SayPro A/B Testing Template

Template Name: SayPro A/B Testing Template
Purpose: This standardized template is designed for documenting A/B testing experiments, including different variables tested, test implementation, and results achieved. It is used in SayPro Monthly January SCMR-5, SayPro Quarterly Classified Performance Optimization Management, and overseen by the SayPro Classified Office under SayPro Marketing Royalty SCMR.

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1. Experiment Overview

• Test Name: [Insert name of the test]
• Date Started: [Insert start date]
• Date Completed: [Insert end date]
• Test Owner: [Name of person or department conducting the test]
• Objective: [Clearly define the goal of the A/B test, e.g., increase conversion rate, improve ad engagement, etc.]

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2. Hypothesis

• Primary Hypothesis: [Explain what you expect to happen, e.g., “Changing the ad headline to a question will increase click-through rate by 10%.”]
• Expected Outcome: [What success looks like, e.g., “If successful, we will roll out this headline format for all classified ads.”]

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3. Test Variants & Setup

• Control (A): [Describe the original version being tested against]
• Variation (B): [Describe the modified version being tested]
• Other Variants (if applicable): [C, D, etc.]
• Test Audience: [Demographic, geographic, or behavioral details of the audience]
• Traffic Split: [Percentage split, e.g., 50/50, 70/30]
• Testing Tool Used: [Google Optimize, Optimizely, VWO, etc.]
• Duration of Test: [Specify the timeframe]

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4. Metrics & KPIs Tracked

• Primary Metric: [What success is measured by, e.g., Conversion Rate, Click-Through Rate, Bounce Rate]
• Secondary Metrics: [Additional insights such as Engagement Time, Cost Per Conversion, Return on Investment]

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5. Results & Analysis

• Outcome Summary: [Describe the key results, e.g., “Variation B increased conversions by 15% compared to Control.”]
• Statistical Significance: [P-value, confidence level, or similar measure]
• Insights: [What was learned, including unexpected findings]

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6. Conclusion & Next Steps

• Winning Variant: [Which version performed better and why]
• Implementation Plan: [If successful, how the change will be rolled out]
• Future Test Recommendations: [Any follow-up tests to refine results]

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This template ensures structured and consistent documentation of A/B testing within SayPro’s marketing operations, improving decision-making and performance optimization.