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What’s holding your app back? One move, not forty ideas.

Find the stage your product is stuck in, and the next right move. Built on Hooked, Actionable Gamification and Influence.

Free · 2 minutes · no signup. Gamify It is $29/mo billed annually when you want the full loop in your assistant.

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Question 1 of 6
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What do you want more of?

Pick the one that would help your app grow most right now.

Recreated session · fictional demo product

What it looks like inside Claude Code.

One question, one card: where the product is, the one bottleneck, the next move with its source, and what not to build this sprint.

Claude Code · crewbook

Fictional, illustrative

  1. Founder: I want more restaurants paying. What should I fix first?

  2. Tool calls: get_statusnext_questions

    No saved products yet

  3. Assistant: I’ll read your repo (read-only) in a minute. Three quick questions first: how do restaurants pay, how many sign up each week, and what does a restaurant do in Crewbook on a good week?

  4. Founder: $39 per location a month after a 14-day trial, card upfront. About 90 sign-ups a week. On a good week the manager publishes next week’s schedule and the staff confirm their shifts.

  5. Tool calls: get_inspection_plan

    Repo mode · read-only scan

  6. Assistant: From the code:

    • Onboarding has 9 screens before the schedule grid appears.
    • SMS reminders go only to the manager. Staff get an email asking them to download an app.
    • PostHog tracks sign-ups and published schedules, but not onboarding steps, staff confirmations or what brings each session in.
    • Availability rules are stored, but nothing uses them to draft next week.

  7. Tool calls: locate_stage

    Stage Card v0 · low confidence

  8. Assistant: A first, provisional read: your bottleneck looks like Start, and the non-obvious part is that your reminders never reach staff. Two read-only queries through your Supabase connector would make this much sharper. OK?

  9. Founder: Go ahead.

  10. Tool calls: your Supabase connector

    12,400 sign-ups since launch: production, not seed data · only aggregates go to Gamify It

  11. Assistant: From the cohort query (12 weeks):

    • 32% of new restaurants publish a schedule that 3+ staff confirm within 7 days.
    • Those that do are 54% active at week 8, vs 9% for the rest. That’s a correlation, for now.
    • Restaurants with 10+ staff: 31% still active at week 8. Under 10 staff: 4%.
    • Trial to paid is 41% past that threshold, and 7% for the rest.

  12. Tool calls: locate_stagescore_hookscore_drivesmap_decision_points

    Binding stage only

  13. Stage Card · Crewbook

    Where you are
    Early fit (M2), medium confidence
    Bottleneck
    Start: 68% never get a schedule published and confirmed in week 1
    Non-obvious
    Reminders never reach staff, so the manager never sees the confirmations
    Not now
    Paid ads · annual discounts · points or badges
    If we’re wrong
    Value, for restaurants under 10 staff

  14. Tool calls: rank_opportunities

    90 eligible a week · 3-week effort budget

  15. Opportunity Board
    OptionPriorityDetectability
    Next Move: “First schedule in 10 minutes” (bundle)0.7Ready, ~6 weeks
    Easy: confirm-by-text to staff only1.3Underpowered alone (~20 weeks)
    Bigger swing: concierge setup for 10+ staff0.2Directional only

  16. Assistant: The easy option scores higher on its own, but it can’t be read at your volume, so it rides inside the bundle: import staff from a CSV, draft a week from a template, text staff a confirm link, show live confirmations, and only then ask for availability rules.

  17. Tool calls: design_experiment

    Baseline 32% · 90 a week · 7-day metric

  18. Assistant: Honest sizing:

    • A 20% lift on 32% needs about 850 restaurants per arm: about 20 weeks. Not worth it.
    • The bundle is designed to detect a 40% lift: about 213 per arm, about 6 weeks including the 7-day metric.
    • Prior range 0 to +40%; P(win) about 25%, uncalibrated. Not a forecast.
    • Guardrails: 7-day trial cancels and week-2 retention.

  19. Founder: Do it.

  20. Tool calls: gamifyit-build (skill)save_session

    Behind the flag onboarding_first_schedule · PR #58

  21. Assistant: PR #58 is ready for review, and EXP-007 is saved with the readout due Monday, December 14. This week’s task: send a one-question PMF survey to your active restaurants.

  22. Two weeks after launch

    The split is healthy (88 vs 91 restaurants), but only about 41% of the sample is in, so the effect isn’t read yet. The survey came back at 47% “very disappointed” among 10+ staff restaurants: stage confidence is now high.

  23. Tool calls: compute_metricssave_experiment

    Readout · December 14

  24. Assistant: Readout under your pre-registered rule:

    • Control 68 of 212 (32.1%); variant 99 of 214 (46.3%). Effect +14.2 points, 95% CI +5.0 to +23.4.
    • That’s above the prior range, so I checked the logs first: exposure and events reconcile in both arms.
    • Shrunk estimate: about +9 points. A 10% holdback re-read decides the durable number.
    • Trial cancels 4.7% vs 4.2%: no significant harm, but that guardrail is not powered.
    • Decision: Ship, with a 60-day holdback. Next binding cell: Return.

Readout · step 24 of 24

Honest limits

The Stage Finder is a first read. The real one runs on your numbers.

A few self-reported answers can earn Low or Medium confidence, never High. In Claude Code, Codex, Claude or ChatGPT, Gamify It reads your real numbers, grades the evidence, picks one move and sizes the experiment to your traffic.

  • One binding stage, with a runner-up in case it is wrong
  • One next move, with its source and evidence grade
  • A Not-now list: what to skip this sprint, and why
  • An experiment sized to your traffic, and a readout that can say “inconclusive”
  • Memory: it remembers what you tried and what happened
  • What Gamify It never sees: your source code, raw events or your users’ personal data.

What you get

One card, readable in a minute.

The full Stage Card for a fictional product, Crewbook: where it is, the one bottleneck, what to skip, and the next move, sized to its traffic.

Stage Card · Crewbook

Fictional, illustrative

Shift-scheduling SaaS for independent restaurants, US ·

Where you are

Early fit (M2), confidence medium.

Restaurants with 10+ staff keep using it (31% still active at week 8); under 10 staff fall to about 4%. Unknown: the PMF survey hasn’t run yet.

Readiness

Your key action is tracked; what brings each session in is not. About 90 sign-ups a week.

Your bottleneck

Start. Only 32% of new restaurants publish a schedule that 3+ staff confirm within 7 days. Those that do are about 6× likelier to be active at week 8 (54% vs 9%; a correlation, not yet causation).

Non-obvious

Your SMS reminders go only to the manager, so staff never see the value that makes a manager come back. The trigger score is capped at 2: no trigger reaches the people whose confirmations are the reward.

Not now

Paid ads (fix the setup leak first) · annual-plan discounts (there’s no habit to protect yet) · points or badges (first steer new restaurants onto the path your retained restaurants took).

Next move

“First schedule in 10 minutes”: import staff from a CSV, generate a draft week, send confirm-by-text to staff, and ask for availability rules after.

How we’ll know

Primary: published + 3 confirmations in 7 days. Readout in about 6 weeks (a bundled change). Guardrails: 7-day trial cancels; week-2 retention.

If we’re wrong

The real bottleneck may be Value for restaurants under 10 staff.

To be more sure

(1) Run the one-question PMF survey with active restaurants. (2) Export PostHog sign-ups by week. (3) Record what brings each session in.

Sources

HK-INV19, HK-INV01, HK-ACT32, HK-TRG08 (Hooked ch. 2, 3, 5) · GT#43 and the First Major Win-State (Actionable Gamification)

  1. A stage, with its confidence

    Maturity comes from product-market-fit signals only, never traffic. The card says how sure it is and what is still unknown.

  2. One cell, not forty ideas

    Ten Constraint Rules pick the single binding cell on the Stage Map. Everything else waits.

  3. Specific to your product

    Server-side contradiction checks surface one insight about your product, not a generic tip from a book.

  4. What to skip, and why

    Good advice at the wrong stage is bad advice. The card names the tempting moves that are out of season for you.

  5. One move, every factor shown

    Moves are ranked by Size × Odds × Fit ÷ Cost, and you can argue with each factor.

  6. Sized to your traffic

    The test is sized before you build. If your traffic can’t detect the change, you get a bigger swing or the low-traffic loop instead of a micro-tweak.

Evidence, not hype

Honest numbers beat big promises.

We are new, so there are no testimonials here yet. What we can show is how we work: real cases, dated and graded, and a contract we keep in every answer.

  • M1 ×Value2018

    Superhuman: Segment before you build

    “Very disappointed” rose from 22% to 33% by segmenting alone, then to 58% in about three quarters.

    Case grade for the number: B. Evidence grade for the mechanism link: B. company-described.
  • M2 ×Start2015

    Slack: Find your activation threshold

    About 93% of teams past 2,000 messages kept using Slack, per its co-founder.

    Case grade for the number: B. Evidence grade for the mechanism link: B. correlational.
  • M4 ×Discover2026

    Peloton: Phase before mechanic

    Paid subscriptions fell 8.8% in fiscal 2026 while average monthly churn stayed at 1.7%.

    Case grade for the number: A. Evidence grade for the mechanism link: D. many causes.
  • We never promise a lift.
  • Every number carries its source, its date and its grade.
  • Readouts come with confidence intervals, and “Inconclusive” is a legitimate outcome.
  • Thresholds like a 40% PMF score are labeled heuristics, not laws.
  • Frameworks are labeled for what they are: the Hook Model is a practical tool, and Octalysis is a practitioner framework.

Pricing

One plan. The whole loop.

Every tool on every assistant, for up to 3 products. Annual saves $120 a year.

$29a month, billed annually ($348)

Or $39 billed monthly. Cancel in one click. Your first payment is refundable within 14 days.

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Questions

Fair questions.

Find the stage you’re stuck in. Then make one move.

Free · 2 minutes · no signup. Gamify It is $29/mo billed annually when you want the full loop in your assistant.

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