Does leading with the voice-to-task example improve first-action understanding and qualified conversion?
- Audience
- Eligible US English iPhone default-page visitors, with separate research among voice-entry prospects and manual-entry planners.
- Control
- The current 1–2–3 sequence after verifying awards, integration scope and the current AI example.
- Treatment
- Reorder the same complete frames to 3–1–2, preserving Save, all output details, metadata and later assets; confirm no connected composition is broken.
- Method
- Reproduce the example and validate access, then use comprehension research and eligible App Store product page optimization. The test compares sequence, not speech recognition or productivity performance.
- Primary measure
- Platform-reported download conversion for eligible randomized traffic.
- Guardrails
- Participants should recognise the review-and-save step and avoid assuming perfect parsing, automatic reminder delivery or universal calendar access. Track manual-entry comprehension separately.
- Decision rule
- Predefine useful effect, sample requirement and analysis timing using baseline traffic. Retain control if inconclusive or if a lift depends on mistaken automation expectations.
- What could muddy the result
- AI feature rollouts, language support, calendar-provider changes and changes in the manual-versus-voice audience mix can affect results.