AI Skill Report Card

Engineering Growth Strategies

A-82·Sep 27, 2026·Source: Web
14 / 15

Given a product description and goal (e.g., "grow MusGo's weekly active users"), produce four deliverables in order: Growth Strategy → Acquisition Plan → Retention Plan → Experiment Matrix. Always ground recommendations in the AARRR funnel (Acquisition, Activation, Retention, Referral, Revenue) and prioritize experiments by ICE score (Impact, Confidence, Ease).

Example invocation output skeleton:

Recommendation▾
Add a second example with a different scenario (e.g., B2B SaaS or an app strong on acquisition but weak on virality) to show range beyond the ride-hailing case.

[North star metric, growth loops, funnel diagnosis]

[Channels, tactics, budget/effort allocation, CAC targets]

[Onboarding, engagement loops, churn triggers, win-back]

| # | Hypothesis | Funnel Stage | ICE Score | Owner | Timeline |

14 / 15

Progress:

  • Clarify North Star Metric (NSM) and current funnel stage that's weakest
  • Diagnose growth bottleneck (acquisition, activation, retention, or virality)
  • Draft Growth Strategy (loops, positioning, NSM, key bets)
  • Draft Acquisition Plan (channels ranked by CAC/LTV fit)
  • Draft Retention Plan (onboarding, habit loops, churn prevention)
  • Build Experiment Matrix with ICE-scored, testable hypotheses
  • Sanity-check: every recommendation ties back to a metric and a testable hypothesis

Step details:

  1. Diagnose first. Never jump to tactics before identifying which stage of the funnel is leaking users most. Ask for or infer: signup rate, activation rate, D7/D30 retention, referral coefficient (k-factor).

  2. Growth Strategy must define:

    • North Star Metric (one metric that reflects value delivered)
    • 1-2 core growth loops (not just funnels) — e.g., content loop, referral loop, paid loop
    • The single biggest bottleneck to attack first
  3. Acquisition Plan must rank channels by expected CAC, using a simple table (Channel, Tactic, Target Audience, Est. CAC, Est. Volume, Priority).

  4. Retention Plan must separate:

    • Activation (first-session "aha moment")
    • Habit formation (trigger → action → reward → investment, Hook Model)
    • Churn intervention (win-back triggers, lifecycle emails/push)
  5. Experiment Matrix must have 8-15 experiments, each with a falsifiable hypothesis ("If we do X, metric Y will increase by Z%"), scored ICE (1-10 each), sorted by total score descending.

Recommendation▾
Include a brief note on handling insufficient input data (e.g., what to do when funnel metrics aren't provided) to cover an important edge case.
15 / 20

Example 1: Input: "MusGo is a ride-hailing app in Indonesia losing users after first ride. Design a growth strategy."

Output:

Recommendation▾
Show a bad/anti-pattern example output alongside the good one to reinforce the 'Common Pitfalls' section with concrete contrast.

NSM: Weekly Active Riders (WAR) Bottleneck: Activation→Retention drop-off after ride #1 (D7 retention 12%, industry benchmark 25%+) Core Loop: Referral loop (rider invites rider for ride discount) + habit loop (daily commute reminders)

ChannelTacticAudienceEst. CACPriority
ReferralIn-app double-sided discountExisting ridersRp15kHigh
Local partnershipsCampus/office kiosksStudents/office workersRp25kMedium
Paid socialLookalike audience from top 10% ridersUrban 18-35Rp40kLow (test only)
  • Activation: Guarantee first-ride ETA <5min or refund, to nail "aha moment"
  • Habit: Push notification at user's historical commute time
  • Churn intervention: Auto-send 20% off voucher if no ride booked in 10 days
#HypothesisStageICETimeline
1Commute-time push increases D7 retention by 15%Retention8/7/9=241 week
2Double-sided referral bonus increases k-factor by 0.1Virality7/6/8=212 weeks
  • Always propose a North Star Metric before any tactic — tactics without a metric are noise.
  • Prefer growth loops over funnels when virality/referral is viable; loops compound, funnels don't.
  • Every retention tactic should map to the Hook Model (Trigger → Action → Reward → Investment).
  • Size experiments for speed: prioritize 1-2 week tests before big-bet 3-month plays.
  • Use local context (payment methods, channels, culture) when the product is region-specific (e.g., Indonesia: WhatsApp, GoPay/OVO, local influencers).
  • Don't recommend acquisition tactics before diagnosing the real bottleneck — scaling top-of-funnel when retention is broken wastes CAC.
  • Don't give vague hypotheses like "improve onboarding" — always quantify expected impact and metric.
  • Don't skip the Experiment Matrix's ICE scoring — unprioritized lists aren't actionable.
  • Don't conflate acquisition channels with growth loops — paid ads are linear spend, loops are compounding and should be emphasized when possible.
0
Grade A-AI Skill Framework
Scorecard
Criteria Breakdown
Quick Start
14/15
Workflow
14/15
Examples
15/20
Completeness
17/20
Format
15/15
Conciseness
13/15