A/B Testing Your Campaigns

Master the science of testing to continuously improve your campaign performance.

A/B Testing Fundamentals

What is A/B Testing?

A/B testing (split testing) compares two versions of your ad to determine which performs better. WilDi Maps makes it easy to test every element of your campaigns.

Why Test?

• Improve conversion rates
• Reduce advertising costs
• Understand your audience
• Make data-driven decisions
• Continuous improvement

What to Test

Priority Testing Elements

Level 1 - High Impact

1. Headlines (biggest impact)
2. Offers/Promotions
3. Call-to-Action
4. Targeting Areas

Level 2 - Medium Impact

1. Images/Graphics
2. Ad Timing
3. Colors/Design
4. Ad Frequency

Level 3 - Fine Tuning

1. Font styles
2. Button shapes
3. Border styles
4. Animation effects

Testing Examples

Headline Tests

• Version A: "50% Off Today Only!"
• Version B: "Half Price - Limited Time!"
• Winner: Version A (32% higher CTR)

Offer Tests

• Version A: "$10 Off Your Order"
• Version B: "20% Off Everything"
• Winner: Version B (better for higher tickets)

CTA Tests

• Version A: "Order Now"
• Version B: "Get Yours Today"
• Winner: Version A (more direct)

Setting Up A/B Tests

Step-by-Step Process

1. Define Your Hypothesis

   • "Urgency increases clicks"
   • "Price beats percentage"
   • "Local references convert better"

2. Choose One Variable

   • Never test multiple changes
   • Isolate the impact
   • Clear results

3. Create Variations

   • Keep everything else identical
   • Significant differences
   • Clear distinction

4. Set Success Metrics

   • Click-through rate
   • Conversion rate
   • Cost per acquisition
   • Revenue per impression

5. Determine Sample Size

   • Minimum 1,000 impressions each
   • Statistical significance
   • Confidence level 95%

6. Run Test Duration

   • Minimum 7 days
   • Full week cycle
   • Account for variations

Statistical Significance

Understanding Results

Confidence Levels

• 95% confidence: Industry standard
• 90% confidence: Acceptable for quick tests
• 99% confidence: High-stakes decisions

Sample Size Calculator

Impressions needed = 16 × (conversion rate × (1 - conversion rate)) / (minimum detectable effect)²

Reading Results

• Look for clear winners
• Check confidence levels
• Consider practical significance
• Factor in costs

Advanced Testing Strategies

Multivariate Testing

Test multiple elements simultaneously:

• More complex setup
• Faster learning
• Requires more traffic
• Advanced users only

Sequential Testing

Test improvements on winners:

1. Test headlines
2. Winner becomes control
3. Test offers
4. Winner becomes control
5. Continue optimizing

Seasonal Testing

• Test holiday themes
• Weather-based creative
• Event-specific messaging
• Time-sensitive offers

Testing Best Practices

Do's

• ✅ Test constantly
• ✅ Document results
• ✅ Share learnings
• ✅ Be patient
• ✅ Test big changes
• ✅ Use adequate sample size
• ✅ Run full cycles

Don'ts

• ❌ Test everything at once
• ❌ End tests early
• ❌ Ignore small wins
• ❌ Test insignificant changes
• ❌ Forget seasonality
• ❌ Skip documentation

Jacksonville-Specific Tests

Local vs. Generic

• "Jacksonville's Best Pizza"
• vs. "Award-Winning Pizza"
• Local references win 68% of time

Neighborhood Targeting

• Riverside messaging
• vs. Generic city-wide
• Neighborhood-specific 45% better

Beach Traffic

• "Skip Beach Traffic"
• vs. "Fast Delivery"
• Traffic reference 2x conversion

Testing Calendar

Weekly Tests

• Monday: Launch new test
• Wednesday: Check data
• Friday: Preliminary results
• Monday: Implement winner

Monthly Testing Focus

• Week 1: Headlines
• Week 2: Offers
• Week 3: Creative
• Week 4: Analysis & planning

Quarterly Reviews

• Compile all test results
• Identify patterns
• Update best practices
• Plan next quarter

Common Testing Mistakes

Statistical Errors

• Ending too early
• Small sample sizes
• Ignoring variance
• False positives

Setup Mistakes

• Multiple variables
• Unclear hypothesis
• Wrong metrics
• Poor documentation

Strategic Errors

• Testing tiny changes
• Not testing at all
• Ignoring results
• No follow-through

Tools and Features

WilDi Testing Dashboard

• Automatic split traffic
• Real-time results
• Statistical calculator
• Visual comparisons

Reporting Features

• Test history
• Winner archive
• Learning library
• Export capabilities

Test Result Examples

Restaurant Campaign

• Tested: "Free Appetizer" vs. "$5 Off"
• Winner: "Free Appetizer" (42% higher conversion)
• Learning: Tangible items beat discounts

Auto Service

• Tested: Price vs. Speed
• Winner: "15-Minute Oil Change" beat "$29.99 Oil Change"
• Learning: Convenience over price

Retail Store

• Tested: Single item vs. Category
• Winner: "50% Off All Shoes" beat "50% Off Nike Runners"
• Learning: Broader appeals win

Testing ROI

Typical Improvements

• First test: 10-30% improvement
• After 6 months: 50-100% improvement
• After 1 year: 100-200% improvement
• Compound effect is powerful

Cost of Not Testing

• Missed opportunities
• Wasted budget
• Competitor advantage
• Stagnant performance

Pro Testing Tips

1. Test your assumptions
2. Start with headlines
3. Big changes first
4. Document everything
5. Share results with team
6. Build testing culture
7. Celebrate wins
8. Learn from losses

Remember: Every test teaches you something about your audience. Even "failed" tests provide valuable insights.

Need help setting up your first A/B test? Contact our optimization team at testing@wildimaps.com.