Copper CRM CSV Import: Fix Google Workspace Upload Errors (2026)

Quick Answer

Copper CRM import failures fall into four categories: missing Name field on People records, tag values using the wrong separator (semicolons instead of commas), phone type labels that don't match Copper's accepted values, and custom field values that don't match the field's defined type.

Why it happens: Copper validates against its own field schema before accepting records, and some errors — like custom field type mismatches — fail silently rather than generating an error row.

The fix: Validate your People CSV against Copper's required field structure before uploading, particularly Name, phone type labels, and tag formatting.

Root cause: Copper's real problem isn't failed imports — it's imports that look successful but aren't. Tag separator issues and missing Name are among the most common causes of the failures you'll actually see in the error report, but the silent drops (wrong phone type, company name mismatch, custom field type errors) are the ones that corrupt your data invisibly.

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Fast Fix (90 Seconds)

If your Copper import failed or records arrived with blank fields, try this first:

1. Check if Name column is present and populated — Copper requires a Name value for every People record. Rows with a blank Name are rejected.
2. Check your Tags column separator — Copper expects comma-separated tags. If your source data used semicolons, do a find-and-replace: ; → , across the Tags column before reimporting.
3. Check your Phone Type values — Copper accepts: work, home, mobile, fax, other (lowercase). Any other value causes the phone field to fail silently.
4. Check for missing data in imported records — If records imported but have blank fields, that signals a column header mismatch or custom field type error, not a row rejection.
5. Reimport only the rows that failed or had blank fields — Use the error report to isolate the affected rows.

If more than 30% of your records have blank fields after import, continue below for the full diagnosis.

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TL;DR: Copper import failures are split between hard rejections (missing Name, invalid email) and silent failures (wrong phone type, custom field type mismatch, tag separator). Run your file through Data Validator to catch both categories before uploading.

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You import 600 contacts into Copper. The import completes with no errors. Then you open a few records and discover the phone numbers are blank. Or the tags didn't transfer. Or a custom field that was populated in your spreadsheet shows nothing in Copper. The import succeeded — technically — but your data didn't.

Copper has two failure modes: rows that are rejected outright (you see these in the error report), and rows that import successfully but with data silently dropped (you don't see these anywhere). The second category is more damaging because there's no error to diagnose.

CRM import files almost always contain customer contact information — names, email addresses, phone numbers, sometimes company details and deal notes. Most cloud-based CSV validation tools upload your file to a remote server to check it. Under GDPR Article 5(1)(c), that upload creates a data minimization exposure before you've confirmed the file is even correct. SplitForge validates in Web Worker threads running entirely in your browser — the file never reaches any server. You can confirm this in Chrome DevTools under the Network tab while the validation runs.

Each error type in this guide was reproduced using the Copper CRM import tool, March 2026. For the complete CRM import failure taxonomy across every major platform, see our CRM import failures complete guide. If your failures look structural rather than Copper-specific, Why Your CRM Rejects CSV Imports covers file-level causes. Teams migrating from HubSpot to Copper will find HubSpot CSV Import Contact Properties useful for understanding which field mappings need to change.

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What Copper CRM's Error Messages Actually Mean

"Name is required" — The Name column is empty or missing for a People record. Copper requires a Name on every person; rows without one are rejected.

"Invalid email format" — The email field contains a malformed address. Copper validates format before accepting the record.

Phone field blank after successful import (no error shown) — The phone type label in your CSV doesn't match Copper's accepted values. The row imports but the phone is silently dropped.

Tags missing after successful import (no error shown) — Tags were semicolon-separated in the source file. Copper expects comma-separated tags; semicolons are treated as part of the tag name rather than a separator.

"Company not found" (no error shown — field left blank) — You imported a People record with a Company association, but the company name doesn't match any existing Company record in Copper. The person imports; the company link is dropped.

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Copper Silent Failure Detection Checklist

Copper has two types of failures. Use this checklist to identify which type you're dealing with before debugging.

Records missing from Copper after import (hard rejection — check error CSV):

• Name column blank → row rejected. Add a Name value to every row before reimporting.
• Email malformed → row rejected. Fix email format ([email protected], no spaces).

Records imported but fields are blank (silent failure — no error shown):

• Phone blank → check Phone Type immediately. Any value not in the five accepted set (work/home/mobile/fax/other), or any capitalized value, drops the phone number silently.
• Tags wrong or missing → check separator immediately. Semicolons create one long tag name instead of multiple tags. Replace all ; with , in the Tags column.
• Company link missing → company name must match an existing Copper record character-for-character, including spaces and punctuation. Import Companies first, then People.
• Custom field blank → value type doesn't match field definition. Numbers in number fields, period-decimal (not comma-decimal), MM/DD/YYYY or YYYY-MM-DD for dates.
• Column data missing entirely → CSV header doesn't match Copper's field label. The column was accepted but mapped to nothing.

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Copper Accepted Phone Type Values

The rule is absolute: any value not in the five accepted set, or any value with capital letters, causes the phone number to import blank with no error message. There is no warning. You discover it by opening the contact record.

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Table of Contents

• Why Copper Fails Silently as Often as It Errors
• Fix 1: Missing Name Field
• Fix 2: Tag Separator Format
• Fix 3: Phone Type Label Errors
• Fix 4: Company Association Failures
• Fix 5: Custom Field Type Mismatches
• Common Scenarios
• Additional Resources
• FAQ

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This guide is for: Sales teams, CRM admins, and RevOps professionals importing contact data into Copper CRM.

Already know your error type? Jump to the fix section using the ToC above.

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Why Copper Fails Silently as Often as It Errors

Copper's import behavior differs from most CRMs in one important way: several common error conditions produce a technically successful import with blank fields, rather than an error report with rejected rows. This means the standard fix of "check the error report and fix the flagged rows" only catches a fraction of Copper import problems.

The hard-rejection failures (missing Name, invalid email) are easy to find — they appear in the downloadable error file after the import. The silent failures (wrong phone type, semicolon tags, company association misses, custom field type errors) require you to spot them in the imported records themselves. This is why a pre-import validation step matters more in Copper than in most CRMs.

What a Copper Import Failure Looks Like Before Cleanup

❌ BROKEN — Copper People import CSV with multiple failure types:

Name,Email,Phone,Phone Type,Tags,Company
Alice Chen,[email protected],+14155550100,work,"prospect;vip",Acme Corp
,[email protected],8005550199,cell,customer,Beta Inc
Carol Jones,[email protected],415-555-0100,Mobile,new lead,Gamma LLC
David Kim,,+14155550200,work,prospect,Delta Co
Emma White,[email protected],,work,,

Row 2: Name is empty → row rejected
Row 2: Phone type "cell" → not in accepted set; phone imports blank if row accepted
Row 3: Phone type "Mobile" → capitalized; should be lowercase "mobile"; imports blank
Row 1: Tags use semicolon → "prospect;vip" imports as a single tag named "prospect;vip"

FIXED:
Name,Email,Phone,Phone Type,Tags,Company
Alice Chen,[email protected],+14155550100,work,"prospect,vip",Acme Corp
Bob Smith,[email protected],+18005550199,mobile,customer,Beta Inc
Carol Jones,[email protected],415-555-0100,mobile,new lead,Gamma LLC
David Kim,,+14155550200,work,prospect,Delta Co
Emma White,[email protected],,work,,

Row 2 needed a Name value added. "cell" changed to "mobile". Row 3's "Mobile" became "mobile". The semicolon in Row 1's tags became a comma. None of these changes are obvious from looking at the data without knowing Copper's specific validation rules.

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Fix 1: Missing Name Field

Name is the only hard-required field for Copper People records. Every row without a Name value is rejected with an explicit error.

For People records, the Name field should contain the person's full name. Copper does not have separate First Name and Last Name fields in its standard import template — the full name goes in a single Name column. Imports from CRMs that export First Name and Last Name as separate columns need these merged before uploading to Copper.

❌ BROKEN — Salesforce contact export with separate name fields:

First Name,Last Name,Email,Phone
Alice,Chen,[email protected],415-555-0100
Bob,Smith,[email protected],800-555-0199
,Jones,[email protected],415-555-0101

Row 3: First Name empty — "Jones" alone imports as Name if Last Name used correctly,
        but First Name + Last Name must be merged into a single Name column for Copper

FIXED — concatenate First Name + Last Name into single Name column:
Name,Email,Phone
Alice Chen,[email protected],415-555-0100
Bob Smith,[email protected],800-555-0199
Carol Jones,[email protected],415-555-0101

Use Data Validator to catch blank Name fields across thousands of rows in seconds. The validator runs in your browser — your contact list never leaves your machine.

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Fix 2: Tag Separator Format

Copper expects tags to be comma-separated within the Tags column. This is one of the most common silent failures in Copper imports: the record imports successfully, but what you intended as two separate tags arrives as a single concatenated tag.

Semicolons are the most frequently seen wrong separator — they're used by many CRM exports and spreadsheet applications as a list separator in European locales.

❌ BROKEN — Tags column with semicolon separators:

Tags column values:
"prospect;vip"           → imports as 1 tag: "prospect;vip"
"customer;enterprise"    → imports as 1 tag: "customer;enterprise"
"lead;cold;Q2"           → imports as 1 tag: "lead;cold;Q2"

No error is shown. Records import. Tags are wrong.

FIXED — comma-separated:
"prospect,vip"           → imports as 2 tags: "prospect" and "vip"
"customer,enterprise"    → imports as 2 tags: "customer" and "enterprise"
"lead,cold,Q2"           → imports as 3 tags: "lead", "cold", "Q2"

The fix is a single find-and-replace in your spreadsheet before export: replace all semicolons in the Tags column with commas. If any of your tag names contain commas (rare but possible), enclose the entire field in double quotes.

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Fix 3: Phone Type Label Errors

Copper requires a Phone Type column alongside the Phone column. The Phone Type value must be one of five accepted labels: work, home, mobile, fax, or other. All must be lowercase.

A phone type value outside this set — whether a misspelling, a capitalized version, or a synonym like "cell" or "office" — causes the phone number to import blank with no error or warning.

❌ BROKEN — Phone Type values that fail silently:

Phone Type values that cause blank phone import:
"cell"      → not in accepted set; use "mobile"
"office"    → not in accepted set; use "work"
"Mobile"    → capitalized; must be lowercase "mobile"
"Work"      → capitalized; must be lowercase "work"
"direct"    → not in accepted set; use "work"
""          → empty type causes phone to be dropped

FIXED — accepted Phone Type values (all lowercase):
"work"
"home"
"mobile"
"fax"
"other"

If your source data has multiple phone columns (work phone, mobile phone), split them into separate rows in Copper format: one Name + Email row with Phone = work number, Phone Type = work; and a duplicate row with the mobile number if needed. Or use Copper's two-phone-field capability by including Phone 2 and Phone Type 2 columns.

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Fix 4: Company Association Failures

When you import a People record with a Company field, Copper looks for an existing Company record with that exact name in your account. If it doesn't find one, the company association is dropped silently — the person imports but is not linked to any company.

This is not a validation error; it's a lookup failure. Copper doesn't create a new Company record from a People import.

The fix is to import Company records first, then import People. The Company name in your People CSV must match the Company record's name in Copper character-for-character, including spacing and punctuation.

❌ BROKEN — Company association fails due to name mismatch:

People CSV company values vs existing Copper Company records:
"Acme Corporation"   ↔  Copper record: "Acme Corp."     → no match; link dropped
"Beta Inc"           ↔  Copper record: "Beta Inc."       → trailing period; no match
"Gamma, LLC"         ↔  Copper record: "Gamma LLC"       → comma difference; no match
"Delta Co"           ↔  Copper record: "Delta Co"        → exact match; links correctly

FIXED:
Update People CSV company names to exactly match Copper Company records, or
update Company records in Copper to match your import file before running the People import.

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Fix 5: Custom Field Type Mismatches

Copper custom fields have defined types: text, number, date, dropdown, and multi-select. A value that doesn't match the defined type is dropped silently — the record imports, the field is blank, and no error is reported.

❌ BROKEN — Custom field values that import as blank:

Custom fields configured in Copper:
- "Contract Value" (type: number)
- "First Contact Date" (type: date)  
- "Account Tier" (type: dropdown — values: Tier 1, Tier 2, Tier 3)

CSV values that fail silently:
Contract Value: "$12,500"    → currency symbol and comma; stores blank
Contract Value: "12,500"     → comma in number; stores blank
First Contact Date: "Jan 2026" → not standard date format; stores blank
Account Tier: "Premium"      → not in dropdown options; stores blank

FIXED:
Contract Value: 12500
First Contact Date: 2026-01-15   (or MM/DD/YYYY depending on your account locale)
Account Tier: Tier 1

For dropdowns, the imported value must exactly match one of the defined options. Adding "Premium" to the Account Tier dropdown before reimporting is the correct path if "Premium" is a valid tier you want to use.

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Common Scenarios

Google Workspace Sync: What It Overwrites and When

This is the most underserved topic in Copper's documentation and a common source of confusing post-import behavior. Copper's Google Workspace integration syncs contacts bidirectionally — meaning a contact you just imported via CSV can be overwritten or merged by the sync if the same email address exists in Google Contacts.

Three specific scenarios to watch for:

1. CSV import followed by Google sync overwrite. You import a contact with a corrected phone number via CSV. The Google sync runs and overwrites it with the old phone number from Google Contacts. Fix: update Google Contacts before or immediately after the CSV import, so the sync reinforces rather than reverses your changes.

2. Import creates duplicate when Google Contact has different email. The CSV has [email protected]. Google Contacts has [email protected]. Copper creates two separate records because the email doesn't match — no merge happens. Fix: standardize email addresses across Google Contacts and your import file before importing.

3. Company field sync conflict. Copper's sync pulls Company from Google Contacts' Organization field. If Google Contacts has a different company name format than your import file (e.g., "Acme" vs "Acme Corp"), the sync can blank or overwrite the company association. Fix: ensure Google Contacts and your CSV use the same exact company name string before importing.

❌ BROKEN — Import order that causes Google sync conflict:

1. Import CSV with [email protected], Phone: +14155550100, Company: Acme Corp
2. Google sync runs with: [email protected], Phone: 415-555-0100, Company: Acme
3. Result: Phone overwrites to 415-555-0100; Company link drops to "Acme" (no match)

FIXED — correct order:
1. Update Google Contacts to match your desired final state
2. Import CSV
3. Let sync reinforce the correct values, not overwrite them

Minimal Valid Copper People CSV

The smallest People CSV that Copper's importer accepts without errors or silent drops. Use this as your base template.

Name,Email,Phone,Phone Type
Alice Chen,[email protected],+14155550100,work

Rules for this template:
✓ Name: required, full name in single column
✓ Email: optional but recommended (enables dedup and Workspace sync)
✓ Phone: optional; include Phone Type whenever Phone is present
✓ Phone Type: must be lowercase — work / home / mobile / fax / other

❌ BROKEN variant (silent drop):
Name,Email,Phone,Phone Type
Alice Chen,[email protected],+14155550100,Work    ← capital W; phone imports blank

FIXED:
Name,Email,Phone,Phone Type
Alice Chen,[email protected],+14155550100,work    ← lowercase; phone imports correctly

For contacts with both a work and mobile number, include two phone rows with the same Name and Email, each with their own Phone Type.

Migrating from HubSpot to Copper

HubSpot exports contacts with separate First Name and Last Name columns. Copper expects a single Name column. Concatenate the columns before import. HubSpot's Lifecycle Stage field doesn't map directly to any Copper field — decide whether to use a custom field or a tag to preserve that data.

Importing a list with company and contact data together

If your source file contains both company data and contact data in the same rows, split it into two CSVs: one for Companies (Name, Phone, Website, Address) and one for People (Name, Email, Phone, Company). Import the Companies CSV first, then the People CSV. Copper creates the associations during the People import by matching company names.

Reimporting after discovering blank fields

Identify which fields are blank in the imported records, then find the root cause (phone type, tag separator, company name mismatch, or custom field type). Correct the source rows in your spreadsheet, then re-import just the affected records. Copper's duplicate detection uses email address — if the email already exists, choose "Update existing" to overwrite the blank fields without creating a second record.

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Additional Resources

Official Copper Documentation:

• Copper CRM — Import Contacts — Official People and Companies import guide
• Copper CRM — Custom Fields — Custom field types and configuration reference

Technical Standards:

• RFC 4180: CSV Format Specification — Official CSV structure standard
• ITU-T E.164 Telephone Numbering Plan — International phone format standard relevant to Copper's phone fields

Privacy & Data Protection:

• GDPR Article 5: Principles Relating to Processing of Personal Data — Data minimization principles for contact data handling

Tested: Copper CRM import tool, March 2026. Each error type reproduced against a Copper account with standard People and Companies imports, custom fields of each type, and an existing company database.

PLATFORM SPECIFICATION SOURCE
Platform: Copper CRM
Source: Copper Help Center — Importing Contacts into Copper
URL: https://support.copper.com/hc/en-us/articles/115001728531
Verified: March 2026
Next re-verify: June 2026

Values in this post reflect official documentation at the verification date.
Copper updates import behavior with product releases — the official source is authoritative.

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FAQ