A/B testing takes the guesswork out of marketing. Here are 20 tests to run.\n\n## What is A/B Testing?\n\nA/B testing compares two versions (A and B) to see which performs better. You test ONE variable at a time, measure results, and keep the winner.\n\n## Why A/B Testing Matters\n\n- Companies that A/B test see 30-50% conversion improvements\n- 60% of companies say A/B testing is 'highly valuable'\n- Takes guesswork out of marketing decisions\n- Small changes can mean big results\n\n## 20 Things to Test\n\n### Website Tests (8)\n\n#### 1. Headline\n- A: 'AI Real Estate Lead Generation'\n- B: 'Never Lose Another Lead'\n- Metric: Bounce rate, time on page\n- Winner: Usually B (benefit-focused)\n\n#### 2. CTA Button Color\n- A: Blue button 'Get Started'\n- B: Gold button 'Get Started'\n- Metric: Click-through rate\n- Winner: Gold typically converts 20-30% better\n\n#### 3. CTA Button Copy\n- A: 'Submit'\n- B: 'Get My Free Valuation'\n- Metric: Form completion rate\n- Winner: B (action-oriented, specific)\n\n#### 4. Hero Image\n- A: Stock photo of happy family\n- B: Real photo of local home\n- Metric: Scroll depth, bounce rate\n- Winner: B (authentic photos win)\n\n#### 5. Form Length\n- A: 7-field form (name, email, phone, budget, timeline, beds, baths)\n- B: 3-field form (name, email, phone)\n- Metric: Form completion rate\n- Winner: B (fewer fields = higher completion)\n\n#### 6. Social Proof Placement\n- A: Testimonials at bottom of page\n- B: Testimonials near CTA\n- Metric: Conversion rate\n- Winner: B (social proof near CTA builds trust)\n\n#### 7. Page Layout\n- A: Single column\n- B: Two column (content + sidebar)\n- Metric: Time on page, scroll depth\n- Winner: A on mobile, B on desktop\n\n#### 8. Video vs Image\n- A: Static image hero\n- B: Auto-playing video hero\n- Metric: Conversion rate, bounce rate\n- Winner: B (video increases engagement 80%)\n\n### Email Tests (6)\n\n#### 9. Subject Line Length\n- A: '3 new listings in [neighborhood] just hit the market today — see them before they're gone!'\n- B: '3 new listings in [neighborhood]'\n- Metric: Open rate\n- Winner: B (shorter = higher opens)\n\n#### 10. Send Time\n- A: Tuesday 10:00 AM\n- B: Wednesday 2:00 PM\n- Metric: Open rate, click rate\n- Winner: A (mornings typically win)\n\n#### 11. Personalization\n- A: 'Check out these new listings'\n- B: '[Name], check out these new listings'\n- Metric: Open rate, click rate\n- Winner: B (personalization = +26% opens)\n\n#### 12. Plain Text vs HTML\n- A: HTML email with images + design\n- B: Plain text email\n- Metric: Open rate, reply rate\n- Winner: B (plain text gets 15% higher opens)\n\n#### 13. Email Frequency\n- A: Weekly email\n- B: Bi-weekly email\n- Metric: Unsubscribe rate, engagement\n- Winner: Depends on audience (test both)\n\n#### 14. CTA in Email\n- A: 'Click here to see listings'\n- B: 'Reply to this email'\n- Metric: Response rate\n- Winner: B (direct reply = higher intent)\n\n### Ad Tests (6)\n\n#### 15. Facebook Ad Image\n- A: Property photo\n- B: Agent headshot + property\n- Metric: CTR, cost per lead\n- Winner: B (human faces increase CTR 38%)\n\n#### 16. Facebook Ad Copy\n- A: 'Beautiful 3BR/2BA home in [neighborhood]'\n- B: 'Don't buy a house until you see this one'\n- Metric: CTR, cost per lead\n- Winner: B (curiosity beats description)\n\n#### 17. Google Ad Headline\n- A: 'Homes for Sale in [City]'\n- B: '[City] Real Estate Agent — Free Home Search'\n- Metric: CTR, cost per lead\n- Winner: B (free + specific = higher CTR)\n\n#### 18. Landing Page\n- A: Send to homepage\n- B: Send to dedicated landing page\n- Metric: Conversion rate\n- Winner: B (landing pages convert 5-10x better)\n\n#### 19. Ad Targeting\n- A: Broad audience (25-65, all interests)\n- B: Specific audience (35-55, recently moved, first-time buyer)\n- Metric: Cost per lead, lead quality\n- Winner: B (specific = cheaper + better leads)\n\n#### 20. Ad Spend\n- A: $10/day spread across 5 ad sets\n- B: $50/day on best-performing ad set\n- Metric: Cost per lead, total leads\n- Winner: B (concentrate budget on winners)\n\n## How to Run A/B Tests\n\n### Step 1: Pick ONE variable to test\n- Don't test headline + image + CTA at once\n- Test one thing, keep everything else constant\n\n### Step 2: Set sample size\n- Minimum: 1,000 visitors per variation\n- Or: 100 conversions per variation\n- Use calculators like optimizely.com/sample-size-calculator\n\n### Step 3: Run for 2-4 weeks\n- Don't declare winner after 2 days\n- Let data accumulate\n- Run during similar time periods\n\n### Step 4: Analyze results\n- Statistical significance: 95%+ confidence\n- Look at primary metric (conversion rate)\n- Look at secondary metrics (bounce rate, time on page)\n\n### Step 5: Implement winner\n- Keep the winning variation\n- Start next test (always be testing!)\n\n## A/B Testing Tools\n\n### Free Tools\n- Google Optimize (discontinued, but alternatives exist)\n- LeadHunting AI — Built-in A/B testing for landing pages\n- Mailchimp — Free email A/B testing (up to 2,000 contacts)\n\n### Paid Tools\n- Optimizely — $50,000+/year (enterprise)\n- VWO — $200-$1,000+/month\n- Unbounce — $99-$225/month (landing page A/B testing)\n- Convert.com — $99-$2,000+/month\n\n## Common A/B Testing Mistakes\n\n1. Testing too many variables — can't isolate what worked\n2. Not enough traffic — results not statistically significant\n3. Stopping too early — need minimum 2 weeks\n4. Ignoring secondary metrics — CTR went up but conversions went down\n5. Not testing at all — relying on 'gut feeling' instead of data\n\n## Conclusion\n\nA/B testing is the most reliable way to improve conversion rates. Start with the 20 tests above, run each for 2-4 weeks, and keep what works. Small improvements compound: 10% improvement x 10 tests = 2.6x overall improvement.