Requirements
How To Start
- STEP 1: Choose Your FormatDecide what you need:- Full catalog: "Show me all available recipes"- Quick list: "List recipes in compact format"- Single recipe: "Explain the TOKEN-MONITOR recipe"- Filtered view: "Show me Base Cookbook recipes only"STEP 2: Review the OutputThe AI generates your requested format with recipe descriptions, purposes, roles in CRAFT, and example usage. Use this as reference documentation or learning resource.
When to Use This Recipe
Use RECIPE-CHEATSHEET during initial CRAFT onboarding to understand the complete recipe ecosystem and which recipes solve which problems. Request it when you encounter a task and wonder "Is there a recipe for this?" to discover existing capabilities before creating custom solutions. Teams should use it during training sessions to introduce new members to available recipes systematically. Individual users benefit from periodic reviews (monthly or quarterly) to discover recipes they haven't been using but could benefit from. It's essential when troubleshooting workflow issues to verify you're using the optimal recipe for each step rather than manual processes that could be automated.
Recipe FAQ
Q1: What's the difference between detailed and compact formats?
A: Detailed format provides complete explanations for each recipe including why it exists, its role in CRAFT, when to use it, and example executions - ideal for learning and understanding recipes deeply. Compact format shows just recipe names with one-line descriptions - perfect as a quick reference when you know what you're looking for but need a reminder of which recipe handles what.
Q2: How do I find the right recipe for my specific task?
A: Start by describing your task naturally: "What recipe helps with X?" The AI will search the catalog and recommend appropriate recipes. Alternatively, use category filters: "Show me recipes for content creation" or "List error handling recipes." The detailed format includes "When to Use" sections that map common scenarios to recipes.
Q3: What does "Why It's CORE" mean for Base Cookbook recipes?
A: "Why It's CORE" explains why a recipe is foundational to CRAFT rather than optional or specialized. CORE recipes address universal needs (session management, error handling, progress tracking) that every CRAFT user encounters. This helps you prioritize which recipes to learn first and understand their importance to framework operation.
Q4: Can I request information about recipes that don't exist yet?
A: The cheatsheet only catalogs recipes present in loaded cookbook files. If you ask about a recipe that doesn't exist, the AI will tell you it's not found and may suggest similar existing recipes. You can request "Show me all available recipes" to see the complete current catalog and avoid asking about non-existent recipes.
Q5: How often should I review the recipe cheatsheet?
A: Review the complete cheatsheet when first learning CRAFT to understand the ecosystem. After that, use it on-demand when you encounter new tasks ("What recipe helps with this?") or when cookbooks are updated with new recipes. Teams should review quarterly to ensure everyone knows about newly added capabilities.
Actual Recipe Code
(Copy This Plaintext Code To Use)
# =========================================================# BEGIN: RCP-004-002-016-PERF-ANALYZER# =========================================================# =========================================================# RECIPE: BEGIN: CAMPAIGN-PERFORMANCE-ANALYZER# =========================================================# Recipe ID: RCP-004-002-016-PERF-ANALYZER-v1.00a# Title: Campaign Performance Analyzer# Category: CAT-004-BRAND-IDENTITY# Subcategory: SUBCAT-002-CAMPAIGN-PLANNING# Layer: OPTIMIZATION# Version: 1.00a# Created: November 25, 2025# =========================================================# =========================================================# Licensed under the Business Source License 1.1 (BSL)# Š 2025 Ketelsen Digital Solutions LLC# Free for non-commercial use (research, educational, experimental).# Commercial use requires a license from Ketelsen Digital Solutions LLC.# On or after 2029-01-01, this file will be licensed under Apache 2.0.# =========================================================CAMPAIGN_PERFORMANCE_ANALYZER = Recipe( recipe_id="RCP-004-002-016-PERF-ANALYZER-v1.00a", title="Campaign Performance Analyzer", description="Provides frameworks for tracking, analyzing, and optimizing campaign performance across all platforms and content types. Supports setup mode for initial configuration and review modes for ongoing analysis. Transforms raw metrics into actionable insights and optimization recommendations.", category="CAT-004-BRAND-IDENTITY", subcategory="SUBCAT-002-CAMPAIGN-PLANNING", layer="OPTIMIZATION", difficulty="medium", estimated_time="30-45 minutes (setup) / 20-30 minutes (per review)", version="1.00a", # ========================================================= # RECIPE DEPENDENCIES # ========================================================= dependencies={ "required_inputs": [ { "source": "RCP-004-002-001-CAMPAIGN-ARCH", "input": "campaign_architecture", "description": "Campaign phases, milestones, goals from Recipe 8" }, { "source": "Campaign Goals", "input": "success_metrics", "description": "KPIs and success criteria defined in campaign planning" } ], "conditional_inputs": [ { "source": "Platform Analytics", "input": "performance_data", "description": "Actual metrics from platforms (required for review modes)", "required_when": "analysis_type != 'setup'" } ], "optional_inputs": [ { "source": "Previous Analysis", "input": "comparison_baseline", "description": "Previous period data for trend analysis" }, { "source": "RCP-004-002-006-CONTENT-CAL", "input": "content_calendar", "description": "Content calendar for content-performance correlation" } ], "feeds_into": [ "Campaign optimization decisions", "Content strategy adjustments", "Resource reallocation", "Future campaign planning" ] }, # ========================================================= # PARAMETERS # ========================================================= parameters={ "campaign_architecture": { "type": "text", "required": True, "description": "Campaign Architecture output with phases, milestones, goals", "example": "CAMPAIGN_ARCHITECTURE_BLOCK from Recipe 8" }, "success_metrics": { "type": "list", "required": True, "description": "KPIs defined in campaign planning", "example": ["Beta signups", "Social followers", "Engagement rate", "Website traffic"] }, "analysis_type": { "type": "enum", "required": True, "options": ["setup", "weekly-review", "phase-review", "final"], "description": "Type of analysis to perform" }, "performance_data": { "type": "dict", "required": False, "description": "Actual metrics from platforms (required for reviews)", "example": {"X_followers": 1250, "engagement_rate": 3.2, "beta_signups": 47} }, "review_period": { "type": "string", "required": False, "description": "Time period being analyzed", "example": "Week 3" or "Phase 1" or "Full Campaign" }, "comparison_baseline": { "type": "dict", "required": False, "description": "Previous period data for comparison", "example": {"X_followers": 1100, "engagement_rate": 2.8, "beta_signups": 32} }, "content_calendar": { "type": "text", "required": False, "description": "Content Calendar for content-performance correlation" }, "include_recommendations": { "type": "boolean", "required": False, "default": True, "description": "Include optimization recommendations in output" } }, # ========================================================= # METRICS FRAMEWORK # ========================================================= metrics_framework={ "awareness_metrics": { "description": "Metrics measuring reach and visibility", "metrics": [ {"name": "Followers/Subscribers", "platforms": "All", "frequency": "Weekly"}, {"name": "Impressions", "platforms": "All", "frequency": "Weekly"}, {"name": "Reach", "platforms": "X, LinkedIn, TikTok", "frequency": "Weekly"}, {"name": "Video Views", "platforms": "YouTube, TikTok", "frequency": "Weekly"}, {"name": "Website Visitors", "platforms": "Analytics", "frequency": "Weekly"}, {"name": "Blog Page Views", "platforms": "Analytics", "frequency": "Weekly"} ], "primary_for_phase": ["Pre-Beta Awareness", "Early phases"] }, "engagement_metrics": { "description": "Metrics measuring interaction quality", "metrics": [ {"name": "Engagement Rate", "platforms": "All", "frequency": "Weekly", "calculation": "(Likes + Comments + Shares) / Impressions à 100"}, {"name": "Likes/Reactions", "platforms": "All", "frequency": "Weekly"}, {"name": "Comments", "platforms": "All", "frequency": "Weekly"}, {"name": "Shares/Reposts", "platforms": "All", "frequency": "Weekly"}, {"name": "Saves/Bookmarks", "platforms": "X, LinkedIn, TikTok", "frequency": "Weekly"}, {"name": "Click-Through Rate", "platforms": "All", "frequency": "Weekly"}, {"name": "Average Watch Time", "platforms": "YouTube, TikTok", "frequency": "Weekly"}, {"name": "Reply Rate", "platforms": "X, LinkedIn, Mastodon", "frequency": "Weekly"} ], "primary_for_phase": ["All phases"] }, "conversion_metrics": { "description": "Metrics measuring desired actions", "metrics": [ {"name": "Beta Signups", "platforms": "CRAFTFramework.ai", "frequency": "Daily/Weekly"}, {"name": "Waitlist Additions", "platforms": "CRAFTFramework.ai", "frequency": "Daily/Weekly"}, {"name": "Email Subscribers", "platforms": "Email Platform", "frequency": "Weekly"}, {"name": "Link Clicks", "platforms": "All", "frequency": "Weekly"}, {"name": "Landing Page Conversions", "platforms": "Analytics", "frequency": "Weekly"}, {"name": "CTA Completion Rate", "platforms": "Analytics", "frequency": "Weekly"} ], "primary_for_phase": ["Beta Launch", "Conversion phases"] }, "community_metrics": { "description": "Metrics measuring community health", "metrics": [ {"name": "Founding Chef Applications", "platforms": "CRAFTFramework.ai", "frequency": "Weekly"}, {"name": "User-Generated Content", "platforms": "All", "frequency": "Weekly"}, {"name": "Mentions", "platforms": "All", "frequency": "Weekly"}, {"name": "Community Questions", "platforms": "All", "frequency": "Weekly"}, {"name": "Referral Traffic", "platforms": "Analytics", "frequency": "Weekly"}, {"name": "Return Visitors", "platforms": "Analytics", "frequency": "Weekly"} ], "primary_for_phase": ["Community Building phases"] }, "content_metrics": { "description": "Metrics measuring content performance", "metrics": [ {"name": "Top Performing Posts", "platforms": "All", "frequency": "Weekly"}, {"name": "Content Type Performance", "platforms": "All", "frequency": "Weekly"}, {"name": "Pillar Performance", "platforms": "Derived", "frequency": "Weekly"}, {"name": "Blog Traffic per Post", "platforms": "Analytics", "frequency": "Weekly"}, {"name": "Social Traffic to Blog", "platforms": "Analytics", "frequency": "Weekly"}, {"name": "Best Posting Times", "platforms": "All", "frequency": "Monthly"} ], "primary_for_phase": ["All phases"] } }, # ========================================================= # PROMPT TEMPLATE # ========================================================= prompt_template=""" #H->AI::Directive: (Execute Campaign Performance Analyzer recipe) #H->AI::Context: (This recipe provides performance tracking, analysis, and optimization frameworks) # ========================================== # STEP 0: POLICY PRE-CHECK # ========================================== Scan prompt for sensitive categories: - Competitive intelligence - Platform algorithm manipulation - Data privacy concerns IF potential conflict detected: #AI->H::PolicyCaution: (Performance analysis should focus on owned metrics) #AI->H::Note: (Avoid recommendations that manipulate platform algorithms) # ========================================== # STEP 0.5: PERSONA ACTIVATION # ========================================== #AI->H::PersonaSwitch: (Activating Maggie Stratton - Marketing Maven persona) ACTIVE_PERSONA = { "name": "Maggie Stratton", "role": "Integrated Marketing Campaign Strategist", "tagline": "Building data-driven campaigns that convert curiosity into customers", "approach": { "methodology": "RACE Framework Analysis + Continuous Optimization", "communication": "Professional yet accessible (formality: 6/10)", "framework_focus": "Dashboards, trend analysis, insight extraction", "confidence_reporting": "Statistical confidence where applicable" }, "expertise": [ "Marketing analytics", "KPI definition and tracking", "A/B test analysis", "Attribution modeling basics", "Performance optimization" ], "personality": { "openness": 7, "conscientiousness": 9, "extraversion": 5, "agreeableness": 6, "neuroticism": 4 }, "communication_patterns": { "greeting": "Let's see what the data tells us.", "questioning": "What's driving this change...", "structure": "1. Data Review 2. Trend Analysis 3. Insight Extraction 4. Recommendations", "visual_frameworks": "Include dashboards, trend charts, comparison tables" }, "boundaries": { "prohibited": ["Vanity metric overemphasis", "Correlation as causation"], "escalation_triggers": ["Major underperformance", "Strategy pivot needed"], "reality_checks": "Contextualizes metrics appropriately" } } #AI->H::Note: (Maggie will guide you through performance analysis with actionable, data-driven insights) **Maggie's Opening:** "Let's see what the data tells us. Performance analysis isn't just about tracking numbersâit's about understanding what's working, what's not, and why. Then we optimize. Running in {analysis_type} mode." # ========================================== # STEP 1: MODE SELECTION & CONTEXT LOADING # ========================================== #AI->H::Status: (Loading context and configuring analysis mode) **1.1 Analysis Mode Configuration:** CONFIGURE analysis based on analysis_type: IF analysis_type == "setup": MODE_CONFIG = { "purpose": "Create tracking infrastructure", "outputs": ["Metrics Dashboard Template", "Data Collection Guide", "Baseline Targets"], "data_required": False, "estimated_time": "30-45 minutes" } #AI->H::Note: (Setup mode: Creating your measurement framework) IF analysis_type == "weekly-review": MODE_CONFIG = { "purpose": "Assess weekly performance and make tactical adjustments", "outputs": ["Weekly Performance Report", "Quick Wins", "Immediate Adjustments"], "data_required": True, "estimated_time": "20-30 minutes" } #AI->H::Note: (Weekly review mode: Analyzing {review_period} performance) IF analysis_type == "phase-review": MODE_CONFIG = { "purpose": "Comprehensive phase analysis and strategic adjustments", "outputs": ["Phase Performance Report", "Strategic Insights", "Next Phase Recommendations"], "data_required": True, "estimated_time": "30-45 minutes" } #AI->H::Note: (Phase review mode: Analyzing {review_period} performance) IF analysis_type == "final": MODE_CONFIG = { "purpose": "Full campaign retrospective and future planning", "outputs": ["Campaign Performance Report", "Key Learnings", "Future Recommendations"], "data_required": True, "estimated_time": "45-60 minutes" } #AI->H::Note: (Final review mode: Full campaign analysis) **1.2 Input Validation:** CHECK campaign_architecture: EXTRACT campaign goals, phases, milestones EXTRACT timeline and key dates CHECK success_metrics: VALIDATE metrics are measurable CATEGORIZE by metric type (awareness, engagement, conversion, community) IF analysis_type != "setup": CHECK performance_data: IF not provided OR empty: #AI->H::Error: (Performance data required for {analysis_type} mode) #AI->H::Instruction: (Please provide actual metrics for the review period) HALT recipe execution VALIDATE data completeness FLAG any missing metrics **1.3 Context Summary:** **Maggie's Context Check:** "Analysis configured: **Mode:** {analysis_type} **Period:** {review_period or 'N/A - Setup mode'} **Success Metrics:** {count} KPIs defined **Data Available:** {Yes/No/Partial} Let's {setup the framework / analyze the data}." # ========================================== # STEP 2: METRICS FRAMEWORK (SETUP MODE) # ========================================== IF analysis_type == "setup": #AI->H::Status: (Creating metrics tracking framework) **2.1 KPI Definition:** FOR each metric in success_metrics: DEFINE metric_spec = { "metric_name": name, "category": awareness/engagement/conversion/community, "definition": clear definition of what's measured, "data_source": where to get this data, "frequency": how often to track, "baseline": current value or "TBD", "target": goal value, "threshold_warning": value that triggers concern, "threshold_success": value that indicates success } **2.2 Dashboard Template:** GENERATE METRICS_DASHBOARD_TEMPLATE: âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ CAMPAIGN PERFORMANCE DASHBOARD Campaign: {campaign_name} Tracking Period: {start_date} to {end_date} Last Updated: {date} âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ EXECUTIVE SUMMARY âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ Overall Health: [đĸ On Track / đĄ Monitor / đ´ Action Needed] PRIMARY KPIs: ââââââââââââââââââââââââââŦâââââââââââŦâââââââââââŦâââââââââââŦâââââââââââââââââ â Metric â Current â Target â % to Goalâ Trend â ââââââââââââââââââââââââââŧâââââââââââŧâââââââââââŧâââââââââââŧââââââââââââââââ⤠â Beta Signups â ___ â ___ â ___% â âââ â â Total Followers â ___ â ___ â ___% â âââ â â Avg Engagement Rate â ___ â ___ â ___% â âââ â â Website Traffic â ___ â ___ â ___% â âââ â ââââââââââââââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ´âââââââââââââââââ AWARENESS METRICS âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ FOLLOWERS BY PLATFORM: ââââââââââââââââŦâââââââââââŦâââââââââââŦâââââââââââŦâââââââââââââââââŦâââââââââââ â Platform â Current â Last Weekâ Change â Target â Status â ââââââââââââââââŧâââââââââââŧâââââââââââŧâââââââââââŧâââââââââââââââââŧââââââââââ⤠â X/Twitter â ___ â ___ â +/- ___ â ___ â đĸđĄđ´ â â LinkedIn â ___ â ___ â +/- ___ â ___ â đĸđĄđ´ â â YouTube â ___ â ___ â +/- ___ â ___ â đĸđĄđ´ â â TikTok â ___ â ___ â +/- ___ â ___ â đĸđĄđ´ â â Bluesky â ___ â ___ â +/- ___ â ___ â đĸđĄđ´ â â Mastodon â ___ â ___ â +/- ___ â ___ â đĸđĄđ´ â ââââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ´âââââââââââââââââ´âââââââââââ REACH & IMPRESSIONS: ââââââââââââââââŦâââââââââââŦâââââââââââŦâââââââââââ â Platform â Impressionsâ Reach â Imp/Post â ââââââââââââââââŧâââââââââââŧâââââââââââŧââââââââââ⤠â X/Twitter â ___ â ___ â ___ â â LinkedIn â ___ â ___ â ___ â â TikTok â ___ â ___ â ___ â ââââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ ENGAGEMENT METRICS âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ ENGAGEMENT BY PLATFORM: ââââââââââââââââŦâââââââââââŦâââââââââââŦâââââââââââŦâââââââââââŦâââââââââââââââââ â Platform â Eng Rate â Likes â Comments â Shares â Benchmark â ââââââââââââââââŧâââââââââââŧâââââââââââŧâââââââââââŧâââââââââââŧââââââââââââââââ⤠â X/Twitter â ___% â ___ â ___ â ___ â 1-3% good â â LinkedIn â ___% â ___ â ___ â ___ â 2-5% good â â TikTok â ___% â ___ â ___ â ___ â 3-9% good â â YouTube â ___% â ___ â ___ â ___ â 2-5% good â ââââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ´âââââââââââââââââ CONVERSION METRICS âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ ââââââââââââââââââââââââââŦâââââââââââŦâââââââââââŦâââââââââââŦâââââââââââââââââ â Metric â This Weekâ Total â Target â Status â ââââââââââââââââââââââââââŧâââââââââââŧâââââââââââŧâââââââââââŧââââââââââââââââ⤠â Beta Signups â ___ â ___ â ___ â đĸđĄđ´ â â Waitlist Additions â ___ â ___ â ___ â đĸđĄđ´ â â Email Subscribers â ___ â ___ â ___ â đĸđĄđ´ â â Founding Chef Apps â ___ â ___ â ___ â đĸđĄđ´ â ââââââââââââââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ´âââââââââââââââââ CONVERSION FUNNEL: Website Visitors â Landing Page â Signup Form â Confirmed _____ â _____ (___%) â _____ (___%) â _____ (___%) CONTENT PERFORMANCE âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ TOP PERFORMING POSTS THIS WEEK: ââââââŦâââââââââââââââŦâââââââââââââââââââââââââââââââŦâââââââââââŦâââââââââââ â # â Platform â Post Summary â Eng Rate â Clicks â ââââââŧâââââââââââââââŧâââââââââââââââââââââââââââââââŧâââââââââââŧââââââââââ⤠â 1 â ___ â ___ â ___% â ___ â â 2 â ___ â ___ â ___% â ___ â â 3 â ___ â ___ â ___% â ___ â ââââââ´âââââââââââââââ´âââââââââââââââââââââââââââââââ´âââââââââââ´âââââââââââ PERFORMANCE BY PILLAR: ââââââââââââââââââââââââŦâââââââââââŦâââââââââââŦâââââââââââ â Content Pillar â Posts â Avg Eng â Clicks â ââââââââââââââââââââââââŧâââââââââââŧâââââââââââŧââââââââââ⤠â Educational â ___ â ___% â ___ â â Behind-the-Scenes â ___ â ___% â ___ â â Community â ___ â ___% â ___ â â Promotional â ___ â ___% â ___ â â Thought Leadership â ___ â ___% â ___ â ââââââââââââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ BLOG PERFORMANCE âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ ââââââââââââââââââââââââââââââââââââââŦâââââââââââŦâââââââââââŦâââââââââââââââ â Blog Post â Views â Avg Time â Social Clicksâ ââââââââââââââââââââââââââââââââââââââŧâââââââââââŧâââââââââââŧââââââââââââââ⤠â {title} â ___ â ___ â ___ â ââââââââââââââââââââââââââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââââââ WEEK-OVER-WEEK TRENDS âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ [Space for trend visualization/chart data] ACTION ITEMS âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ đ´ URGENT: âĸ [Action items for metrics in red] đĄ MONITOR: âĸ [Items to watch] â
WINS: âĸ [Celebrate successes] âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ **2.3 Data Collection Guide:** GENERATE DATA_COLLECTION_GUIDE: âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ DATA COLLECTION GUIDE âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ COLLECTION SCHEDULE: âĸ Daily: Beta signups, critical conversion events âĸ Weekly: All metrics in dashboard (recommend: every Monday) âĸ Monthly: Deep analysis, trend review, strategy adjustment DATA SOURCES BY PLATFORM: X/Twitter (@KetelsenCRAFT): âĸ Native Analytics: analytics.twitter.com âĸ Metrics: Followers, impressions, engagement, link clicks âĸ Export: CSV available LinkedIn (linkedin.com/in/richketelsen): âĸ Native Analytics: LinkedIn Analytics dashboard âĸ Metrics: Followers, impressions, engagement, demographics âĸ Note: Personal profile analytics more limited than company pages YouTube (@CRAFTFramework): âĸ Native Analytics: YouTube Studio âĸ Metrics: Subscribers, views, watch time, CTR âĸ Export: Available TikTok (@craftframework): âĸ Native Analytics: TikTok Analytics (Creator tools) âĸ Metrics: Followers, views, engagement, demographics âĸ Note: Requires creator/business account Bluesky (@craft-framework.bsky.social): âĸ Native Analytics: Limited native analytics âĸ Workaround: Manual tracking or third-party tools Mastodon (@CRAFTFramework@mastodon.social): âĸ Native Analytics: Post-level stats only âĸ Workaround: Manual tracking Website (CRAFTFramework.ai): âĸ Analytics Tool: [Google Analytics / Plausible / etc.] âĸ Metrics: Visitors, page views, traffic sources, conversions Blog (Ketelsen.ai): âĸ Analytics Tool: [Same as website or separate] âĸ Metrics: Page views, time on page, referral sources âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ **2.4 Target Setting:** GENERATE TARGET_FRAMEWORK: âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ TARGET SETTING FRAMEWORK âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ BASELINE (Current State): Record current metrics before campaign starts TARGETS (SMART Goals): For each metric, define: âĸ Specific: What exactly are we measuring? âĸ Measurable: Can we track it reliably? âĸ Achievable: Is this realistic given resources? âĸ Relevant: Does this support campaign goals? âĸ Time-bound: By when? SUGGESTED TARGET RANGES (adjust based on baseline): AWARENESS TARGETS (6-month campaign): âĸ Follower growth: 50-200% increase from baseline âĸ Weekly impressions: 10-50x follower count âĸ Website traffic: 100-500% increase from baseline ENGAGEMENT TARGETS: âĸ X/Twitter: 1-3% engagement rate âĸ LinkedIn: 2-5% engagement rate âĸ TikTok: 3-9% engagement rate âĸ YouTube: 2-5% engagement rate CONVERSION TARGETS: âĸ Beta signups: [Define based on capacity and goals] âĸ Founding Chef applications: [Define based on program design] âĸ Email subscribers: [Define based on list goals] âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ # ========================================== # STEP 3: PERFORMANCE ANALYSIS (REVIEW MODES) # ========================================== IF analysis_type in ["weekly-review", "phase-review", "final"]: #AI->H::Status: (Analyzing performance data for {review_period}) **3.1 Data Validation:** VALIDATE performance_data: FOR each expected metric: IF metric present: RECORD value ELSE: FLAG as missing #AI->H::Note: (Missing data for: {metric}) IF comparison_baseline provided: VALIDATE baseline data format PREPARE comparison calculations **3.2 Metric Calculations:** CALCULATE derived metrics: // Growth calculations IF comparison_baseline: FOR each metric: absolute_change = current - baseline percent_change = ((current - baseline) / baseline) à 100 trend = "â" if positive else "â" if negative else "â" // Engagement rate engagement_rate = (likes + comments + shares) / impressions à 100 // Conversion rate conversion_rate = conversions / visitors à 100 // Goal progress FOR each target: progress_percent = (current / target) à 100 status = "đĸ" if >= 90% else "đĄ" if >= 70% else "đ´" **3.3 Performance Summary:** GENERATE PERFORMANCE_SUMMARY: âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ PERFORMANCE SUMMARY: {review_period} Analysis Type: {analysis_type} Generated: {current_date} âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ OVERALL ASSESSMENT âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ Campaign Health: [đĸ On Track / đĄ Monitor / đ´ Action Needed] **Quick Stats:** âĸ Period: {review_period} âĸ Days Analyzed: {count} âĸ Content Published: {count} posts âĸ Primary Goal Progress: {percentage}% **Headline Metrics:** ââââââââââââââââââââââââââŦâââââââââââŦâââââââââââŦâââââââââââŦâââââââââââââââââ â Metric â Actual â Target â Progress â vs. Last Periodâ ââââââââââââââââââââââââââŧâââââââââââŧâââââââââââŧâââââââââââŧââââââââââââââââ⤠â {primary_metric_1} â {value} â {target} â {%}% â {+/-X%} â â {primary_metric_2} â {value} â {target} â {%}% â {+/-X%} â â {primary_metric_3} â {value} â {target} â {%}% â {+/-X%} â ââââââââââââââââââââââââââ´âââââââââââ´âââââââââââ´âââââââââââ´âââââââââââââââââ DETAILED METRICS âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ [Insert populated dashboard sections with actual data] TREND ANALYSIS âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ IMPROVING (â): âĸ {metric}: +{X}% from last period âĸ {metric}: +{X}% from last period DECLINING (â): âĸ {metric}: -{X}% from last period STABLE (â): âĸ {metric}: within Âą5% of last period âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ # ========================================== # STEP 4: INSIGHT EXTRACTION # ========================================== IF analysis_type in ["weekly-review", "phase-review", "final"]: #AI->H::Status: (Extracting insights from performance data) **4.1 Pattern Recognition:** ANALYZE performance_data for patterns: CONTENT_PATTERNS: - Which pillar performs best? (highest avg engagement) - Which content type performs best? (threads, images, video) - Which topics resonate most? (from top performers) - Best performing posting times - Platform-specific patterns AUDIENCE_PATTERNS: - Where is growth fastest? - Which platform drives most conversions? - Comment sentiment (if trackable) - Follower-to-engagement ratio by platform CONVERSION_PATTERNS: - Top traffic sources to website - Best performing CTAs - Signup day/time patterns - Funnel drop-off points **4.2 Insight Generation:** GENERATE insights using pattern analysis: INSIGHT_CATEGORIES: WINS (What's Working): - Identify top 3-5 positive patterns - Quantify the success - Hypothesize why it's working OPPORTUNITIES (Could Do More): - Identify underutilized tactics that show promise - Gaps in content mix - Platform opportunities CONCERNS (What's Not Working): - Identify underperforming areas - Quantify the gap - Hypothesize causes SURPRISES (Unexpected Findings): - Note any anomalies - Unexpected successes or failures - External factors that may have influenced results **4.3 Insight Output:** GENERATE INSIGHTS_REPORT: âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ KEY INSIGHTS: {review_period} âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ â
WINS (What's Working) âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ 1. **{Insight Title}** Data: {Supporting metric} Why it matters: {Explanation} Implication: {What to do with this} 2. **{Insight Title}** Data: {Supporting metric} Why it matters: {Explanation} Implication: {What to do with this} đ¯ OPPORTUNITIES (Could Do More) âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ 1. **{Opportunity}** Evidence: {What suggests this} Potential impact: {Estimated upside} â ī¸ CONCERNS (Needs Attention) âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ 1. **{Concern}** Data: {Supporting metric} Severity: [High/Medium/Low] Possible causes: {Hypotheses} đ SURPRISES (Unexpected Findings) âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ 1. **{Finding}** Expected: {What we thought would happen} Actual: {What happened} Investigation needed: {Yes/No} âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ # ========================================== # STEP 5: OPTIMIZATION RECOMMENDATIONS # ========================================== IF include_recommendations == True AND analysis_type != "setup": #AI->H::Status: (Generating optimization recommendations) **5.1 Recommendation Framework:** GENERATE recommendations based on insights: FOR each CONCERN: CREATE recommendation = { "issue": what's not working, "recommendation": specific action to take, "expected_impact": what should improve, "effort": Low/Medium/High, "priority": 1-5 (1 = highest) } FOR each OPPORTUNITY: CREATE recommendation = { "opportunity": what could be better, "recommendation": specific action to take, "expected_impact": potential upside, "effort": Low/Medium/High, "priority": 1-5 } FOR each WIN: CREATE recommendation = { "success": what's working, "recommendation": how to double down, "expected_impact": scalability, "effort": Low/Medium/High, "priority": 1-5 } **5.2 Prioritization Matrix:** GENERATE PRIORITY_MATRIX: âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ â OPTIMIZATION PRIORITY MATRIX â ââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ⤠â IMPACT â â â LOW â HIGH â â ââââââââââââŧâââââââââââââââââŧâââââââââââââââââ â â E LOW â Nice to have â đ¯ QUICK WINS â â F â (do if time) â (do first) â â F âââââââââŧâââââââââââââââââŧâââââââââââââââââ â â O HIGH â Reconsider â Strategic â â R â (maybe skip) â (plan & execute) â â T â â â âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ **5.3 Recommendations Output:** GENERATE RECOMMENDATIONS_REPORT: âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ OPTIMIZATION RECOMMENDATIONS âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ đ¯ QUICK WINS (High Impact, Low Effort) - DO THIS WEEK âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ 1. **{Recommendation}** Issue/Opportunity: {context} Action: {specific steps} Expected Result: {outcome} Time Required: {estimate} 2. **{Recommendation}** ... đ STRATEGIC INITIATIVES (High Impact, High Effort) - PLAN FOR NEXT PHASE âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ 1. **{Recommendation}** Issue/Opportunity: {context} Action: {specific steps} Expected Result: {outcome} Resources Needed: {requirements} Timeline: {suggested timeframe} đĄ EXPERIMENTS TO TRY âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ 1. **{Experiment}** Hypothesis: {what we think will happen} Test: {how to test it} Success Metric: {how we'll know if it worked} Duration: {test length} đĢ STOP DOING âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ âĸ {Tactic that isn't working and should be stopped} âĸ {Content type that underperforms consistently} âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ # ========================================== # STEP 6: REPORTING OUTPUT # ========================================== #AI->H::Status: (Generating final report output) **6.1 Report Generation by Type:** IF analysis_type == "setup": COMPILE setup_output: - Metrics Dashboard Template - Data Collection Guide - Target Framework - Tracking Checklist IF analysis_type == "weekly-review": COMPILE weekly_report: - Performance Summary - Key Metrics Update - Top/Bottom Performers - Quick Insights - Immediate Actions IF analysis_type == "phase-review": COMPILE phase_report: - Comprehensive Performance Summary - All Metrics Analysis - Detailed Insights Report - Recommendations Report - Next Phase Adjustments IF analysis_type == "final": COMPILE final_report: - Full Campaign Performance Summary - Goal Achievement Analysis - Complete Insights Report - Key Learnings Document - Future Campaign Recommendations - Pre-Beta to Beta Transition Insights **6.2 Final Output Block:** âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ CAMPAIGN_PERFORMANCE_BLOCK - {analysis_type} Generated: {current_date} Source Recipe: RCP-004-002-009-PERF-ANALYZER-v1.00a Guided by: Maggie Stratton - Marketing Maven âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ ANALYSIS METADATA âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ âĸ Analysis Type: {analysis_type} âĸ Period Analyzed: {review_period} âĸ Campaign: {campaign_name} âĸ Generated: {current_date} {INSERT APPROPRIATE SECTIONS BASED ON analysis_type} âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ USAGE INSTRUCTIONS: âĸ Setup output: Use dashboard template weekly, follow data collection guide âĸ Weekly review: Share with stakeholders, implement quick wins immediately âĸ Phase review: Use for strategy adjustments, inform next phase planning âĸ Final review: Archive as campaign learnings, apply to future campaigns âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ **6.3 Quick Reference Card:** âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ â đ PERFORMANCE ANALYSIS QUICK REFERENCE â ââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ⤠â đ ANALYSIS TYPE: {analysis_type} â â đ
PERIOD: {review_period} â â đ¯ OVERALL STATUS: {đĸđĄđ´} â ââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ⤠â KEY NUMBERS: â â âĸ Primary Goal Progress: {X}% â â âĸ Top Performing Platform: {platform} â â âĸ Best Content Pillar: {pillar} â â âĸ Biggest Opportunity: {opportunity} â ââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ⤠â IMMEDIATE ACTIONS: â â 1. {action_1} â â 2. {action_2} â â 3. {action_3} â âââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââââ #AI->H::Deliverable: (Performance analysis complete) **Maggie's Closing Summary:** IF analysis_type == "setup": "Your measurement framework is ready. **You now have:** âĸ Dashboard template to track all KPIs âĸ Data collection guide for consistent measurement âĸ Target framework for goal setting **Next Step:** Fill in your baseline metrics before campaign launch, then run weekly-review each week." IF analysis_type == "weekly-review": "Weekly analysis complete for {review_period}. **Quick Summary:** âĸ Overall: {status} âĸ Top Win: {win} âĸ Top Concern: {concern} âĸ Immediate Action: {action} **Next Step:** Implement quick wins this week, prepare for next weekly review." IF analysis_type == "phase-review": "Phase analysis complete for {review_period}. **Phase Summary:** âĸ Goal Progress: {percentage}% âĸ Key Learning: {learning} âĸ Major Adjustment: {adjustment} **Next Step:** Apply insights to next phase planning, update strategy as needed." IF analysis_type == "final": "Full campaign analysis complete. **Campaign Summary:** âĸ Overall Success: {assessment} âĸ Goals Achieved: {count}/{total} âĸ Biggest Win: {win} âĸ Key Learning: {learning} **Next Step:** Archive these learnings, apply to Beta phase planning." #AI->H::RecipeComplete: (RCP-004-002-009-PERF-ANALYZER-v1.00a executed successfully) #AI->H::OutputReady: (CAMPAIGN_PERFORMANCE_BLOCK available) """, # ========================================================= # OUTPUT SPECIFICATIONS # ========================================================= outputs={ "setup_outputs": { "METRICS_DASHBOARD_TEMPLATE": "Blank template for tracking", "DATA_COLLECTION_GUIDE": "Where and how to gather data", "TARGET_FRAMEWORK": "Goal-setting structure", "available_when": "analysis_type == 'setup'" }, "review_outputs": { "PERFORMANCE_SUMMARY": "Metrics overview with status", "INSIGHTS_REPORT": "Pattern analysis and findings", "RECOMMENDATIONS_REPORT": "Prioritized action items", "available_when": "analysis_type in ['weekly-review', 'phase-review', 'final']" }, "final_outputs": { "CAMPAIGN_LEARNINGS": "Key takeaways for future", "TRANSITION_INSIGHTS": "Pre-Beta to Beta recommendations", "available_when": "analysis_type == 'final'" }, "reference_outputs": { "QUICK_REFERENCE_CARD": "At-a-glance summary" } }, # ========================================================= # INTEGRATION NOTES # ========================================================= integration_notes=""" RECEIVES FROM: âĸ Recipe 8 (Campaign Architecture): Goals, phases, milestones âĸ Recipe 13 (Content Calendar): Content-to-performance mapping âĸ Platform Analytics: Actual performance data âĸ Previous analyses: Comparison baselines FEEDS INTO: âĸ Campaign strategy adjustments âĸ Content calendar optimizations âĸ Resource reallocation decisions âĸ Future campaign planning USAGE PATTERN: 1. Run SETUP at campaign start 2. Run WEEKLY-REVIEW every week (recommend Monday) 3. Run PHASE-REVIEW at each phase transition 4. Run FINAL at campaign end DATA REQUIREMENTS: âĸ Setup: No data needed âĸ Weekly: Basic platform metrics âĸ Phase: Comprehensive metrics + comparison âĸ Final: Full campaign data """, # ========================================================= # VALIDATION CHECKLIST # ========================================================= validation_checklist=""" SETUP MODE: ⥠All KPIs defined with clear metrics ⥠Data sources identified for each metric ⥠Targets are SMART (Specific, Measurable, Achievable, Relevant, Time-bound) ⥠Dashboard template covers all metric categories ⥠Collection schedule is realistic REVIEW MODES: ⥠All required data provided ⥠Calculations verified ⥠Trends correctly identified ⥠Insights are actionable ⥠Recommendations are prioritized ⥠Quick wins identified """)# =========================================================# RECIPE: END: CAMPAIGN-PERFORMANCE-ANALYZER# =========================================================# =========================================================# USAGE EXAMPLES# ========================================================="""EXAMPLE 1: Initial Setup#H->AI::Directive: (Execute Recipe 16 - Campaign Performance Analyzer)Parameters: campaign_architecture: [CAMPAIGN_ARCHITECTURE_BLOCK] success_metrics: [ "Beta signups", "Total social followers", "Average engagement rate", "Website traffic", "Email subscribers", "Founding Chef applications" ] analysis_type: "setup" include_recommendations: falseEXAMPLE 2: Weekly Review#H->AI::Directive: (Run weekly performance review)Parameters: campaign_architecture: [CAMPAIGN_ARCHITECTURE_BLOCK] success_metrics: [Beta signups, followers, engagement, traffic] analysis_type: "weekly-review" review_period: "Week 3 (Dec 16-22, 2025)" performance_data: { "beta_signups_week": 12, "beta_signups_total": 47, "x_followers": 1250, "linkedin_followers": 890, "avg_engagement_rate": 3.2, "website_visitors": 2100, "blog_views": 850 } comparison_baseline: { "beta_signups_week": 8, "x_followers": 1100, "avg_engagement_rate": 2.8 } include_recommendations: trueEXAMPLE 3: Phase Review#H->AI::Directive: (Run Phase 1 performance review)Parameters: campaign_architecture: [CAMPAIGN_ARCHITECTURE_BLOCK] success_metrics: [all KPIs] analysis_type: "phase-review" review_period: "Phase 1: Pre-Beta Awareness (Dec 1 - Jan 15)" performance_data: {comprehensive metrics} comparison_baseline: {pre-campaign baseline} content_calendar: [CONTENT_CALENDAR_BLOCK for correlation] include_recommendations: trueEXAMPLE 4: Final Campaign Review#H->AI::Directive: (Run final campaign analysis)Parameters: campaign_architecture: [CAMPAIGN_ARCHITECTURE_BLOCK] success_metrics: [all KPIs] analysis_type: "final" review_period: "Full Campaign (Dec 2025 - May 2026)" performance_data: {complete campaign metrics} comparison_baseline: {pre-campaign baseline} include_recommendations: true"""# =========================================================# VERSION HISTORY# ========================================================="""VERSION HISTORY:v1.00a (2025-11-25) - Initial release - 6-step workflow (Mode Selection through Reporting Output) - Maggie Stratton persona integration - Four analysis modes (setup, weekly-review, phase-review, final) - Comprehensive metrics framework - Dashboard template generation - Insight extraction engine - Prioritized recommendations - Platform-specific data collection guidance"""# =========================================================# END RECIPE-ID: RCP-004-002-016# =========================================================