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Importing data into Foxly: a step-by-step guide for CSV import with custom fields

Importing data into Foxly: a step-by-step guide for CSV import with custom fields

The Foxly: Requirements Backlog Prioritization, Planning Poker app empowers users to prioritize issues using predefined templates like ICE and RICE or custom templates tailored to their needs. Each template allows for various types of metrics, such as numbers, ratings (stars), short text, or labels. By default, these metrics are stored in Foxly's dedicated custom fields. Still, linking them to custom fields, even when using metrics like labels or ratings, can also be linked to Jira custom fields for seamless integration.

In this article, we’ll explore how users can import data into Foxly templates by linking them to custom fields, even when using metrics like labels or ratings.

Understanding Foxly’s custom fields

When the Store values in custom field option are enabled in a template, Foxly creates two corresponding custom fields:

  • Label field: Stores the textual representation of the metric.

  • Value field: Stores the numeric value of the metric.

These fields follow the naming pattern:
<Metric Name> - <Template Name> Label and <Metric Name> - <Template Name> Value.
For example:

  • Impact - ICE Label

  • Impact - ICE Value

Exception

The Number metric is linked to a single custom field without requiring separate fields for label and value.

Importing data into Foxly from a CSV file

If you have a CSV file containing pre-existing data (for example, before adopting Foxly), you can import this data into a Foxly template—even when using metrics like labels or ratings. To do this, link your data to the Value custom field.

Example Scenario

Imagine you’re using the RICE template, which includes:

  • Rating metrics

  • Number metrics

  • Two label metrics

You have a CSV file with backlog data from before using Foxly and want to import it into the RICE template.

Step-by-step guide to importing data

1. Prepare your CSV file

Ensure your CSV file contains columns corresponding to the metrics in your Foxly template.

CVS file data

2. Access the CSV import feature

Navigate to Jira's CSV File Import feature. Avoid using the default Bulk Create: Setup option, as it does not recognize Foxly's custom fields.

CVS File import panel
Bulk create Setup process

3. Upload your CSV file

Attach the prepared CSV file and proceed to the next step. Select the project where you want the data to be imported.

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4. Map CSV columns to Foxly fields

In the mapping step, link your CSV columns to the corresponding Foxly Value custom fields. For example:

  • Impact → Impact - RICE Value

Proceed to the next step and start the import.

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5. Review the Results

Once the import is complete, the data from your CSV file will be reflected in the corresponding Foxly fields.

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Important Notes

  • Remember to check the Store values in custom field option to create custom fields.

  • Ensure your CSV file is formatted correctly to avoid mapping errors during import.

By following these steps, you can seamlessly integrate legacy data into Foxly, ensuring your team has a unified and efficient prioritization process.