ContactMonkey maps your CSV columns to default fields based on the column header names. Use these exact column headers (matching the spelling and capitalization):
Contact Identifiers (Required)
Use at least one:
| ContactMonkey Field | CSV Column Header | Data Set? |
|---|---|---|
| Email Address | No | |
| ✨ Phone Number | mobilePhone | No |
✨ Phone numbers must be in E.164 format - learn more here.
Basic Contact Information
| ContactMonkey Field | CSV Column Header | Data Set? |
|---|---|---|
| Display Name | displayName | No |
| First Name | firstName | No |
| Last Name | lastName | No |
| Employee ID | employeeId | No |
Location Information
| ContactMonkey Field | CSV Column Header | Data Set? |
|---|---|---|
| Street Address | streetAddress | No |
| City | city | Yes |
| State | state | Yes |
| Postal Code | postalCode | No |
| Country | country | Yes |
| Office Location | officeLocation | Yes |
| Location | location | Yes |
Organizational Information
| ContactMonkey Field | CSV Column Header | Data Set? |
|---|---|---|
| Company Name | companyName | Yes |
| Business Unit | businessUnit | Yes |
| Department | department | Yes |
| Division | division | Yes |
| Job Title | jobTitle | Yes |
| Job Level | jobLevel | Yes |
Employment Details
| ContactMonkey Field | CSV Column Header | Data Set? |
|---|---|---|
| Employee Type | employeeType | Yes |
| Employment Type | employmentType | Yes |
| User Type | userType | Yes |
| Status | status | Yes |
| Exempt | exempt | Yes |
| Creation Type | creationType | Yes |
Dates (Format: YYYY-MM-DD)
| ContactMonkey Field | CSV Column Header | Data Set |
|---|---|---|
| Birthday | birthday | No |
| Hire Date | hireDate | No |
| Termination Date | terminationDate | No |
Additional Fields
| ContactMonkey Field | CSV Column Header | Data Set? |
|---|---|---|
| Preferred Language | preferredLanguage | Yes |
| Time Zone | timeZone | Yes |
| Usage Location | usageLocation | Yes |
| Preferred Data Location | preferredDataLocation | Yes |
| External User State | externalUserState | Yes |
Preferred Language and Multi-Language Emails
With Preferred Language Delivery, Preferred Language decides which version of a multi-language email each contact gets. Contacts without a recognized language get the email's default language.
You can add a preferred language in two places:
-
Contact CSV import: a
preferredLanguagecolumn saves the language on the contact for future sends. -
Recipient CSV: a
preferredLanguagecolumn in the CSV you upload when sending applies to that send only. It's used before the language on the contact record.
Accepted formats:
| Format | Examples |
|---|---|
| Language name in English |
French, Simplified Chinese, Brazilian Portuguese
|
| Language name in the language itself |
Français, Deutsch, 日本語
|
| Two-letter code |
fr, de, ja
|
| Code with a region or script |
fr-CA, pt_BR, zh-Hant
|
| Three-letter code |
fra, deu, eng
|
| Language name with a region |
French (Canada), US English, Chinese (Hong Kong)
|
- Capital letters, extra spaces and accents don't matter.
- Regional versions get the main language. For example,
fr-CAgets your French version. - Chinese for Hong Kong, Taiwan or Macau gets Traditional Chinese. Chinese with no region, or for mainland China or Singapore, gets Simplified Chinese.
- A value with two languages, such as
English/Spanish, uses the first one. -
UKorNoon their own aren't recognized. - Anything else that isn't recognized, such as
N/Aor a number, gets the default language. It never stops your upload. - A blank cell never clears a language already saved on a contact. Languages that come from Azure AD or Workday can only be changed there.
Understanding Data Sets
What are Data Sets?
Fields marked as Data Set: Yes provide a drop-down selection when filtering, making it easier to create accurate lists.
Non-Data Set Fields
Fields marked as Data Set: No allow text entry with operators like "equals", "contains", "does not contain", etc.
Why does this matter?
When you create filtered lists, data set fields show all possible values in a dropdown, preventing typos and speeding up list creation.
Understanding Column Data Types
ContactMonkey scans the first several rows of each column to determine the data type (text, number, date, etc.). This automatic detection affects how you can filter and use that field later.
Why This Matters
If the first few rows contain sample data that doesn't match the rest of your column, ContactMonkey may assign the wrong data type. For example:
- A column meant for employee IDs (numbers like 10234, 10235) but starting with "ID" or "TBD" in the first rows will be treated as text
- A column meant for text values (like department names) but starting with numbers in the first rows may cause filtering issues
Best Practices for Data Types
Before uploading your CSV:
- Remove placeholder values from the top rows (like "TBD", "N/A", or test data)
- Ensure the first 5-10 rows contain real, representative data for each column
- Check that number columns contain only numbers (no text)
- Format dates consistently using YYYY-MM-DD (example: 2024-10-15)
- Use E.164 format for phone numbers (example: +15555555555)
Custom Fields
Not seeing a field you need?
You can include additional columns in your CSV that aren't in the table above. ContactMonkey will create custom fields for any unrecognized column headers, which you can then use in list filtering.
Requirements for custom fields:
- Must include at least one identifier (Email or mobilePhone)
- Can use any column header name
- Will appear in the Directory after upload