A/B Testing Best Practices

Every AdScail campaign includes an A/B testing framework. Here's how to use it to systematically improve your results.

What AdScail Generates

Your testing section includes:

• Test hypotheses: What we think will work and why
• Variant suggestions: Specific A vs B recommendations
• Success metrics: What to measure and target benchmarks
• Test priority: Which tests to run first for maximum impact

Setting Up Tests

1. Pick one variable: Don't test headline AND image together
2. Create variants: Use AdScail's suggestions or create your own
3. Set up in platform: Use native A/B testing or create duplicate ad sets
4. Allocate budget: Split evenly between variants
5. Wait for significance: Don't call winners too early

Testing Hierarchy

Test things in order of impact:

1. Offer/Angle: What you're selling and how you position it
2. Hook: First 3 seconds of video or headline
3. Creative format: Video vs image vs carousel
4. Body copy: Long vs short, different messaging
5. CTA: Different calls-to-action

Reading Results

Key metrics to compare:

• CTR: Which variant gets more clicks?
• CPC: Which costs less per click?
• Conversion rate: Which turns more clicks into customers?
• CPA/ROAS: Which is more profitable?

Important: High CTR doesn't always mean better results. A variant with lower CTR but higher conversion rate might be more profitable.

When to Call a Winner

• At least 1,000 impressions per variant
• At least 100 conversions total (ideally 50+ per variant)
• 95% statistical significance (use a calculator)
• Difference is meaningful (10%+ improvement, not 2%)

After the Test

1. Document learnings: What worked? What didn't? Why?
2. Scale the winner: Increase budget on winning variant
3. Plan next test: Use learnings to inform your next hypothesis
4. Update brand profile: If you learned something about your audience, save it