Needs more than a quick edit7 of 11 checks passed
The output lacks a condition that would change the recommendation, omits unknowns, makes unsupported causal claims, and does not explicitly pair the North Star with a business measure. A PM would need to rework these gaps.
Output
To: CEO & Growth Lead From: Head of Product Subject: Aligning on Our North Star Metric
Choosing between Monthly Active Users (MAU) and Monthly Recurring Revenue (MRR) is a classic tension between reach and monetization. But choosing either will hurt Simmer.
Here is why neither works as our North Star, what we should measure instead, and how we keep the business honest.
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Why Not MAU or MRR?
- MAU is a vanity metric that invites bad behavior. 68% of our monthly actives are transient visitors who read one recipe from Google and bounce, retaining at a dismal 4% by month six. Last year’s push notification test proved MAU is dangerous: blast notifications spiked MAU by 6%, but Cook Mode usage didn’t budge and uninstalls doubled. Optimizing for MAU encourages low-intent traffic acquisition and spammy retention hacks.
- MRR is a lagging output. MRR tells us if we extracted value last month, not if we created value today. Optimizing directly for MRR leads teams to tighten paywalls, increase discounts, or push annual locks—tactics that burn long-term trust without fixing the core product engine.
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The Proposed North Star: Weekly Active Cooks (WAC)
Definition: The number of unique users who complete at least one recipe in Cook Mode in a rolling 7-day window.
A great North Star sits at the intersection of customer value and enterprise value. For Simmer, that intersection is Cook Mode:
- It predicts retention: Users who cook $\ge$2 recipes a week retain at 61% at month 6 (compared to 9% for passive recipe savers and 4% for browsers).
- It fuels monetization: 82% of new subscribers completed at least three Cook Mode sessions in their first two weeks. Cook Mode is the direct gateway to our $6/month Simmer Plus subscription.
If Weekly Active Cooks grows sustainably, MAU becomes higher-intent and MRR growth naturally follows.
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Team Input Metrics
Product, Growth, and Content teams cannot easily move WAC directly; they need operational inputs they can own day-to-day:
1. Browse-to-Cook Activation Rate (New User Experience & Growth): % of first-time visitors who enter Cook Mode within 7 days of their first session. Goal: Move users out of the 68% bounce bucket and into an interactive cooking experience. 2. Multi-Cook Frequency (Core Product): % of active cooks completing $\ge$2 Cook Mode sessions per week. Goal: Deepen habit formation to hit the threshold associated with our 61% 6-month retention rate. 3. Weekly Meal Plan Adoption (Engagement & Feature Hook): % of monthly actives who schedule $\ge$3 recipes into a weekly meal plan. Goal: Only 7% have ever tried meal planning, yet planners show 54% month-6 retention. Meal planning provides the forward-looking intent that drives repeat Cook Mode completions. 4. Qualified Cook-to-Subscriber Conversion (Monetization): Conversion rate to Simmer Plus among users who have completed their 3rd Cook Mode recipe. Goal: Target our paywalls and free-trial prompts precisely when users reach the high-intent threshold (the 82% cohort), rather than hitting casual browsers with hard walls.
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Guardrail Metrics (To Prevent Gaming)
To ensure teams do not inflate WAC artificially, we must establish three non-negotiables:
- Cook Mode Session Integrity: Cook Mode completions are only counted if the user spends at least 5 minutes in the mode with step-progression intervals matching real cooking behavior. This prevents growth teams from auto-completing sessions via deep links.
- Net Churn & Uninstall Rate: Every experiment that touches engagement or notifications must track app uninstalls and notification opt-outs. Any test that increases uninstalls (like the push notification failure) is an automatic rollback, regardless of active-cook uplift.
- Monthly Cohort Renewal Rate: We must monitor 30- and 90-day retention of new Simmer Plus subscribers to ensure we are not driving low-intent conversions through deceptive trial dark-patterns.
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By rallying around Weekly Active Cooks, we bridge the gap between audience growth and revenue: we build a sticky, habitual product first, and harvest the revenue second.
Grades and run details
Decision model 86 · LLM judge 58
Decision model checks
- passUses the supplied evidence correctly32%
- passAddresses the actual decision51%
- passRespects explicit constraints38%
- failIdentifies material uncertainty95%
- partialAvoids unsupported claims60%
- passProduces the required deliverable85%
- passAnswers both proposals with the data94%
- passMeasures value created, not captured95%
- passGets the base of every number right68%
- passBreaks it into inputs teams can move48%
- passSays how it could be gamed99%
Run
- Run
- #1
- API response time
- 22 s
- Submitted
- 5 Oct 2026