Every business website wants visitors converting from just visitors to customers. The rate at which a website is able to do this is its conversion rate that means Measuring the performance of a variation (A or B). So, A/B testing allows you to make this
How to Conduct A/B Testing
Before the A/B Test
1- Identify your goal
Before you create a test, you need to know what, exactly, you’re hoping to accomplish. Although you’ll measure a number of metrics for every one test, choose a primary metric to focus on before you run the test. determine a target metric you want to achieve with your test. This will be a specific number related to the KPI you’re focusing on.
If your goal is simply to improve your website or increase revenue, you’ll have a tough time figuring out where to start with your changes. And at the end of your test, it will likely be difficult to say for sure whether your test was successful. Instead, be specific about exactly which actions on your site you want to generate.
First, identify your main business objectives. In most cases, this will be increasing product sales, user signups, or client contracts. Next, determine your most important website goals. These are likely closely related to your business objectives.
2- Determine your sample size
How you determine your sample size will also vary depending on your A/B testing tool, as well as the type of A/B test you’re running. If you’re A/B testing an email, you’ll probably want to send an A/B test to a smaller portion of your list to get statistically significant results. Eventually, you’ll pick a winner and send the winning variation on to the rest of the list.
3- Decide how significant your results need to be
Once you’ve picked your goal metric, think about how significant your results need to be to justify choosing one variation over another. Statistical significance is a super important part of A/B testing process that’s often misunderstood.
The higher the percentage of your confidence level, the surer you can be about your results. In most cases, you’ll want a confidence level of 95% minimum — preferably even 98% — especially if it was a time-intensive experiment to set up. However, sometimes it makes sense to use a lower confidence rate if you don’t need the test to be as stringent.
During the A/B Test
4- Use an A/B testing tool
To do an A/B test on your website or in an email, you’ll need to use an A/B testing tool. you can use Google Analytics’ Experiments, which lets you A/B test up to 10 full versions of a single web page and compare their performance using a random sample of users.
5- Design your test
By this point, you’ve set a goal, selected a page, and determined what you want to test. Now, it’s time to create and launch your test. First, you’ll need to develop the “creative” part of the test. This might involve rewriting copy, coming up with new calls to action, or redesigning a graphic.
Next, you’ll need to select the testing platform you want to use. There are many tools available for this, but if you’re new to A/B testing, you’ll want to select one that makes it easy to get your test up and running.
After the A/B Test
6- Focus on your goal metric
Again, although you’ll be measuring multiple metrics, keep your focus on that primary goal metric when you do your analysis.
7- Measure the significance of your results using our A/B testing calculator
Now that you’ve determined which variation performs the best, it’s time to determine whether or not your results statistically significant. In other words, are they enough to justify a change?
To find out, you’ll need to conduct a test of statistical significance. You could do that manually or you could just plug in the results from your experiment to our free A/B testing calculator. For each variation you tested, you’ll be prompted to input the total number of tries, like emails sent or impressions seen. Then, enter the number of goals it completed generally, you’ll look at clicks, but this could also be other types of conversions.