Experiment Engine
Test what works
Every decision becomes a measurable experiment. Autopsify takes an opportunity, frames it as a test with a real baseline, and captures the result and learning — so your next move is sharper than your last.
The learning loop
From opportunity to next action
Opportunity
Hypothesis
Creative
Experiment
Result
Learning
Next action
How an experiment runs
Baseline, run, measure, learn
Baseline
Starting the experiment snapshots the real metric it targets, so you measure against truth.
Target
Set the outcome you're aiming for — the experiment is framed around a concrete goal.
Run
Move the experiment through its lifecycle: draft → ready → running.
Result
Capture what actually happened when the experiment completes.
Before / after
The engine computes the change against the baseline so the effect is unambiguous.
Learning
Record what you learned — the durable takeaway, win or lose.
Write-back
The outcome and learning flow back onto the linked opportunity, closing the loop.
Restock & redirect traffic
RunningBaseline
3 OOS
Target
0 OOS
Learning
Captured on completion and fed back to the opportunity.
Illustrative experiment
Honest measurement
Measured against real data — or clearly marked when it isn't
Baselines and results read from live store metrics. Product and inventory metrics are available today; some order and customer metrics may be unavailable while Shopify's Protected Customer Data access is restricted. When a metric can't be measured, the experiment says so with the reason — it's never quietly reported as zero.
Turn decisions into evidence
Connect your store and run your first experiment against a real baseline.