CRO Glossary
Experiment Read-Out
A structured summary presenting an experiment's results, statistical validity, and recommended next action to stakeholders.
An experiment read-out is the document or presentation delivered at the end of a test that translates raw statistical output into a decision-ready narrative. It typically covers the original hypothesis, what was tested, the primary and guardrail metrics, whether the result reached the pre-defined significance and power thresholds, any notable segment differences, and a clear recommendation — ship, iterate, or kill. Good read-outs also disclose caveats, like whether the test ran through a full business cycle or hit an SRM check.
Read-outs matter because raw dashboards and p-values don't drive organizational decisions on their own; someone has to translate 'variant B lifted conversion by 4.2%, p=0.03' into 'we recommend shipping B to 100% of traffic, expected impact $X/year.' Poor read-outs — ones that cherry-pick favorable metrics or gloss over inconclusive results — are how bad decisions and confidence washing creep into a testing program.
A well-run team standardizes its read-out template so that every test, win or loss, gets recorded the same way: hypothesis, result, confidence level, business impact estimate, and follow-up actions. This creates a searchable experiment history that prevents re-testing the same idea and helps new team members understand why certain UI decisions were made.
For instance, a checkout page test might read out as: 'Removing the coupon code field increased conversion by 3.1% (95% CI: 1.2%–5.0%), no negative impact on AOV guardrail metric. Recommend full rollout and follow-up test on field placement for upsell.'
Related terms
Above vs Below Median Split
A segmentation technique that divides users into two groups at the median of a metric to compare high and low engagers.
Qualitative Feedback Loop
A recurring process of collecting and acting on user comments, session recordings, and survey responses to inform test hypotheses.
Experiment Metadata
The structured record of who, what, when, and how for a test — hypothesis, owner, dates, variants, and metrics used to track and audit it.
Pre-Test Analysis
The upfront work of validating traffic, metrics, and baseline data quality before launching an experiment.
Above-the-Fold vs Below-the-Fold Messaging Hierarchy
How the order and prominence of value-proposition messaging is split between the visible screen and the rest of the page.
Experiment Contamination
When a control or variant group is unintentionally exposed to the other condition, corrupting the comparison.
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