Channel Performance Review AI Prompt
Analytics & ReportingintermediateClaude 3.5 Sonnet or GPT-4o. Claude excels at structured analysis and clear reasoning through complex datasets. GPT-4o offers faster processing for large data sets. Both handle multi-section frameworks well and produce executive-ready output.
When to Use This Prompt
Use this prompt when conducting monthly or quarterly channel performance reviews, preparing reports for leadership, or evaluating whether to increase/decrease spend on specific marketing channels. It's ideal when you have historical data and need structured analysis with recommendations.
The Prompt
You are a marketing analytics expert. Analyze the following channel performance data and provide a comprehensive review with actionable insights.
## Data to Analyze
Channel: [CHANNEL_NAME]
Time Period: [START_DATE] to [END_DATE]
Metrics:
- Total Spend: $[TOTAL_SPEND]
- Impressions: [IMPRESSIONS]
- Clicks: [CLICKS]
- Conversions: [CONVERSIONS]
- Revenue Generated: $[REVENUE]
- Average Cost Per Click: $[CPC]
- Conversion Rate: [CONVERSION_RATE]%
- Return on Ad Spend (ROAS): [ROAS]x
Previous Period Comparison:
- Spend Change: [SPEND_CHANGE]%
- Click Change: [CLICK_CHANGE]%
- Conversion Change: [CONVERSION_CHANGE]%
- Revenue Change: [REVENUE_CHANGE]%
## Analysis Framework
Provide your review in these sections:
1. **Performance Summary**: Overall assessment of channel health (strong/moderate/underperforming) with key metrics highlighted.
2. **Trend Analysis**: Compare current period to previous period. Identify what's improving and what's declining.
3. **Efficiency Metrics**: Evaluate CPC, conversion rate, and ROAS. Benchmark against [INDUSTRY_BENCHMARK] if available.
4. **Key Findings**: List 3-5 most important observations about channel performance.
5. **Recommendations**: Provide 4-6 specific, actionable recommendations to improve performance. Prioritize by impact.
6. **Risk Assessment**: Identify any concerning trends or metrics that need immediate attention.
7. **Next Steps**: Outline specific actions to take in the next [TIME_PERIOD] with success metrics.
Be specific with numbers and percentages. Use clear language suitable for executive stakeholders. Focus on business impact, not just metrics.
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Tips for Best Results
- 1.Paste actual numbers from your analytics platform—the more specific your data, the more actionable the recommendations. Avoid rounding or estimates.
- 2.Include previous period data for comparison; this enables trend analysis and helps identify whether changes are seasonal or strategic.
- 3.Specify your industry benchmark or target ROAS if available; this contextualizes performance and makes recommendations more relevant to your business.
- 4.Ask for recommendations prioritized by impact and timeline; this helps you focus on high-leverage actions rather than implementing everything at once.
Example Output
## Channel Performance Review: Google Ads Search
**Period:** January 1 - January 31, 2024
### Performance Summary
Google Ads Search is performing **strongly** this period. The channel generated $47,250 in revenue on $8,400 spend, delivering a 5.6x ROAS—above your 4.5x target. Click volume increased 18% while maintaining quality, indicating effective bid management and ad relevance.
### Trend Analysis
Compared to December, this channel shows positive momentum: spend increased 12% strategically, clicks grew 18%, and conversions jumped 22%. Revenue increased 28%, significantly outpacing spend growth. This suggests improved ad targeting and keyword performance.
### Efficiency Metrics
Average CPC of $1.12 is down 8% from last month, indicating better auction efficiency. Conversion rate improved to 3.8% (from 3.2%), and ROAS of 5.6x exceeds your 4.5x benchmark by 24%. These metrics suggest the channel is operating at peak efficiency.
### Key Findings
- High-intent keywords in the "enterprise" segment are converting at 6.2%, double the channel average
- Mobile traffic now represents 62% of clicks but only 48% of conversions, indicating a mobile experience issue
- Brand keywords maintain 8.1% conversion rate; non-brand keywords at 2.9%
- Quality Score improved to 8.2 average across active campaigns
### Recommendations
1. **Increase budget by 15-20%** for enterprise keywords—they're underinvested relative to performance
2. **Audit mobile landing pages** to close the conversion gap; test faster load times and simplified forms
3. **Expand non-brand keyword list** using search term analysis; current list is leaving revenue on table
4. **Test audience segmentation** to bid higher on high-value customer segments
5. **Implement automated bid adjustments** for top-performing keywords to capture more volume
### Risk Assessment
No immediate risks identified. Channel is stable and growing. Monitor mobile conversion rate closely—if it drops further, pause mobile spend until issues resolved.
### Next Steps
Implement recommendations 1-3 by February 15. Track mobile conversion rate daily. Target 6.2x ROAS by end of Q1 through keyword expansion and bid optimization.
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