Evidence-first methodology

Detect first. Explain second. Decide with the evidence visible.

OptiWhiz is designed to make the reasoning behind a conversion recommendation inspectable, rather than asking teams to trust a black box.

Why analytics alone rarely creates a CRO roadmap

Analytics can show a drop-off or difference. Turning it into a good decision still requires a team to compare segments, check context, evaluate the strength of the signal, and write a testable hypothesis. That manual handoff is where evidence often gets lost.

1. Assemble evidence

OptiWhiz begins with observed conversion behavior and rule-based detection. It identifies patterns worth review before generating an explanation.

2. Preserve uncertainty

Confidence, estimated impact, comparison context, and limitations are presented as decision inputs. A likely cause remains a hypothesis until a team validates it.

3. Use AI for the right work

AI helps summarize evidence, frame recommendations, and turn a grounded finding into a structured experiment idea. It is not allowed to invent behavioral data, causal certainty, or promised business impact.

4. Move to a testable next step

Each recommendation can become a hypothesis with a proposed change, target audience, and success metric. OptiWhiz does not automatically deploy tests or modify customer websites.

Provider-independent by design

The decision model is intentionally separate from any single analytics provider. Supported data connections and onboarding workflows are discussed during early access.

Make the next CRO decision easier to defend.

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