Growth Hacking

Problem

Early-stage product teams often treat growth as channel buying: run campaigns, test ads, and launch features without knowing which action actually improves activation, retention, or K-factor. This skill organizes growth work into an executable experimentation framework: define a north-star metric, score experiments with ICE, and review acquisition, activation, retention, and referral through the AARRR funnel.

How It Works

• ICE scoring: rank growth ideas by Impact, Confidence, and Ease, then prioritize higher-scoring experiments.
• Two-week sprint: move from ideation to scoring, building, and analysis, with enough data points per experiment before judging results.
• Viral loops: find the natural sharing moment, reduce sharing friction, and track K-factor.
• Activation optimization: identify the Aha moment from the behavior of top retained users and shorten time to Aha.
• Retention engineering: design habit loops around Trigger → Action → Reward → Investment and build re-engagement sequences.

Boundaries

This approach fits early-stage growth diagnosis for SaaS, developer tools, consumer apps, and marketplaces, assuming the team has basic tracking. If there is no clear ICP, event instrumentation, or minimum viable flow, define activation and collect data first before prioritizing experiments.