Quick start
1
Gather your data
Use “Find Entities” to collect the data you want to analyze (like tickets from a specific client or time period).
2
Describe your analysis
Clearly describe what insights you want. For example: “Create a table showing ticket volume by category for the past month.”
3
Choose your approach
Either use “USE AI” to generate a script, select a pre-built template, or write your own Python code.
4
Configure output
Set up column names if you want a data table, and enable CSV export if you plan to email the results. To email results, enable CSV export and pair this action with “Notify Internal Team” using email delivery, so the CSV is attached.
How it works
This action processes data from previous workflow actions through a custom analysis:- Gathers data: Takes data from previous workflow actions (like “Find Entities”)
- Prepares for analysis: Makes data accessible to Python scripts with helper functions
- Executes analysis: Runs your chosen script (AI-generated, template, or custom)
- Produces results: Creates text summaries and optional data tables
- Prepares exports: Formats data tables as CSV files for email delivery if enabled
Setup
Analysis description: Describe what you want to analyze. This is crucial for AI-generated scripts and serves as documentation for custom scripts. Python code: The script that will be executed. Can be AI-generated, from a template, or written by you. Complex scripts can run slowly. Keep the code efficient. Report columns (optional): Specify column names if your script produces a data table for CSV export. CSV export (optional): Enable if you want data tables available as CSV files for email delivery.Example workflow
Monthly client report- Trigger: Scheduled workflow (monthly)
- Find Entities - Gather all tickets for a specific client from the past month
- Data Analysis - Generate a report with a ticket summary and resolution metrics
- Notify Internal Team - Email the report with the CSV attachment to the account manager
