Analyze Key Drivers
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Version 4.0.26.6 (latest)
Analyze Key Drivers
Identifies the dimensional segments that most significantly drove a metric's change between two time periods.
Given a data source (a saved query or a model/explore pair), a contribution metric, and a list of
dimensions to analyse, this endpoint compares a test (breach) period against a control (baseline)
period and returns a ranked list of segment-level insights.
Each insight reports the metric value in both periods, the absolute and relative difference,
the unexpected deviation (how much a segment over or under-performed relative to the overall trend),
its proportional contribution to the total change, and its a-priori support (what share of total volume that segment represents).
Defines the Looker dataset. Must provide either query_id OR (model_name + explore_name).
contribution_metric
string
The LookML measure to analyze (e.g., 'orders.total_revenue').
dimensions
string[]
base_filters
object
Optional Looker-syntax filters to scope the entire dataset (e.g., {'users.country': 'India'}).
baseline_filters
object
Defines the EXPECTED, PAST, or NORMAL group (State A). For time KDA, put the past date filter here (e.g., {'orders.created_date': 'last week'}). For cohort KDA, put the baseline segment here (e.g., {'users.status': 'Active'}).
breach_filters
object
Defines the ANOMALOUS, CURRENT, or COMPARISON group (State B). For time KDA, put the current date here. For 'Rest of Population' cohort comparisons, use a minus sign to negate the baseline (e.g., {'users.status': '-Active'}).
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2026-03-25 UTC."],[],[]]