All examples for Confidence Interval Calculator & Interpreter

Email Campaign Open Rate Analysis

Calculating a 95% confidence interval for email campaign open rate using Wilson score method. Demonstrates proportion CI with clear business interpretation comparing to industry benchmarks and actionable recommendations for optimization.

Input

What you provide to the skill

Our email campaign had 847 opens out of 3200 sent. Calculate a 95% CI for the true open rate.

Output

What the skill generates for you

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EMAIL CAMPAIGN OPEN RATE ANALYSIS
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Sample Data:
  Emails sent: 3,200
  Opens: 847
  Sample open rate: 26.5%

Confidence Interval (Wilson Score Method):
  95% CI: (25.0%, 28.0%)
  Margin of error: ±1.5%
  Standard error: 0.0078

Visualization saved: email_open_rate_ci.png

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INTERPRETATION
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Based on 847 opens from 3,200 emails sent, your campaign achieved a
26.5% open rate.

CONFIDENCE INTERVAL:
We are 95% confident that the true open rate for this campaign (if sent
to the entire population) falls between 25.0% and 28.0%.

WHAT THIS MEANS:
• If you repeated this campaign 100 times, approximately 95 of those
  confidence intervals would contain the true open rate
• The margin of error is ±1.5%, indicating good precision with
  this sample size
• Your open rate is substantially above the industry average (~20%)

PRACTICAL IMPLICATIONS:
• Your campaign is performing 1.3x better than typical email
  marketing benchmarks
• Even the conservative lower bound (25.0%) exceeds industry
  standards by 25%
• This level of engagement suggests strong subject lines, audience
  targeting, and/or email deliverability

BUSINESS RECOMMENDATIONS:
1. REPLICATE SUCCESS: Analyze what made this campaign effective
   - Subject line approach
   - Send time and day
   - Audience segmentation
   - Email design/content

2. SCALE WITH CONFIDENCE: Your sample size (3,200) provides reliable
   estimates. You can confidently apply these learnings to larger sends.

3. OPTIMIZE FURTHER: While performance is strong, there's still room
   to improve toward the upper bound (28.0%). Consider:
   - A/B testing subject lines
   - Personalization experiments
   - Send time optimization

4. MONITOR TRENDS: Track whether future campaigns maintain this
   performance level. Regression toward the mean is possible.

5. MOVE TO CLICK-THROUGH: With strong open rates, focus optimization
   efforts on click-through rates and conversions to maximize ROI.

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