When uploading contacts or working with profile properties in PredictaMail, it’s important to understand the different data types we support. Using the correct format ensures accurate data mapping, better segmentation, and a smooth import experience.
This article explains the supported data types in PredictaMail and how to structure each one properly—especially when importing data via CSV.
Where Data Types Are Used
Data types appear when:
Mapping columns during a contact import
Creating custom fields or properties
Filtering contacts in segments
Sending customer data via integrations or API
Each field is assigned a data type, which defines how the information is stored and interpreted.
Supported Data Types in PredictaMail
Below is a breakdown of all available field types in PredictaMail, including when to use them and how to format your data for import.
1. Text Input
A single-line text field used for short, simple strings.
Use it for:
First or last names
Email addresses
Cities
Job titles
CSV Example:
Email,First Name
jane@example.com,Jane
john@example.com,John
Use Text Input for values that don’t require line breaks and are under ~255 characters.
2. Text Area
A multi-line text field used for longer responses or descriptions.
Use it for:
Customer notes
Special instructions
Product feedback
CSV Example:
Email,Notes
jane@example.com,"Loyal customer, prefers email over SMS."
Text Area can handle longer values and line breaks if needed.
3. Date
Used for date-only fields. Format as YYYY-MM-DD.
Use it for:
Birthdays
Signup dates
Renewal dates
CSV Example:
Email,Birthday
jane@example.com,1992-08-07
Make sure all entries follow the same date format.
4. Date Time
Used when you want to capture both date and time. Format as YYYY-MM-DD HH:MM:SS.
Use it for:
Event timestamps
Last login date/time
Purchase date and time
CSV Example:
Email,Last Login
jane@example.com,2025-08-07 14:35:00
Useful for flows or segmentation based on exact times.
5. Boolean (True/False)
Boolean fields represent binary values—true or false.
Use it for:
Marketing consent
Subscribed status
Is customer VIP
Accepted values:
True: true, 1, yes, y
False: false, 0, no, n
CSV Example:
Email,Subscribed
jane@example.com,true john@example.com,false
Values are not case-sensitive, and common alternatives like "1"/"0" are supported.
6. Number Input
For numeric values like counts or scores. Must be integers (no decimals).
Use it for:
Number of purchases
Age
Loyalty points
CSV Example:
Email,Purchase Count
jane@example.com,5
john@example.com,12
Do not include commas, currency symbols, or decimal points.
Why Formatting Matters
Proper formatting ensures that:
Fields are imported without errors
Segments and filters work as expected
Custom properties store data correctly
Automations run based on accurate criteria
Incorrect formats may result in:
Failed imports
Unrecognized values
Broken segmentation logic
Still Have Questions? If you're unsure which data type to use for a property or need help formatting your CSV, reach out to us at support@predictamail.ai — we’re here to help!