deals_get_deals_timeline
Group deals by day, week, month, or quarter to forecast revenue and analyze trends over time using a date field like expected close date.
Instructions
Get deals timeline grouped by intervals.
Returns open and won deals grouped by a defined interval of time set in a date-type field.
Workflow tips:
Useful for revenue forecasting and trend analysis
Group deals by day, week, month, or quarter
Use field_key to specify which date field to use (e.g., add_time, update_time, close_time, expected_close_date)
Filter by user, pipeline, or custom filter
Set exclude_deals to true to get only summary data
Use totals_convert_currency for multi-currency reporting
Common use cases:
Monthly revenue forecast: { "start_date": "2024-01-01", "interval": "month", "amount": 12, "field_key": "expected_close_date" }
Weekly deal creation trends: { "start_date": "2024-01-01", "interval": "week", "amount": 8, "field_key": "add_time" }
Quarterly sales pipeline: { "start_date": "2024-01-01", "interval": "quarter", "amount": 4, "field_key": "close_time", "pipeline_id": 1 }
User performance: { "start_date": "2024-01-01", "interval": "month", "amount": 6, "field_key": "won_time", "user_id": 123 }
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| start_date | Yes | The date when the first interval starts (YYYY-MM-DD) | |
| interval | Yes | The type of interval | |
| amount | Yes | The number of intervals to fetch | |
| field_key | Yes | The date field key to retrieve deals from | |
| user_id | No | Filter by user ID | |
| pipeline_id | No | Filter by pipeline ID | |
| filter_id | No | Filter by filter ID | |
| exclude_deals | No | Whether to exclude deals list (1) or not (0) | |
| totals_convert_currency | No | 3-letter currency code for converted totals |