Module 2: Analyze Campaign Data

Turning Data Into Actionable Insights

Data analysis is often time-consuming and complex. Claude Code can help you quickly analyze campaign performance, identify trends, extract insights, and create reports.

What You’ll Learn

Analyzing campaign performance data
Creating executive reports
Identifying optimization opportunities
Multi-channel attribution analysis
Building data-driven recommendations

Campaign Performance Analysis

Analyze Q2 campaign performance data:

I have campaign data in analytics/q2-campaign-data.csv with columns:
- Date, Channel, Campaign, Spend, Impressions, Clicks, Conversions, Revenue

Please analyze and create a report that includes:

OVERALL PERFORMANCE:
- Total spend, conversions, revenue
- Overall ROI and ROAS
- Cost per acquisition
- Conversion rate

BY CHANNEL:
- Performance breakdown by channel
- Best and worst performing channels
- Efficiency metrics (CPA, ROAS by channel)
- Budget allocation recommendations

BY CAMPAIGN:
- Top 5 performing campaigns
- Bottom 5 campaigns (candidates for optimization/pause)
- Win analysis (what worked and why)

TRENDS:
- Week-over-week performance trends
- Day-of-week patterns
- Performance trajectory (improving/declining)

RECOMMENDATIONS:
- Where to increase spend
- What to pause or optimize
- Testing opportunities
- Quick wins

Save analysis as analytics/q2-campaign-analysis-report.md
Include visualizations descriptions (for charts to create)

Content Performance Analysis

Analyze blog content performance:

Review analytics/blog-performance-q2.csv with:
- Post title, Publish date, Views, Avg time on page, Bounce rate,
  Conversions, Traffic sources

Create analysis report:

TOP PERFORMERS:
- Top 10 posts by views
- Top 10 by engagement (time on page)
- Top 10 by conversions
- What they have in common

UNDERPERFORMERS:
- Posts with high bounce rate
- Posts with low engagement
- Posts with no conversions
- Improvement recommendations for each

CONTENT INSIGHTS:
- Best performing topics
- Optimal post length (based on engagement)
- Best publish days/times
- Traffic source analysis

SEO PERFORMANCE:
- Posts ranking on page 1
- Keyword opportunities
- Posts needing optimization

RECOMMENDATIONS:
- Topics to expand on
- Posts to update/refresh
- Content gaps to fill
- Promotion strategies

Save as analytics/blog-performance-analysis.md

Email Campaign Analysis

Analyze email marketing performance:

Data in analytics/email-metrics-q2.csv:
- Campaign, Send date, List, Recipients, Opens, Clicks, Conversions, Unsubscribes

Create comprehensive email analysis:

DELIVERABILITY METRICS:
- Overall delivery rate
- List health indicators
- Unsubscribe rate trends

ENGAGEMENT METRICS:
- Open rates by campaign type
- Click rates by CTA type
- Best performing subject line patterns
- Send time optimization

CONVERSION ANALYSIS:
- Conversion rate by email type
- Revenue attribution
- Funnel effectiveness

SEGMENT PERFORMANCE:
- Performance by list/segment
- Persona-based analysis
- Lifecycle stage effectiveness

A/B TEST RESULTS:
- Subject line tests conclusions
- Content tests findings
- Send time tests results

RECOMMENDATIONS:
- Email template improvements
- Subject line formulas to use
- Optimal send times
- List segmentation strategy
- Re-engagement campaign needs

Save as analytics/email-marketing-analysis.md

Multi-Channel Attribution

Analyze customer journey and attribution:

Data: analytics/conversions-with-touchpoints.csv
Each conversion with: Customer ID, Conversion date, Touchpoints (channel + timestamp)

Perform attribution analysis:

LAST-TOUCH ATTRIBUTION:
- Channel that gets credit for final conversion
- Revenue by last-touch channel

FIRST-TOUCH ATTRIBUTION:
- Channel that started the journey
- Best awareness channels

MULTI-TOUCH ATTRIBUTION:
- Common journey patterns (e.g., Social → Blog → Email → Conversion)
- Average touchpoints to conversion
- Channel role analysis (awareness vs conversion)

ASSIST ANALYSIS:
- Channels that rarely convert but assist
- Channels that convert directly
- Synergy between channels

TIME TO CONVERSION:
- Average days from first touch to conversion
- Shortest and longest paths
- Trends over time

INSIGHTS:
- Most efficient paths to conversion
- Undervalued channels
- Budget reallocation opportunities
- Campaign optimization strategies

Save as analytics/attribution-analysis.md

Competitive Performance Benchmarking

Create competitive performance comparison:

Our data: analytics/our-performance-q2.csv
Industry benchmarks: analytics/industry-benchmarks.csv

Compare our performance to industry averages:

PAID ADVERTISING:
- CTR vs industry average
- CPA vs industry average
- Conversion rate vs benchmark
- Where we excel, where we lag

ORGANIC/SEO:
- Traffic growth vs competitors
- Keyword rankings comparison
- Content performance
- Domain authority trends

SOCIAL MEDIA:
- Engagement rates vs benchmark
- Growth rate comparison
- Content performance vs competitors

EMAIL MARKETING:
- Open rates vs industry
- Click rates vs industry
- List growth vs benchmark

OVERALL:
- Market share trends
- Share of voice
- Competitive positioning

RECOMMENDATIONS:
- Areas to improve to reach industry average
- Strengths to double down on
- Competitive threats to address

Save as analytics/competitive-benchmarking.md

Executive Dashboard & Reporting

Create executive summary report for Q2:

Combine data from all sources to create concise executive report:

# Q2 Marketing Performance - Executive Summary

## Headline Metrics
- Revenue: $XXX (XX% vs target)
- New customers: XXX (XX% vs target)
- ROI: X.XX (XX% vs Q1)
- Customer acquisition cost: $XX (XX% vs Q1)

## Key Wins
1. [Biggest success with data]
2. [Second biggest success]
3. [Third biggest success]

## Key Challenges
1. [Biggest challenge with impact]
2. [Second challenge]
3. [Third challenge]

## Channel Performance Snapshot
[Table with: Channel, Spend, Conversions, CPA, ROAS, vs Q1]

## What We Learned
- Learning 1 and implication
- Learning 2 and implication
- Learning 3 and implication

## Q3 Recommendations
1. [Top priority with expected impact]
2. [Second priority]
3. [Third priority]

## Budget Request
- Proposed Q3 budget: $XXX
- Allocation by channel
- Expected return
- Risk factors

Create in both detailed and 1-page executive versions
Save as analytics/q2-executive-report.md and analytics/q2-executive-summary-1page.md

Predictive Analysis

Create predictive model based on historical data:

Using data from analytics/historical-performance-12months.csv:

TREND ANALYSIS:
- Seasonal patterns identified
- Growth trajectory calculation
- Anomaly detection

PREDICTIVE MODELING:
- Q3 performance forecast
- Expected conversion volume
- Required budget to hit goals
- Confidence intervals

SCENARIO PLANNING:
- Best case (optimistic): XXX conversions
- Base case (realistic): XXX conversions
- Worst case (pessimistic): XXX conversions
- Probability of each scenario

WHAT-IF ANALYSIS:
- If we increase budget by 20%, expect XXX more conversions
- If we improve conversion rate by 10%, achieve XXX revenue
- If we pause underperforming channels, impact is XXX

RECOMMENDATIONS:
- Budget allocation for Q3
- Risk mitigation strategies
- Opportunities to accelerate growth

Save as analytics/q3-forecast-and-planning.md

From Data to Action Framework

When turning data into actionable insights, follow this framework:

Observation: What does the data show?
Insight: Why is this happening?
Implication: What does this mean for us?
Recommendation: What should we do?
Expected Impact: What will change if we do this?
Resources Needed: What’s required to implement?

Exercise: Complete Analysis Package

Create sample campaign data (or use real data)
Perform comprehensive performance analysis
Identify top 3 insights
Develop specific recommendations
Create executive summary (1 page)
Build detailed report (10 pages)

Key Takeaways

Claude can quickly analyze complex marketing data
Good analysis turns observations into actionable insights
Executive reports should be concise with clear recommendations
Multi-channel attribution reveals true marketing impact
Predictive analysis helps with planning and budgeting
Automated reporting saves time and ensures consistency

Data-Driven Marketing: You can now analyze campaign performance, extract insights, and create compelling reports in minutes instead of days. This allows you to make faster, better-informed marketing decisions.

Analyze Campaign Data