Know exactly what moved your metric
When revenue dips 8% overnight, your team shouldn't spend two days digging through dashboards. Golden Analytics decomposes any metric movement into its exact drivers automatically.
Manual root-cause analysis doesn't scale
Every time a KPI shifts, someone rebuilds the same investigation from scratch. That cycle consumes analyst bandwidth that could go toward forward-looking work.
Hours per investigation
A typical metric movement investigation requires pulling multiple dashboard views, running ad-hoc queries, and cross-referencing segment breakdowns. A task that should take minutes takes a full afternoon.
Inconsistent methodology
Different analysts decompose the same metric in different ways. One uses relative contribution, another uses absolute delta. Results diverge, and stakeholders lose confidence in both answers.
Ticket queue bottleneck
Business teams can't investigate metrics themselves, so every question becomes a ticket. Analytics teams spend more time answering yesterday's questions than building tomorrow's answers.
Dimensional decomposition, automated
Golden Analytics reads directly from your warehouse, applies a statistically consistent attribution model, and returns a ranked driver explanation in under 30 seconds on tables with 10M+ rows, based on our internal benchmark suite.
Connect your warehouse
Read-only service account to Snowflake, BigQuery, or Redshift. No data copies, no pipeline changes. Your data stays in your warehouse.
Define your metric tree
Map the dimensions that can explain each metric: region, channel, product tier, customer segment. The tree encodes your analytical logic once.
Get driver explanations instantly
Any stakeholder can ask "why did this metric move?" and receive a ranked contribution breakdown in plain language, with no analyst in the loop.
What attribution gives your team
Segment contribution ranking
Every driver is ranked by its share of total metric change. You see not just which segments moved but how much each contributed to the overall shift.
Multi-dimensional decomposition
Layer region, product, channel, and cohort simultaneously. The model separates overlapping effects so you don't double-count contributions.
Configurable comparison windows
Week-over-week, month-over-month, quarter-over-quarter, or any custom date range. The attribution model is consistent regardless of comparison period.
Alert-triggered attribution
Pair anomaly alerts with automatic attribution. When a metric crosses a threshold, the system immediately identifies the segment driving the anomaly.
Exportable breakdowns
One-click export to CSV or a shareable link with full driver context. Your stakeholders get a clean summary without a separate presentation deck.
API access
Trigger attribution programmatically from your own pipelines or dashboards. Integrate driver breakdowns into BI tools your team already uses.
Pair attribution with these capabilities
NL Querying
Let any team member ask follow-up questions about driver breakdowns in plain English. No SQL required.
Learn moreStakeholder Reporting
Turn attribution results into formatted exec reports automatically. Reduce the time from insight to stakeholder distribution.
Learn moreRun your first attribution in minutes
Connect your warehouse with a read-only service account. No data copies, no pipeline changes. Free trial, no credit card required.