A/B Testing

What does A/B testing mean?

A/B testing, also known as split testing, is a user testing method where two versions of a webpage, app or digital content are compared to see which results in better customer experiences. To run an A/B test, you split your users into two groups, with one experiencing the original (control) version and the other the modified (variant) version. By measuring specific outcomes such as click-through rates, conversions, customer satisfaction and engagement, businesses can identify which version resonates more with users. 

Here’s how A/B testing benefits businesses: 

• It increases conversion rates by pinpointing which changes encourage actions like purchases or sign-ups. 
• The process supports data-driven decisions, eliminating guesswork through reliable data analysis. 
• It reduces bounce rates by improving content, making users stay longer on-page or in conversation. 
• A/B testing maximizes ROI by putting resources into the most effective strategies. 

Now that you understand the definition of A/B testing, let’s jump into how & when to use A/B testing. 

How does A/B testing work? 

An ideal A/B test would work through the following steps. 

1. Collect data on high-traffic areas or pages with high bounce rates using customer journey analytics. Supplement with heatmaps, social media insights and surveys. 
2. Define clear conversion goals, such as button clicks, link clicks or product purchases. 
3. Create and prioritize test hypotheses based on their potential impact and implementation difficulty. 
4. Create different versions of your content, like reordering elements or altering customer service workflows.
5. Launch the test, randomly assigning visitors to either the control or variant and measuring their interactions to compare performance.