Elite Marketing Strategist — Growth Loops + JTBD

Name: Elite Marketing Strategist — Growth Loops + JTBD
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Author: vlados

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Description

Elite marketing strategy combining Brian Balfour’s growth loops, Jobs-to-be-Done framework, Blue Ocean Strategy, attribution modeling, product-led growth, and community-driven tactics. Use for comprehensive marketing strategy, channel selection, growth experimentation, attribution analysis, and…

What Claude Learns

→ Core Philosophy
→ Strategic Frameworks
→ Jobs-to-be-Done (JTBD) Theory
→ Blue Ocean Strategy
→ Growth Loops (Brian Balfour Framework)
→ Product-Led Growth (PLG)

Installation

1. Visit the GitHub repository: https://github.com/vlados/lawdiff
2. Copy the SKILL.md file contents
3. Save to ~/.claude/commands/skill-name.md
4. Restart Claude Code to load the new skill

Stack & Dependencies

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Frequently Asked Questions

Is Elite Marketing Strategist u2014 Growth Loops + JTBD free to use?

Yes u2014 Elite Marketing Strategist u2014 Growth Loops + JTBD is free. Install it directly with one command (`npx mkt-skills install marketer`) or download the SKILL.md file and drop it into your `~/.claude/skills/` directory. No account, no sign-up, no license fee.

Download SKILL.md GitHub

---
name: marketer
description: Elite marketing strategy combining Brian Balfour's growth loops, Jobs-to-be-Done framework, Blue Ocean Strategy, attribution modeling, product-led growth, and community-driven tactics. Use for comprehensive marketing strategy, channel selection, growth experimentation, attribution analysis, and sustainable competitive advantages.
---

# Elite Marketer

Build compounding growth systems through customer-centric strategy, systematic experimentation, and data-driven channel optimization.

## Core Philosophy

Marketing is not about tactics—it's about understanding why customers choose you (Jobs-to-be-Done), building self-reinforcing growth systems (Growth Loops), and creating sustainable competitive advantages (Blue Ocean Strategy). Elite marketers focus on compounding mechanisms over linear funnels.

## Strategic Frameworks

### Jobs-to-be-Done (JTBD) Theory

Customers don't buy products—they "hire" them to make progress in their lives. Understand the job, win the market.

**The Three Job Dimensions:**

**1. Functional Job** (The practical task)
- What are they trying to accomplish?
- What's the current solution they're "firing"?
- What progress are they seeking?

**2. Emotional Job** (How they want to feel)
- What emotional outcome do they desire?
- What feelings are they avoiding?
- What does success feel like emotionally?

**3. Social Job** (How they want to be perceived)
- How do they want others to see them?
- What tribe/identity are they joining?
- What status are they seeking?

**JTBD Interview Framework:**

"Tell me about the last time you [solved this problem]..."
- What prompted you to look for a solution?
- What alternatives did you consider?
- What made you choose [product]?
- What was the moment you decided to switch?
- What concerns or anxieties did you have?
- What would have happened if you'd done nothing?

**Application:**
- Position product around job, not features
- Identify competition as anything hired for same job (including inaction)
- Segment by job-to-be-done, not demographics
- Innovate by solving job better than alternatives

**Example:** Milkshake case study revealed morning commuters hired milkshakes for "make my commute less boring" job, not "satisfy hunger" job. Different job = different marketing, product improvements, competition.

### Blue Ocean Strategy

Create uncontested market space where competition becomes irrelevant through value innovation.

**The Four Actions Framework:**

**Eliminate**: What factors can you remove that the industry takes for granted?
**Reduce**: What factors can you reduce well below industry standard?
**Raise**: What factors can you raise well above industry standard?
**Create**: What factors can you create that the industry has never offered?

**Strategy Canvas Exercise:**
1. Map competitors on key industry factors
2. Identify where everyone competes (red ocean)
3. Apply four actions to create new value curve
4. Validate with customer research

**Real Examples:**
- **Warby Parker**: Eliminated retail overhead, reduced price 70%, raised style/quality, created virtual try-on
- **Dollar Shave Club**: Eliminated retail distribution, reduced price 80%, raised convenience, created subscription model
- **Slack**: Eliminated enterprise complexity, reduced setup time, raised team collaboration, created searchable communication

**Validation Checklist:**
- [ ] Focus: Does your strategy concentrate on factors that matter most to customers?
- [ ] Divergence: Does your value curve differ dramatically from competitors?
- [ ] Compelling tagline: Can you articulate your blue ocean in one sentence?
- [ ] Commercial viability: Can you profit at strategic price point?

### Growth Loops (Brian Balfour Framework)

Sustainable growth comes from self-reinforcing loops, not linear funnels. Loops compound, funnels don't.

**Anatomy of a Growth Loop:**

Input → Action → Output → New Input

Output of one cycle becomes input to next cycle, creating compounding growth.

**The Five Core Loop Types:**

**1. Content/SEO Loop**
- User creates content → Content ranks in search → New users find content → New users create more content
- Examples: Quora, Medium, Wikipedia, Pinterest
- Timeframe: 6-12 months to compound
- Optimal for: Platforms with user-generated content

**2. Viral Loop**
- User joins → User invites friends → Friends join → Friends invite their friends
- Formula: Growth = Conversion rate × Viral coefficient (K) × Cycle time
- K > 1 = Exponential growth
- Examples: Dropbox referrals, WhatsApp, PayPal sender/receiver
- Optimal for: Products with network effects

**3. Performance Marketing Loop**
- Revenue → Reinvest in ads → New customers → More revenue → Larger ad budget
- Key metric: LTV:CAC ratio (need 3:1 minimum for sustainable loop)
- Examples: DTC brands, SaaS with strong retention
- Timeframe: 30-90 days per cycle
- Optimal for: High-margin products with repeatable acquisition

**4. Sales Loop**
- Close customer → Customer refers → Sales rep follows up → Close new customer
- Examples: B2B SaaS, professional services
- Strengthen with: Incentives, easy referral mechanisms, sales training
- Optimal for: Relationship-driven purchases

**5. User-Generated Content (UGC) Loop**
- User creates content → Content attracts users → New users create content
- Examples: TikTok, YouTube, Instagram
- Strengthen with: Creator incentives, discovery algorithms, tools
- Optimal for: Social platforms, marketplaces, review sites

**Growth Loop Design Process:**

1. **Map Current User Journey**
   - What triggers initial awareness?
   - What actions do users take?
   - What outputs generate more inputs?

2. **Identify Loop Opportunities**
   - Where do users naturally share/create?
   - What outputs could drive acquisition?
   - What would motivate amplification?

3. **Build Minimum Viable Loop (MVL)**
   - Design simplest functional version
   - Instrument to measure cycle time and amplification
   - Launch to 5-10% of users

4. **Optimize Loop Mechanics**
   - Increase conversion at each step
   - Decrease cycle time
   - Raise amplification factor
   - Remove friction points

5. **Stack Multiple Loops**
   - Combine content + viral + paid loops
   - Create reinforcing effects
   - Build defensible moat

**Critical Metrics:**

- **Cycle Time**: How long from input to output?
- **Conversion Rate**: % progressing through each step
- **Amplification Factor**: How many new inputs per output?
- **Loop Quality**: Do loop-acquired users complete loop themselves?

Target: <30 day cycle time, >40% step conversion, >1.5 amplification factor

### Product-Led Growth (PLG)

Let the product drive acquisition, expansion, conversion, and retention instead of sales teams.

**The PLG Flywheel:**

Free users → Try product → Experience value → Upgrade → Advocate → Bring more free users

**PLG Prerequisites:**
- Product delivers value before payment (freemium or free trial)
- User can self-serve signup and onboarding
- Time-to-value < 5 minutes ideally
- Clear upgrade path when hitting limits
- Built-in viral mechanisms

**Optimize Three Stages:**

**1. Acquisition (Free Users)**
- SEO for bottom-funnel keywords
- Product-qualified leads vs marketing-qualified leads
- Viral invite mechanisms
- Integration ecosystems

**2. Activation (First Value Experience)**
- Onboarding that showcases core value immediately
- Progressive disclosure of features
- "Aha moment" within first session
- Automated email sequences for incomplete setups

**3. Monetization (Conversion to Paid)**
- Value-based pricing tied to usage
- Upgrade prompts at point of need
- Seat-based or usage-based pricing
- Self-serve checkout

**4. Expansion (Increased Spending)**
- Usage naturally drives upgrades
- Team expansion through invites
- Feature upsells at relevant moments
- Annual plan conversions

**PLG Metrics:**

- **Time to Value (TTV)**: Minutes until user experiences core benefit
- **Product-Qualified Lead (PQL)**: Users who've experienced key value moments
- **Free-to-Paid Conversion**: % of free users who upgrade
- **Expansion Revenue**: Revenue growth from existing customers
- **Viral Coefficient**: New signups per existing user

**Examples:** Slack (team invites), Zoom (meeting participants), Dropbox (shared folders), Notion (workspace collaboration)

### Community-Led Growth

Build engaged communities that reduce CAC, increase retention, and create defensible moats.

**Why Communities Work:**
- 20-50% lower CAC through word-of-mouth
- 2-5x higher retention vs non-community members
- Creates switching costs (lose network if you leave)
- Generates user-generated content naturally
- Provides feedback and co-creation opportunities

**Community Types:**

**1. Support Community**
- Peer-to-peer help reduces support costs
- Power users answer questions
- Examples: Stack Overflow, Apple Communities

**2. Content Community**
- Users create/share content
- Algorithms surface best content
- Examples: Reddit, TikTok, Medium

**3. Practice Community**
- Users improve skills together
- Courses, workshops, challenges
- Examples: Peloton, Duolingo leagues

**4. Brand Community**
- Shared identity around brand
- Exclusive access, events, perks
- Examples: Harley Davidson HOG, Sephora Beauty Insider

**5. Network Community**
- Connect members with each other
- Facilitate relationships and transactions
- Examples: LinkedIn groups, Airbnb host communities

**Build Stages:**

**Stage 1: Gather (First 100 Members)**
- Recruit passionate early adopters manually
- Create intimate space (Slack, Discord, Circle)
- Founder-led engagement daily
- Focus: Quality over quantity

**Stage 2: Engage (100-1,000 Members)**
- Develop content calendar and rituals
- Empower community moderators
- Create member onboarding process
- Focus: Establishing culture and norms

**Stage 3: Scale (1,000-10,000+ Members)**
- Automate onboarding and guidelines
- Create sub-communities by topic/location
- Build recognition and reward systems
- Focus: Self-sustaining engagement

**Stage 4: Monetize**
- Premium tiers with exclusive access
- Sponsorships and partnerships
- Educational content and certifications
- Events and conferences

**Community Engagement Formula:**

**Content Strategy**: 60% education, 30% inspiration, 10% promotion
**Posting Cadence**: Daily for small communities, multiple times daily for large
**Response Time**: <2 hours for questions/comments
**Recognition**: Highlight member wins weekly

**Key Metrics:**
- Daily Active Users (DAU) / Monthly Active Users (MAU) ratio
- Posts per member per month
- Reply rate to new member questions
- Net Promoter Score (NPS) of community members
- Community-sourced revenue percentage

### Attribution Modeling

Understand true channel value and optimize budget allocation through multi-touch attribution.

**Attribution Models:**

**1. Last-Touch Attribution** (Simple but misleading)
- Credits final touchpoint before conversion
- Easy to measure, severely undervalues awareness channels
- Use only for: Simple, short-cycle purchases

**2. First-Touch Attribution**
- Credits initial touchpoint that started journey
- Overvalues top-of-funnel, ignores conversion optimization
- Use for: Brand awareness campaign measurement

**3. Linear Attribution**
- Equal credit to all touchpoints
- Simple but unrealistic (not all touches are equal)
- Use for: Baseline understanding of journey complexity

**4. Time-Decay Attribution**
- More credit to recent touchpoints
- Better than linear, still somewhat arbitrary
- Use for: Longer sales cycles where recency matters

**5. Position-Based (U-Shaped) Attribution**
- 40% to first touch, 40% to last, 20% to middle
- Recognizes importance of introduction and conversion
- Use for: Balanced view of full funnel

**6. Data-Driven (Algorithmic) Attribution** (BEST)
- Machine learning determines credit based on impact
- Accounts for interaction effects between channels
- Requires: Significant data volume (1,000+ conversions/month)
- Use for: Sophisticated marketing with multiple channels

**Implementation Steps:**

1. **Tracking Setup**
   - UTM parameters on all links (consistent taxonomy)
   - Cookie tracking for return visitors
   - Cross-device identification where possible
   - Server-side tracking for accuracy

2. **Customer Journey Mapping**
   - Identify all touchpoints in typical journey
   - Measure time between touchpoints
   - Document common paths to conversion

3. **Model Selection**
   - Start with position-based for 3+ month data collection
   - Upgrade to data-driven when dataset sufficient
   - Run multiple models in parallel for comparison

4. **Budget Reallocation**
   - Identify undervalued channels (high assist, low last-touch)
   - Test increasing spend on high-ROI channels
   - Don't kill channels immediately—measure lift

5. **Ongoing Optimization**
   - Update attribution model quarterly
   - Account for seasonality in analysis
   - Test incrementality with hold-out groups

**Common Findings:**
- Organic search often 2-3x more valuable than last-touch suggests
- Display ads primarily valuable as awareness, not last-touch
- Email's true value often 40-60% higher than last-touch shows
- Social often strong assist channel, weak last-touch

**Tool Stack:**
- Google Analytics 4 (free, data-driven attribution)
- Segment (data collection and routing)
- Northbeam, Hyros, Triple Whale (advanced attribution for e-commerce)
- Custom data warehouse solution (most sophisticated)

## Channel Strategy & Optimization

### Channel Selection Framework

Not all channels work for all businesses. Choose channels that match your customer acquisition economics.

**Calculate Channel Viability:**

LTV (Lifetime Value) must be >3x CAC (Customer Acquisition Cost)

**LTV = Average Order Value × Purchase Frequency × Customer Lifespan × Margin**
**CAC = Marketing Spend / New Customers Acquired**

**Channel-Product Fit Matrix:**

**Content/SEO**: High LTV, long sales cycle, education-driven, complex products
**Paid Search**: High intent, clear keywords, strong margins, immediate need
**Paid Social**: Visual products, impulse purchases, targeting specific demographics
**Email**: Re-engagement, repeat purchases, relationship-building
**Influencer**: Trust-driven, lifestyle products, younger demographics
**Affiliate**: Performance-based, established market, strong conversion rates
**PR**: Brand building, fundraising announcements, thought leadership
**Events**: Enterprise sales, community building, education sector
**Direct Sales**: High-ticket, complex, relationship-driven

**Test-Learn-Scale Protocol:**

**Phase 1: Micro-Test ($500-2000 budget)**
- Run for 2-4 weeks minimum
- Test 2-3 message variants
- Target narrow, ideal customer segment
- Goal: Is CAC < 1/3 LTV?

**Phase 2: Meso-Test ($5,000-10,000)**
- Expand winning messages
- Broader audience while maintaining targeting
- Optimize landing pages
- Goal: Consistent CAC across 4-6 weeks

**Phase 3: Scale (10x+ investment)**
- Automate what works
- Test new creatives monthly
- Monitor for channel saturation
- Goal: Maintain CAC while growing volume

**When to Kill a Channel:**
- CAC > 1/2 LTV after 3 months of optimization
- Declining ROAS despite creative refreshes
- Channel maxed out (can't increase spend without CAC spike)
- Better opportunities elsewhere

### Paid Advertising Optimization

**Creative Best Practices:**

**Facebook/Instagram:**
- Video outperforms static 2:1 typically
- Square or vertical formats (mobile-first)
- Hook in first 3 seconds (stop the scroll)
- Minimal text on image (Facebook algorithm penalizes heavy text)
- User-generated content outperforms polished ads 30-40%
- Test 5-7 creative variants per campaign
- Refresh creative every 4-6 weeks (avoid fatigue)

**Google Search:**
- Responsive search ads with 8-10 headlines, 3-4 descriptions
- Include target keyword in 2+ headlines
- Emotional headline + logical description combo
- Use all extensions: Sitelink, callout, structured snippet, call
- Quality Score >7 required for cost efficiency
- Match landing page messaging to ad copy exactly

**LinkedIn:**
- Image ads: 1200×627 px, professional but eye-catching
- Video ads: First-person testimonials work best
- Targeting: Job title + company size + industry
- Expect 2-3x higher CPC than Facebook, but higher quality for B2B
- Retargeting crucial (first touch won't convert)

**Targeting Strategy:**

**Layer 1: Core Audience**
- Demographics matching ICP
- Behavioral signals of intent
- Lookalike audiences of customers

**Layer 2: Retargeting**
- Website visitors (last 30 days)
- Engagement with content (video watchers, post engagers)
- Cart abandoners (highest priority)
- Past customers (cross-sell, upsell)

**Layer 3: Exclusions**
- Current customers (unless upselling)
- Employees and competitors
- Low-quality converters
- Converted users from ongoing campaigns

**Budget Allocation by Funnel:**
- Awareness: 30-40% (cold traffic, brand building)
- Consideration: 30-40% (retargeting, nurturing)
- Conversion: 20-40% (high-intent, retargeting converters)

Adjust based on CAC:LTV by stage. If bottom-funnel has 5:1 ROAS, skew budget there.

### Conversion Rate Optimization (CRO)

**Prioritization Framework: PIE**

**Potential**: How much improvement is possible?
**Importance**: How valuable is the page?
**Ease**: How difficult to implement?

Score each 1-10, multiply, test highest scores first.

**High-Impact Tests (Priority Order):**

1. **Headline** (Biggest impact)
   - Clearer benefit communication
   - Stronger emotional appeal
   - Curiosity-driven variants

2. **Hero Image/Video**
   - Show product in use vs static shot
   - Before/after comparisons
   - Human faces increase trust

3. **Call-to-Action**
   - Button color (contrast with page)
   - Button copy (first-person: "Start my trial" > "Start your trial")
   - Placement (above fold + after social proof)
   - Size and prominence

4. **Social Proof**
   - Quantity: "2,347 customers" vs "thousands"
   - Specificity: Full names, photos, companies
   - Placement: Near objections and CTAs
   - Format: Video testimonials convert best

5. **Form Length**
   - Remove non-essential fields
   - Multi-step forms can increase conversions 20-30%
   - Only ask what you'll actually use

6. **Page Speed**
   - Every 1-second delay = 7% conversion loss
   - Mobile page speed crucial (70%+ of traffic)
   - Compress images, minimize scripts

7. **Trust Signals**
   - Security badges near payment
   - Money-back guarantees
   - Press mentions and awards
   - Industry certifications

**Testing Discipline:**
- One test at a time (isolate variables)
- 95% statistical confidence minimum
- Full business cycle (7+ days, account for day-of-week variance)
- Document all tests in central repository
- Run winning variants for 30 days before next test

**Tools:**
- VWO, Optimizely, Google Optimize (A/B testing platforms)
- Hotjar, FullStory, Clarity (heatmaps and session recordings)
- Google Analytics, Amplitude (funnel analysis)

Target: 10-30% improvement per winning test, compound quarterly.

## Modern Marketing Approaches

### AI-Augmented Marketing

**High-Value AI Applications:**

**Content Creation at Scale**
- Blog post outlines and first drafts
- Social media caption variants
- Email subject line testing (generate 50+ variants)
- Product description variations for A/B testing
- Ad copy permutations

**Audience Research**
- Analyze thousands of customer reviews for insights
- Reddit/forum thread analysis for pain points
- Competitor analysis and positioning gaps
- Trend identification and topic clustering

**Personalization**
- Dynamic email content by segment
- Website copy variations by traffic source
- Product recommendations by behavior
- Chatbot conversations and support

**Analytics Enhancement**
- Predictive customer lifetime value
- Churn risk scoring
- Next-best-action recommendations
- Automated anomaly detection

**Process Optimization**
- Bid optimization in paid campaigns
- Send-time optimization for emails
- Budget allocation recommendations
- Creative fatigue detection

**AI Limitations:**
- No strategic thinking (you set strategy, AI executes)
- Can't read between the lines of qualitative research
- Limited brand voice consistency without extensive training
- May hallucinate data or statistics
- Needs human validation for customer-facing content

**Best Practice:** Use AI for speed, scale, and initial drafts. Always have human review for strategy, brand voice, accuracy, and final approval.

### Privacy-First Marketing (2025 Reality)

**Cookie Deprecation Impact:**

Third-party cookies dying → First-party data becomes crucial

**Adapt Strategy:**

**1. Build First-Party Data Assets**
- Email capture with valuable lead magnets
- Account creation with gated content
- SMS/push notification permissions
- Loyalty programs with points/rewards
- Community memberships

**2. Server-Side Tracking**
- Implement server-side Google Tag Manager
- Use Segment or similar for event tracking
- First-party cookie tracking where possible
- Reduces ad blocker impact, improves accuracy

**3. Privacy-Compliant Attribution**
- Google Enhanced Conversions (hashed email matching)
- Conversion API for Facebook/Meta
- Aggregated measurement protocols
- Incrementality testing with hold-out groups

**4. Contextual Targeting Renaissance**
- Target based on page content, not user behavior
- Keyword targeting in display
- Topic-based YouTube ads
- Intent-based rather than identity-based

**5. First-Party Audiences**
- Customer match campaigns (upload email lists)
- Lookalike audiences from customer data
- Engagement-based remarketing
- Value-based lookalikes (upload LTV data)

**Expect:** 10-20% increase in CAC short-term, but first-party data relationships will compound long-term value.

## Measurement Framework

**North Star Metric (NSM)**

Single metric that best captures core value delivered to customers.

**Examples:**
- Airbnb: Nights booked
- Spotify: Time spent listening
- Facebook: Daily active users
- Amazon: Purchase frequency
- Slack: Messages sent by teams

Choose NSM that:
- Directly reflects customer value
- Indicates business health
- Influences revenue
- Your team can impact

**Supporting Metrics Hierarchy:**

**Tier 1: Business Outcomes**
- Revenue, profit, growth rate
- Customer acquisition cost (CAC)
- Lifetime value (LTV)
- LTV:CAC ratio (target: 3:1 minimum)

**Tier 2: North Star & Inputs**
- NSM and components that drive it
- Activation rate (% experiencing core value)
- Retention rate (cohort-based)
- Engagement metrics (DAU/MAU, session frequency)

**Tier 3: Channel Metrics**
- ROAS by channel
- Conversion rate by traffic source
- Email open/click rates
- Social engagement rate
- SEO traffic and rankings

**Tier 4: Tactical Metrics**
- Ad CTR, CPC, CPM
- Landing page conversion rate
- Form completion rate
- Page speed, bounce rate

Focus leadership reporting on Tiers 1-2. Use Tiers 3-4 for operational optimization.

**Cohort Analysis:**

Track user cohorts by month/week of acquisition through their lifecycle.

**Key Questions:**
- Do cohorts improve over time? (Learning effect)
- Which acquisition channels produce best cohorts?
- When do cohorts plateau or churn?
- What's the payback period by cohort?

**Retention Curves:**

Plot % of cohort still active by days/weeks/months since acquisition.

**Good retention curves:**
- Plateau rather than trending to zero
- Each cohort better than last
- Minimal drop-off after first experience

**Poor retention curves:**
- Continual downward trend
- Worsening cohorts over time
- Large initial drop-off (activation issue)

Fix retention before scaling acquisition—leaky buckets don't fill.

## Experimentation Framework

**Velocity of Learning > Velocity of Launches**

Run more experiments faster to maximize learning rate.

**Experiment Design:**

1. **Hypothesis**: "We believe [change] will result in [outcome] because [reasoning]"
2. **Metrics**: Primary metric + guardrail metrics (ensure no negative side effects)
3. **Sample Size**: Calculate required sample for statistical significance
4. **Duration**: Minimum 7 days, full business cycle
5. **Success Criteria**: Define ahead of time, prevent cherry-picking

**Experiment Types:**

**Feature Tests**: New functionality impact on engagement/retention
**Growth Tests**: New acquisition channel or tactic viability
**Optimization Tests**: Improving existing conversion funnels
**Pricing Tests**: Different price points, structures, or presentation

**Document Everything:**

Build centralized experiment log with:
- Hypothesis
- Date run
- Results (win/loss/neutral)
- Impact (% lift in metric)
- Learnings and next steps
- Screenshots/recordings

This becomes invaluable institutional knowledge.

**When to Run More Experiments:**
- Test velocity <2 experiments/week: Increase
- Learning rate slowing: Expand test surface area
- Success rate >70%: Taking insufficient risk
- Success rate <20%: Hypothesis quality issue

**When to Scale Winners:**
- Statistically significant results (95%+ confidence)
- Positive secondary metrics (no cannibalization)
- Reproducible across multiple tests
- Margin of improvement >10% on important metric

## Strategy Execution Checklist

**Quarterly Marketing Planning:**

- [ ] Define North Star Metric and quarterly target
- [ ] Review previous quarter: What worked? What didn't? Why?
- [ ] Map customer journey and identify friction points
- [ ] Audit channel performance: LTV:CAC by source
- [ ] Identify 3-5 growth hypotheses to test
- [ ] Design growth experiments (PIE framework prioritization)
- [ ] Set experiment calendar (2-4 tests per week target)
- [ ] Allocate budget by channel based on performance
- [ ] Define success metrics and review cadence
- [ ] Build attribution model if not existing

**Weekly Growth Meetings:**

- [ ] Review North Star Metric progress
- [ ] Analyze ongoing experiment results
- [ ] Launch new experiments per calendar
- [ ] Channel performance review (ROAS, CAC trends)
- [ ] Creative performance review (refresh needs)
- [ ] Roadblock identification and solution brainstorm

**Monthly Deep Dives:**

- [ ] Cohort analysis: Retention and LTV trends
- [ ] Attribution model review and insights
- [ ] Competitor landscape changes
- [ ] Content performance analysis
- [ ] Community engagement metrics
- [ ] Budget reallocation based on learnings

Elite marketing is systematic, data-driven, and customer-centric. Build loops, not funnels. Test fast, learn faster. Compound growth over time.

Description

What Claude Learns

Installation

Stack & Dependencies

Frequently Asked Questions

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