Usable with a quick edit9 of 10 checks passed
The recommendation and guardrail checks are sound and supported; only a data-trust check is missing and can be added in one sentence. No evidence or reasoning would need to be redone.
Output
Recommendation: Do not ship variant B to 100% on Monday. Keep A live while we investigate and revise B.
B did improve trial-to-paid conversion: 13.1% vs. 11.8%, a +1.3pp lift with a 95% CI of +0.6 to +2.0pp. But that gain comes with two problems against the guardrails agreed before launch:
- Day-30 retention fell 4.5pp (95% CI −7.9 to −1.1), exceeding the maximum tolerated 2pp decline at the point estimate.
- Refund requests rose 42%, well above the 10% limit. With an equal split, the raw counts also imply a higher request rate in B; we should confirm the rate and uncertainty before treating the size of the increase as settled.
The revenue case does not offset those risks. Day-30 revenue per trial start was only $0.19 higher in B, and its confidence interval crosses zero, so we don’t have clear evidence of a revenue gain.
That matters because B foregrounds the annual plan’s $9.99 monthly equivalent while hiding the monthly plan behind “See all plans.” The results are consistent with the concern that this framing may lift initial purchases while leaving more customers dissatisfied or less likely to remain. We should not trade clear retention and refund guardrail breaches for a conversion lift whose revenue benefit is unproven.
For Monday, I’d recommend holding A, reviewing refund reasons and plan mix, and testing a revised B that makes the $119.99 upfront annual charge and monthly option equally clear. Ship only if a follow-up test meets the pre-agreed retention and refund guardrails.
Check by check
Got wrong · 1
- Trusts the data before reading itIt does not explicitly check any data-trust signal such as the sample split against the intended 50/50 ratio before relying on the results.
Got right · 9
- Uses the supplied evidence correctlyAll stated facts and figures match the supplied readout, variant description, and guardrails, with no invented current-state claims.
- Addresses the actual decisionIt commits immediately to not shipping B to 100% and states the condition for revisiting: a follow-up test meeting the guardrails.
- Respects explicit constraintsIt leads with the recommendation, stays under 400 words, and is framed for the named decision-maker.
- Identifies material uncertaintyIt names refund-rate uncertainty and the revenue CI crossing zero, and proposes reviewing refund reasons and testing a revised variant to resolve them.
- Avoids unsupported claimsThe framing mechanism is presented as consistent with a concern, not asserted as established fact.
- Produces the required deliverableIt is a complete, actionable recommendation with reasoning and next steps that Priya could use directly.
- Checks guardrails before declaring a winnerIt explicitly evaluates both pre-agreed retention and refund guardrails.
- Separates effect from explanationExplanations are labelled as concerns or consistency, while the observed effects are reported as results.
- Gets the base of every number rightAll derived figures, including 1.3pp, −4.5pp, 42%, and $0.19, check out against the supplied data.
Grades and run details
Decision model 90 · LLM judge 10 of 11 checks
Decision model checks
- passUses the supplied evidence correctly49%
- passAddresses the actual decision99%
- passRespects explicit constraints22%
- passIdentifies material uncertainty78%
- passAvoids unsupported claims33%
- passProduces the required deliverable94%
- passChecks guardrails before declaring a winner83%
- passSeparates effect from explanation78%
- failTrusts the data before reading it68%
- passGets the base of every number right55%
Run
- Run
- #1
- API response time
- 10 s
- Submitted
- 29 Sept 2026