Metric Monitoring

Problems in Your Business Don't Announce Themselves.

By the time someone notices a metric has moved, the window to act has usually closed. Fig watches your metrics around the clock, catches the signal the moment it appears, and automatically delivers the diagnosis — so your team wakes up to answers, not alarms.

From Alert to Answer — Automatically

Five steps from "something moved" to "here's exactly why and what to do about it" — with no analyst required.

1

Choose What to Watch

Pick the metrics that matter to your business. Set how much movement counts as a real problem versus normal noise — so you only get notified when something actually deserves attention.

2

Set the Cadence

Tell Fig how often to check. Daily for revenue. Hourly for time-sensitive operations. Weekly for strategic metrics. Fig watches on your schedule, in your timezone, without anyone pressing a button.

3

Catch the Signal

When a metric moves outside its expected range, Fig catches it immediately — distinguishing a real problem from normal day-to-day fluctuation, so your team isn't flooded with false alarms.

4

Trace the Cause

The moment an anomaly is detected, Fig automatically kicks off a root cause investigation — tracing through your causal map to identify what upstream change drove it.

5

Deliver the Diagnosis

Your team receives a structured report: what happened, the most likely causes ranked by impact, supporting evidence, and recommended next steps. Ready to act on — not to investigate.

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Why Monitoring Without Diagnosis Is Just Noise

Traditional Alerts

A dashboard turns red. Your team scrambles to figure out what happened. They open five tabs, run ad-hoc queries, and spend the morning narrowing down the cause.

By the time they have an answer, the impact has already compounded — and the explanation is often incomplete.

Fig Monitoring

Fig detects the anomaly, immediately enqueues root cause analysis, and delivers a structured report — with contributing factors ranked by impact.

Your team wakes up to the diagnosis, not the alarm. They skip the investigation phase entirely and go straight to action.

Alerts tell you something is wrong. Fig tells you why it is wrong — and does it automatically, on the schedule you set.

Real Monitoring Scenarios

See how automated anomaly detection and root cause analysis work together in practice.

Trigger

Collection rate drops 8% on Tuesday

What Fig Finds

Fig's monitors catch the anomaly within the scheduled window. Automatic RCA traces the decline to provider schedule changes that reduced follow-up capacity.

So that your team sees the specific scheduling changes within hours, not weeks — and can act before the drop compounds.

Trigger

Same-store sales decline across 12 locations

What Fig Finds

Auto RCA decomposes the decline and finds two concurrent drivers: foot traffic patterns shifting and seasonal inventory misalignment at specific locations.

So that your team knows exactly where the decline is concentrated and what correlates — not just that sales are down.

Trigger

ROAS drops below your configured threshold

What Fig Finds

RCA traces the performance drop to a bid strategy change that went live the same day a landing page update increased load time by 1.8 seconds.

So that your team sees the two concurrent changes that caused the drop — and doesn't waste a week testing one variable at a time.

Stop Reacting. Start Diagnosing Automatically.

Set up your first monitor in minutes. Fig watches your metrics around the clock and delivers root cause reports — so your team focuses on decisions, not investigation.