

• 3 people imported
• Linked to existing companies or new ones created
• If email exists, person updated

Import Best Practices

Start with a small test

Before importing thousands of records:

1. Create CSV with 10-20 test rows
2. Run import
3. Verify data looks correct
4. Check field mappings
5. Then import full dataset

Clean data before importing

Better to fix in source:

• Remove duplicates in CSV
• Standardize formats
• Validate emails and phones
• Fill required fields

Saves time and reduces errors.

Map all important fields

Don’t skip columns you’ll need later:

• Review all CSV columns
• Map everything relevant
• Unmapped data is lost

Choose duplicate strategy carefully

Consider your data:

• Skip: When existing data is authoritative
• Update: When import has latest info
• Create: When duplicates are valid

Review error reports

For failed rows:

1. Download error CSV
2. Fix issues
3. Re-import failed rows

Common errors:

• Invalid email format
• Number in text field
• Select option doesn’t exist
• Required field missing

Troubleshooting Imports

Import Failed

Common causes:

• File too large (>100 MB)
• Invalid CSV format
• Encoding issues (not UTF-8)
• Corrupted file

Solutions:

• Split large files
• Re-export as UTF-8 CSV
• Check file isn’t corrupted

Many Rows Failed

Check:

• Field type compatibility
• Required fields populated
• Select options exist
• Date formats correct

Download error report to see specific issues.

Relations Not Linking

Causes:

• Relation matching field incorrect
• Values don’t match exactly
• Related records don’t exist

Solutions:

• Verify matching field
• Check for typos/extra spaces
• Import related records first
• Enable “Create if not found”

Duplicates Created Unexpectedly

Causes:

• Duplicate detection field wrong
• Matching too strict (case-sensitive)
• Empty match fields

Solutions:

• Review duplicate settings
• Clean up duplicates after import
• Re-import with correct settings

After Importing

1. Verify data

   Check a sample of imported records:

   • Fields populated correctly
   • Relations linked
   • No obvious errors
2. Clean up duplicates

   If duplicates created:

   • Use duplicate management tool
   • Merge similar records
   • Delete true duplicates
3. Enrich data

   Add missing information:

   • Fill in optional fields
   • Update outdated info
   • Add notes and context
4. Set up workflows

   Automate future data entry:

   • Auto-assign records
   • Calculate scores
   • Send notifications

Next Steps

Exporting Data

Learn how to export data from Twenty

Data Migration

Migrate from other CRM systems