A/B testing, also known as split testing, is a powerful tool for optimizing your website and improving conversions. It allows you to test changes by showing different versions of a page to subsets of your traffic and seeing which version performs better.
Implementing an effective A/B testing strategy takes some planning and effort, but it can yield huge dividends in the form of more leads, sales, and signups. Here are some tips to help you get the most out of your A/B tests:
Focus on One Change at a Time
When setting up an A/B test, resist the urge to test multiple elements on the page at once. Changing too many things makes it hard to determine which variation drove the impact. Instead, isolate a single change like the headline, call-to-action, image, or even page layout. Focusing on one difference allows you to measure its effect accurately.
Test Strategically Based on Data
Look at existing metrics and data to identify problem areas on your site with room for improvement. Maybe your product page has a high bounce rate or your opt-in form's conversion rate is lower than your goal. Use this information to craft an insightful hypothesis and test changes that could boost performance in those weak spots.
Prioritize Changes with High Potential Impact
Not all page elements have the same influence on conversions. You'll get the biggest bang for your buck by testing changes to headlines, value propositions, calls-to-action (CTAs), and key product images. These prominent items have an outsized impact on conversion rates.
Use a Dedicated A/B Testing Tool
Conducting manual A/B tests is tedious and error-prone. Invest in a trusted A/B testing platform like Optimizely, VWO, or Google Optimize. These tools make it simple to set up concurrent variation tests, segment audiences, collect data, identify winners, and launch winning versions live.
Don't Test Too Many Variations
When A/B testing, more options don't necessarily yield better results. Stick to just two or three variations - an original and one or two challengers. Testing too many versions lowers statistical significance and delays learning. Focus on quality, not quantity.
Drive Adequate Test Traffic
To generate statistically significant results, you need adequate sample sizes. Small sample sizes increase the risk of variability and reduce confidence in winner selection. Use power calculators to determine the minimum traffic needed, and run tests until you achieve it.
Give Tests Enough Time to Run
Conversion optimization takes patience. Don't stop tests prematurely or you may misidentify the true winning variation. Most tests require at least two weeks to collect enough data. Run tests for longer periods to be certain winners are valid over time.
Calculate Conversion Rate Lift
When evaluating A/B test results, look beyond absolute metrics to measure conversion rate lift. If Version B gets 5 more conversions but 10% more traffic, it actually performed worse per visitor. Calculate lift percentages to accurately assess impact.
Test and Iterate in a Continuous Loop
A/B testing is an ongoing process, not a one-time event. Once you complete a test series, take learnings into future tests. Continuously refine page elements through multiple iterative cycles to compound conversion gains.
Personalize Based on User Segments
Not all visitors interact with your site the same way. Tailor test variations to target personas and high-value segments. Test customized messaging for return visitors versus new visitors, or promotional offers for past purchasers.
Check Mobile and Desktop Performance
Optimizing for desktop can diminish mobile experiences, and vice versa. Evaluate A/B tests separately for mobile and desktop to ensure changes don't deliver mixed results across devices. Mobile optimization is especially critical.
Test Across Different Campaigns and Channels
Results for one campaign don't necessarily apply everywhere. Verify that winning variations maintain their edge when run across different channels, ad groups, email lists, etc. Create variations tailored to each source when appropriate.
Leverage Multivariate Testing
Multivariate testing combines multiple page elements into a single experiment. Test headline copy, image size, CTA text, and button color simultaneously to identify the optimal combination of factors.
Let the Data Be Your Guide
When it comes to picking winners, resist hand-picking favorites and let the data decide. Don't ignore or override statistically significant results in favor of variations you simply prefer. Trust the numbers.
Avoid Common Statistical Mistakes
Beware of common pitfalls like testing too early, low power tests, attribution errors, and incorrect lift calculations. Work with analysts or use advanced tools to avoid misinterpreting results.
Don't Trust Results Blindly
While the data doesn't lie, it doesn't reveal the whole story either. Dig deeper into surprising test outcomes to understand user behavior. Significant variances from expected results warrant further qualitative research.
Implement Winners Fully
Once you identify an A/B test winner, roll it out across the full site permanently. Limiting winning versions to small sections limits potential gains. Capitalize on proven improvements with a complete implementation.
By focusing your A/B testing efforts, running iterative cycles, targeting high-impact page elements, and letting data guide decisions, you can unlock major conversion rate optimization wins. Consistent testing and refinement using these tips will add up to tangible boosts in bottom line business metrics over time. Consider using heat mapping software to further optimize your site's UX.