Campaign Post-Mortem Analysis
Analytics & ReportingintermediateClaude 3.5 Sonnet or GPT-4o. Claude excels at structured analysis and connecting data points logically. GPT-4o handles large datasets and produces well-organized reports. Both maintain context across detailed metrics without losing analytical rigor.
When to Use This Prompt
Run this analysis within 1-2 weeks after a campaign concludes while data is fresh and team memory is intact. Use it to document lessons learned, justify budget decisions to leadership, and create a knowledge base for future campaign planning. Essential for quarterly marketing reviews and annual strategy refinement.
The Prompt
You are a marketing analytics expert conducting a comprehensive post-mortem analysis of a completed campaign. Analyze the following campaign data and provide actionable insights.
## Campaign Overview
- Campaign Name: [CAMPAIGN NAME]
- Duration: [START DATE] to [END DATE]
- Primary Objective: [OBJECTIVE - e.g., lead generation, brand awareness, sales]
- Target Audience: [AUDIENCE DESCRIPTION]
- Budget: $[TOTAL BUDGET]
- Channels Used: [LIST CHANNELS - e.g., email, paid social, content, organic]
## Performance Metrics
- Total Impressions: [NUMBER]
- Total Clicks: [NUMBER]
- Click-Through Rate: [PERCENTAGE]%
- Conversions: [NUMBER]
- Conversion Rate: [PERCENTAGE]%
- Cost Per Acquisition: [DOLLAR AMOUNT]
- Return on Ad Spend: [RATIO]
- Engagement Rate: [PERCENTAGE]%
## Channel Breakdown
[PROVIDE PERFORMANCE BY CHANNEL - impressions, clicks, conversions, cost]
## What Worked Well
[LIST 2-3 ELEMENTS THAT EXCEEDED EXPECTATIONS]
## What Underperformed
[LIST 2-3 ELEMENTS THAT MISSED TARGETS]
## External Factors
[NOTE ANY MARKET CONDITIONS, COMPETITIVE ACTIVITY, OR TIMING ISSUES]
Provide a structured post-mortem that includes:
1. Executive Summary (key wins and misses)
2. Channel Performance Analysis (what drove results)
3. Audience Insights (who converted best, engagement patterns)
4. Root Cause Analysis (why underperforming elements failed)
5. Top 5 Actionable Recommendations (specific, implementable next steps)
6. Budget Reallocation Suggestions (where to invest more/less)
7. Testing Opportunities (what to A/B test in future campaigns)
Be specific and data-driven. Avoid generic observations. Focus on insights that inform future strategy.
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Tips for Best Results
- 1.Include actual numbers and percentages in your metrics section—avoid placeholders. AI produces more accurate analysis with real data than with generic examples.
- 2.Specify what 'success' looked like for your campaign (target CPA, ROAS, conversion rate). This helps AI identify true wins vs. misses rather than making assumptions.
- 3.Add context about competitive landscape or market conditions. AI can then distinguish between campaign execution issues and external factors beyond your control.
- 4.Request specific output format (bullet points, tables, narrative) and include any internal terminology or KPI definitions your team uses for consistency.
Example Output
## Executive Summary
The Q3 Product Launch campaign generated 12,400 conversions at a $18 CPA, exceeding the $22 target by 18%. However, overall ROAS of 3.2x fell short of the 4.0x goal due to underperforming display channels.
## Channel Performance Analysis
Paid Search dominated with 58% of conversions at $12 CPA and 5.8x ROAS. Email marketing was the second-best performer (22% of conversions, $16 CPA). Programmatic display underperformed significantly, generating only 8% of conversions at $31 CPA despite 40% of budget allocation.
## Audience Insights
Users aged 35-54 converted at 3.2x the rate of younger audiences. Mid-market companies (100-500 employees) showed 45% higher lifetime value than enterprise accounts. Geographic data revealed unexpected strength in secondary markets (Austin, Denver, Portland) suggesting untapped expansion opportunities.
## Root Cause Analysis
Display underperformance stemmed from: (1) creative fatigue after week 3, (2) audience overlap with paid search creating inefficient frequency, (3) landing page mismatch for display traffic. Email success was driven by segmentation strategy and personalized subject lines achieving 34% open rate.
## Top 5 Recommendations
1. Reallocate 20% of display budget to paid search expansion
2. Implement weekly creative rotation for display to combat fatigue
3. Develop secondary market-specific landing pages
4. Expand email segmentation to 8+ audience tiers
5. Test lookalike audiences from high-LTV customer segments
## Budget Reallocation
Increase paid search by $15K, reduce display by $12K, add $8K to email list expansion.
## Testing Opportunities
A/B test landing page layouts, subject line formats, and audience exclusion strategies in next campaign.
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