Hypothesis & metric design
Define the change, expected mechanism, primary outcome and guardrails before launch.
SERVICES05 / A/B TESTING
A strong opinion.
A fair test.
Controlled experiments that turn a specific prediction into evidence your team can use.
Discuss your project +A GOOD FIT FOR
For businesses with enough eligible traffic and conversions to test meaningful changes within a practical timeframe.
THE CONSTRAINT
An attractive variation and a higher observed conversion rate can still produce an unreliable conclusion. Test design and data integrity determine what you can learn.
THE NEXT STEP
A properly scoped experiment, a defensible analysis and a clear recommendation tied to the business decision.
WHAT THE WORK INCLUDESDEFINED AROUND YOUR SCOPE
Sample & feasibility plan
Assess baseline performance, detectable effect, sample requirements and expected duration.
Setup & quality checks
Validate assignment, tracking and treatment behavior; monitor sample ratio and implementation integrity.
Analysis & decision
Report effect size, uncertainty and commercial implications, including inconclusive or negative findings.
From question
to a better decision.
- 01Frame the hypothesis
- 02Check feasibility
- 03Launch and monitor
- 04Interpret the evidence
HOW SUCCESS IS DEFINED
A credible decision, including when the evidence does not support a rollout. A test can teach you something useful without producing a positive result.
VayKLife: why an observed result needs context before a decision.
Explore the case studyBefore we begin.
How long does a test run?+
Duration depends on baseline conversion, traffic, the effect you need to detect and the design. We estimate it before launch and avoid ending a test simply because a dashboard turns green.
Do you guarantee a winning variation?+
No. The commitment is to a rigorous process, transparent analysis and useful learning. Outcomes depend on the hypothesis and customer behavior.