analytics_insight_run

Tool

analytics_insight_run

Run a saved insight of the current product and return its numbers: every series executed over the resolved window and aligned onto the same buckets, the formula evaluated bucket by bucket, a total per series, optional series_labels keyed by series key, and whether the target was met. Grouped metric insights return ranked groups (top_n plus other for count/sum), and meta with group_by and group counts. Money stays raw at its scale; series_format tells the app how to convert and display it. When grouped by currency, each value group carries its own format and currency; mixed-currency headlines, formula totals, and the other group are null with a reason in meta. A funnel insight also returns steps: per series key, every step over the whole window with label, persons, conversion_from_first and conversion_from_prev — a step nobody reached is 0, never missing; its series and total remain the last step per bucket. A pivot insight returns pivot: rows {key, label, cells} per group value merged across series by exact string key (a cell is null where that series has no row), other (the rows past top_n), total and total_reasons, sort and meta {rows_total, rows_dropped, top_n}; a funnel series is one cell per step keyed <key>.<stepIndex> with series_steps labels, and step_pct on each row, on other and as total_step_pct gives each step cell over that row's first step (1 for step 0, null when step 0 is 0), so a cell reads 41 · 13.6 %; rows_label is the row-header title when the insight declares one. An insight with formulas returns formulas (per key, bucket by bucket; absent for a pivot, whose numbers are the cells f1..f4), formula_labels and formula_formats keyed by formula key in definition order, and each formula's total under total[key]; compare carries formulas and total[key] the same way. Totals are honest: count and sum are summed over all rows; count_distinct, avg and ratio are read ungrouped over the window; a grouped funnel's rows overlap (a person is in every group they entered by), so its step totals are the ungrouped funnel — distinct people — and its other is read on its own: the distinct people who entered by any group past top_n. Where a total cannot be read it is null with the reason in total_reasons (other follows the same rule), never a wrong number. A pivot has no buckets: series is empty and formula null. Missing count/sum buckets are zero. The window comes from the stored definition — relative windows and the current cycle are resolved at call time — and `from` and `to` override it for this call only, changing nothing stored. Use this rather than rebuilding the insight out of analytics_metric_query calls: the alignment and the formula are what make the numbers comparable.

Behavior

HTTP: POST /analytics/insights/:idOrSlug/run

Arguments

Name	Type	Required	Description
to	string	—	Inclusive window end; overrides the stored window
from	string	—	Inclusive window start; overrides the stored window
idOrSlug	string	•	The insight's slug, or its uuid

Response

Field	Type	Always
meta	object	—
extra	object	—
pivot	object	—
steps	object	—
total	object	•
groups	array	—
series	object	•
window	object	•
compare	object	—
formula	array	•
insight	object	•
formulas	object	—
formula_label	string	—
series_format	object	•
series_labels	object	—
target_status	string	•
formula_labels	object	—
filters_skipped	array	—
formula_formats	object	—

Try it

Run a saved insight of the current product and return its numbers: every series executed over the resolved window and aligned onto the same buckets, the formula evaluated bucket by bucket, a total per series, optional series_labels keyed by series key, and whether the target was met.

When to use

Example

Ask your agent something like this:

Run a saved insight of the current product and return its numbers: every series executed over the resolved window and aligned onto the same buckets, the formula evaluated bucket by bucket, a total per series, optional series_labels keyed by series key, and whether the target was met.

The agent will invoke analytics_insight_run with these arguments:

{
  "idOrSlug": "<idOrSlug>"
}