The Customer Data Suite is an Early Access feature. Contact your Account Executive for more information.
Best Practices
To help you get started with CDS, we provide a sample CSV that is correctly formatted.
Sample Data Overview
- mobile: Use E164 formatted phone numbers. The Lumary Engagement Console supports sending to any E164 formatted phone number (e.g. +61XX XXX XXX for Australian recipients)
- email: Email fields should be simple strings.
- first-names: While spaces in column headers are supported, hyphens are an accepted industry standard.
- datetime: Date fields follow the RFC 3339 format. These are converted to UNIX epoch timestamps in the Experience and Workflow Studio so you can perform datetime comparisons etc.
Type Inference and Validation
On upload, CDS automatically infers column data types. The ‘Fields’ step allows you to confirm and override these inferred types if necessary. Field data types are crucial for specific operations like number comparison in Criteria filters.
Supported column data types include:
- String
- Integer
- Decimal
- Date/time (RFC 3339)
If your date field is not automatically inferred, adjust the cell data in your CSV and re-upload.
Supported Date/Time Formats
CDS supports and validates date/time data columns against the RFC 3339 format. This format ensures consistent and accurate representation of timestamps. Examples of valid and invalid RFC 3339 date-time strings are provided to help you avoid common formatting issues.
Examples of Valid RFC 3339 Date-Time Strings
- Basic Date-Time Format with UTC
2024-06-17T13:45:30Z
- Date-Time with Fractional Seconds and UTC
2024-06-17T13:45:30.123Z
- Date-Time with Time Zone Offset
2024-06-17T13:45:30+02:00
Examples of Invalid RFC 3339 Date-Time Strings
- Invalid Date Format
24-06-17T13:45:30Z(year not in YYYY format)
- Invalid Time Format
2024-06-17T13:45Z(missing seconds)
If your settings fail validation, you can go back to change the column data types or re-upload the CSV.
Invisible CSV rows
CDS recognises each row as an experience. Remember to remove blank rows before you import the CSV file into CDS to prevent unintended experiences.