Campaign Reports
- Wingify Campaign Reports: Statistical Models and Inference Levels
- Level 0: Gathering Reliable Data for Website Optimization
- Level 1: Analyzing Average and Normal Distributions
- Level 2: Interpreting Expected Improvement in Web Experimentation
- Level 3: Calculating the Probability of Improvement
- Navigate the Campaign Reports Dashboard
- Navigate and Customize Your Campaign Report
- Document Campaign Learnings in Wingify
- Understanding Sample Size Calculations
- Avoiding Misinterpretations in Data Analysis (Simpson's Paradox)
- Assessing the Maximum Duration of Your Campaign
- What is the Region of Practical Equivalence (ROPE)
- Ensuring Data Collection in Your Experiments
- Understanding Guardrails in A/B Testing
- Avoiding Faulty Experiment Conduct
- Understanding Minimum Test Duration
- Understanding Bonferroni Correction
- Understanding Sequential Testing Correction
- Estimating the Visitor Volume for Your Experiment
- Identify Real Uplifts in Your Test Using Statistical Power
- Understanding False Positive Rate (FPR)
- Understanding Minimum Detectable Effect (MDE)
- Understand Warnings, Recommendations, and Error Messages in Campaign Reports
- Leverage Enhanced Graphs to Analyze Your Campaign Report
- Estimate Your Campaign Duration
- Achieve Accurate Campaign Results with SmartStats Configuration
- Keep Your Campaigns Healthy With Experiment Vitals
- Monitor Your Experiment Using the Campaign Progress Indicator
- Understand Campaign Performance Through Integrated Heatmaps
- Understand Campaign Performance Through Integrated Session Recordings