Growth Hacking

Triggers

• growth hacking
• user acquisition
• viral growth
• growth experiment
• conversion funnel
• referral program
• viral loop
• A/B testing
• growth metrics
• user retention
• activation rate
• churn reduction
• product-led growth
• growth model
• CAC optimization
• LTV optimization
• north star metric
• growth channel

Instructions

Growth Strategy Development

1. Identify the North Star metric that best represents product value delivery.
2. Use web_search and browser_navigate to research competitor growth strategies, industry benchmarks, and proven growth playbooks.
3. Map the full growth funnel: Awareness > Acquisition > Activation > Retention > Revenue > Referral (AARRR).
4. Identify the weakest stage of the funnel and prioritize experiments there.
5. Save growth strategy using knowledge_write.

Growth Experiment Design and Execution

1. Design experiments using the ICE framework: Impact (1-10), Confidence (1-10), Ease (1-10).
2. Prioritize experiments by ICE score, running highest-scoring first.
3. Define clear hypotheses, success metrics, sample sizes, and duration for each experiment.
4. Run 10+ experiments per month, aiming for 30% winner rate.
5. Document all experiment results using knowledge_write for institutional learning.

Viral Mechanics and Referral Programs

1. Design viral loops: identify the core action that triggers sharing.
2. Build referral programs with clear incentives for both referrer and referred.
3. Optimize the viral coefficient (K-factor) to exceed 1.0 for sustainable viral growth.
4. Use browser_navigate to study competitor referral programs and viral mechanics.
5. Track viral coefficient and referral conversion rates.

Conversion Funnel Optimization

1. Map every step of the user journey from first touch to conversion.
2. Identify drop-off points using analytics (via browser_navigate to dashboards).
3. Design A/B tests for each funnel stage: landing pages, onboarding, activation, purchase.
4. Optimize CAC (Customer Acquisition Cost) and track LTV:CAC ratio (target 3:1+).
5. Implement multivariate testing for complex funnels.

Product-Led Growth

1. Optimize user onboarding: reduce time-to-value, improve activation rate (target 60%+).
2. Identify product features that drive retention and double down on them.
3. Build in-product sharing and collaboration features that naturally drive growth.
4. Design free-to-paid conversion paths with clear value gates.

Marketing Automation

1. Design email sequences for onboarding, re-engagement, and conversion.
2. Set up retargeting campaigns for users who dropped off at key funnel stages.
3. Build personalization engines that adapt messaging to user behavior.
4. Use email_send for automated sequence delivery.

Analytics and Attribution

1. Set up cohort analysis to track user behavior over time.
2. Build attribution models to understand which channels drive quality users.
3. Use browser_navigate to monitor analytics dashboards and extract insights.
4. Track key metrics: DAU/MAU ratio, activation rate, retention curves, revenue per user.
5. Report growth metrics and experiment results using knowledge_write.

Tools Reference

• web_search for competitor research, growth playbook research, channel discovery
• browser_navigate, browser_extract for analytics dashboards, competitor analysis, funnel monitoring
• knowledge_write for persisting experiment results, growth strategies, and metrics
• knowledge_search for retrieving previous experiment data and growth learnings
• email_send for automated email sequences and re-engagement campaigns

Deliverables

Growth Experiment Tracker

# Growth Experiment Log

## Experiment: [Name]
- **Hypothesis**: If we [change], then [metric] will [improve by X%] because [reason]
- **ICE Score**: Impact: X, Confidence: Y, Ease: Z = Total: N
- **Metric**: [Primary metric to track]
- **Duration**: [X days/weeks]
- **Sample Size**: [N users per variant]
- **Result**: [Winner/Loser/Inconclusive]
- **Learning**: [What we learned]
- **Next Step**: [Follow-up experiment or implementation]

Growth Model Template

# Growth Model

## North Star Metric: [Metric]
## AARRR Funnel
| Stage | Current Rate | Target Rate | Key Lever |
|-------|-------------|-------------|-----------|
| Awareness | X | Y | [Channel] |
| Acquisition | X% | Y% | [Tactic] |
| Activation | X% | Y% | [Feature] |
| Retention | X% | Y% | [Strategy] |
| Revenue | $X | $Y | [Model] |
| Referral | X% | Y% | [Mechanism] |

## Viral Loop Design
1. User completes [core action]
2. User is prompted to [share mechanism]
3. Recipient sees [value proposition]
4. Recipient signs up because [incentive]
5. K-factor: [current] -> [target]

Success Metrics

• User Growth Rate: 20%+ month-over-month organic growth
• Viral Coefficient: K-factor > 1.0 for sustainable viral growth
• CAC Payback Period: < 6 months for sustainable unit economics
• LTV:CAC Ratio: 3:1 or higher for healthy growth margins
• Activation Rate: 60%+ new user activation within first week
• Retention Rates: 40% Day 7, 20% Day 30, 10% Day 90
• Experiment Velocity: 10+ growth experiments per month
• Winner Rate: 30% of experiments show statistically significant positive results

Verify

• The actual channel was reached (post URL, message ID, or platform-side confirmation captured), not just a draft saved locally
• Targeting parameters (subreddit, hashtag, audience, time zone) match what the growth-hacking guide prescribes for the chosen platform
• Copy was checked against the platform's character/format limits before posting; the final character count is recorded
• Engagement plan for the first 1-2 hours after posting is written down with specific actions, not 'monitor and reply'
• At least one platform-specific anti-pattern from the skill (e.g., 'don't ask for upvotes', 'don't post the same link to multiple subs') was explicitly checked against the draft
• A measurable success metric (impressions, signups, click-through, replies) is defined with a numeric threshold before the post goes live