Pick a North Star metric

To: CEO, Growth Lead From: Head of Product Re: Simmer's North Star

Recommendation

Make the North Star Weekly Active Cookers (WAC): users who complete Cook Mode on two or more recipes in a week.

Both of your metrics matter, but neither measures the thing that drives the business.

Why not MAU. 68% of our 2.1M monthly actives arrive from search, read one recipe and leave. They retain at 4% at month 6. Last year's push test shows the risk: MAU rose 6%, uninstalls doubled, and Cook Mode completions didn't move. A MAU target rewards exactly that trade.

Why not MRR. MRR ($840K, from 140K subscribers at $6) is the outcome we want, but it lags. It can also be moved by a price change or a paywall tweak without making the product better, and it tells a team nothing about what to do this week.

Why WAC. People who cook twice or more a week retain at 61% at month 6, against 9% for savers who never cook and 4% for browsers. And 82% of new subscribers cooked at least three recipes in Cook Mode in their first two weeks. Cooking sits upstream of both retention and revenue, so growing WAC should grow MRR, and teams can influence it within a sprint.

MRR stays as our top-line business outcome, reported alongside WAC. MAU becomes a funnel-health metric, since it is the pool WAC is converted from.

One caveat: these are correlations, and committed cooks may simply be our best users anyway. In the first quarter we should run a holdout experiment, such as a stronger first-week cooking prompt, to confirm that causing more cooking causes better retention and conversion.

Input metrics teams can own

1. New-user activation (Onboarding): % of new users who complete a Cook Mode recipe within 7 days, with the 3-recipes-in-14-days rate tracked as the subscription-intent signal.
2. Save-to-cook rate (Discovery and Cook Mode): % of savers who cook a saved recipe in Cook Mode within 14 days. Savers who never cook retain at 9%, so this is our biggest leak.
3. Browse-to-return conversion (Growth and SEO): % of search-landing visitors who save a recipe or come back within 7 days. This gives Growth a real lever on the 68%, and on MAU quality.
4. Planning adoption (Planning): % of monthly actives who build a weekly plan. Only 7% have ever done it, yet weekly planners retain at 54%.

Guardrails against gaming

Against cheap cooking events. Completion is logged when someone reaches the last step, so tapping through counts. - Track a "quality completion" (minimum elapsed time relative to recipe length, or timer use) and report WAC on that basis. - Monitor median time per completion for sudden drops. - Add an occasional "Did you cook it?" prompt to calibrate against self-report.

Against the notification trap. - Set a hard cap on push frequency. - Treat uninstall rate and notification opt-outs as blocking metrics: any experiment that worsens either is not shipped, whatever it does to WAC or MAU.

Against short-term lifts. - Judge any WAC gain by its 30- and 90-day cohort retention, so we don't buy a spike with users who disappear.

Against revenue gaming. - Track subscriber churn, refund rate and cancellation-flow completion alongside MRR. - Don't count MRR gains from price changes or paywall aggressiveness as product wins. - Don't gate Cook Mode so tightly that new users can't reach the 3-recipe habit that predicts subscribing.

Against MAU drift. - Keep reporting MAU, but as a watch metric with no team target. If MAU rises while WAC is flat, we treat it as a warning sign rather than a win.

What each of you gets

• CEO: a metric that leads MRR and that teams can act on, with MRR still reported at the top. If WAC grows and conversion holds, MRR follows.
• Growth lead: ownership of the biggest untapped pool, the browse-only majority. Success is measured by how many of them become cookers, not by how many we can get to open the app.

I'd propose we adopt WAC from next quarter, baseline it in the first month, set targets once we see the quality-adjusted number, and review the causal experiment results at the end of the quarter.

Simmer's North Star: Weekly Active Cooks

To: [CEO], [Growth Lead] From: Head of Product

Recommendation

Our North Star should be Weekly Active Cooks: users who complete two or more recipes in Cook Mode in a given week.

Neither MRR nor MAU is wrong as something to watch. But neither works well as the one number every team steers by. Weekly Active Cooks sits between them. It is the behaviour that best predicts both retention and revenue, and teams can move it week to week.

Why not MRR

MRR is the outcome we're ultimately accountable for, and it stays on the board. As a North Star, it has two problems.

• It lags. Revenue moves after behaviour has already changed, so teams learn too late whether their work helped.
• Most teams can't touch it directly. The levers that move MRR fastest are pricing, paywalls and discounting. Those can lift revenue in the short term while hurting the habit that sustains it.

The behaviour that comes before revenue is cooking. 82% of new subscribers cooked at least three recipes in Cook Mode in their first two weeks.

Why not MAU

MAU measures reach, and reach matters. But our own data shows it rewards the wrong things.

• Most of it doesn't stick. 68% of monthly actives only browse: they arrive from search, read one recipe and leave. Only 4% of them are still active at month 6.
• It's easy to inflate. Last year's daily push notification raised MAU by 6%. Uninstalls doubled, and Cook Mode completions didn't change. MAU went up while the business got slightly worse.

Why Weekly Active Cooks

• It predicts retention. 61% of users who cook twice a week are still active at month 6. That is the strongest retention signal we have, ahead of weekly planners (54%), savers who never cook (9%) and browse-only users (4%).
• It predicts revenue. Cooking comes before subscribing for most new subscribers.
• It reflects real value. Someone who cooked dinner with Simmer got what we promise.
• It's weekly. Teams get feedback fast enough to iterate.

A caveat: this evidence is correlational. People who cook may simply be more committed to begin with. Before we fully commit, I propose a holdout test of one cook-encouraging change to confirm that causing cooking improves retention. We also need to establish the current baseline, which we don't track today.

Input metrics teams can own

1. Browse-to-cook conversion (owner: Growth/SEO). The share of search visitors who start Cook Mode in that visit or return within seven days. Our biggest pool of users is the 68% who browse, and this turns reach into habit. It also gives the growth team a version of the audience goal that counts.
2. New-user activation (owner: Onboarding). The share of new users who cook three recipes in their first 14 days. This mirrors the path most subscribers took.
3. Save-to-cook rate (owner: Recipe/Discovery). The share of saved recipes cooked within 14 days. Savers save four recipes a week, but saving alone retains only 9% of them. Reminders, shopping lists and "cook what you saved" features should close this gap.
4. Weekly planning adoption (owner: Meal Planning). The share of actives who plan a week of meals. Only 7% have ever done it, yet planners retain at 54%. Planning is also a Plus feature, so it has a direct line to revenue.

Guardrails

• MRR and free-to-paid conversion, reviewed monthly. If Weekly Active Cooks rises but conversion falls, we may be giving away too much free.
• Uninstall rate and notification opt-outs. Any engagement push that worsens these gets reviewed, given what happened with the daily notification.
• Cook Mode completion quality. We currently log a cook when someone reaches the last step, which is easy to tap through. We should only count completions with plausible time spent on the steps. A share of completions should also show supporting signals, such as timers used or the recipe rated or repeated.
• Six-month retention by cohort. This is the ultimate check that more cooks means more lasting users.
• MAU, tracked but not targeted. If reach collapses, the funnel feeding Weekly Active Cooks dries up.

Next steps

If you both agree, we will:

• instrument the metric and the quality filter,
• publish a baseline within three weeks,
• run the causal test, and
• set first-half targets for each input metric with their owning teams.

Recommendation: optimize for weekly cooking, not revenue or visits

Our North Star should be Weekly Engaged Cooks: the number of unique users who complete at least two recipe-cooking sessions in Cook Mode within a rolling seven-day period. Count each person once, across free and paid users.

Simmer’s core promise is helping people make meals—not merely find recipes. This metric captures users repeatedly receiving that value.

The evidence points toward cooking: - Users cooking at least twice a week have 61% month-six retention, versus 9% for save-only users and 4% for browse-only users. - 82% of new subscribers cooked at least three recipes in their first two weeks. - Weekly planners also retain well, at 54%, but planning has reached only a small minority of users. It should support cooking, not define value for everyone.

These are associations, not proof that pushing users across a threshold causes retention or subscription. They are nevertheless our strongest starting evidence; we should test whether product changes that increase genuine cooking also improve those outcomes.

Why not MRR or MAU?

To our CEO: MRR remains a critical business outcome. But as the North Star, it could reward price increases or aggressive paywalls even while fewer people get value. Weekly cooking gives teams a customer-value objective with a plausible connection to durable revenue.

To our growth lead: MAU measures reach, but treats a one-recipe search visitor like a habitual cook. Our notification experiment demonstrates the danger: MAU rose 6%, uninstalls doubled, and cooking completions stayed flat. That was more activity, not more value.

Four input metrics teams can own

These are drivers, not independent targets to maximize at any cost. Track their absolute user counts alongside rates so teams cannot improve percentages simply by shrinking eligibility.

Guardrails against gaming

1. Measure cooking, not button presses. Reaching the last step is a proxy, not proof of a cooked meal. Exclude automated activity and duplicate completion events. Audit suspicious completion patterns and periodically validate the proxy through user research. Don’t reward tapping through steps, auto-completion, or cosmetic changes to logging.

2. Protect the whole experience. Monitor uninstalls, notification opt-outs, complaints, and cooking satisfaction. Reject “growth” that increases qualifying activity through nagging while materially worsening these measures. Preserve browse-only usefulness; not every visitor needs to become a tracked cook.

3. Require durable gains. Evaluate experiments on sustained weekly cooking and cohort retention, not just a short-lived threshold crossing. Keep metric definitions stable and report results separately for new, existing, free, and paid users.

4. Keep economics visible. Review MRR, paid conversion, subscriber churn, and contribution margin alongside the North Star. More cooking is not enough if it undermines a sustainable business.

Bottom line: MAU tells us who arrived; MRR tells us what we earned. Weekly Engaged Cooks tells us whether Simmer is becoming useful enough to return to—and pay for.