In general, A/B testing is the method of comparing two items against each other to determine which drives better results. A lot of businesses perform A/B split testing to test hypotheses so they can make informed decisions with regards to their websites, mobile apps, and emails. The items which can be tested are limitless. You might want to validate which headline or call-to-action results to higher click-through rate, optimize the layout of your landing page, or test which shopping cart flow would lead to a lower abandonment rate.
By running tests on a regular basis and making necessary changes based on your findings, you are able to make effective product improvements. Let is take a look at the steps involved in performing A/B tests.
Formulate a Hypothesis
The first step in A/B testing would be to understand what it is you want to test and generate a general hypothesis about what could possibly occur.
Select a Metric or Variable
Once you have formulated a hypothesis, the next step would be to test it. Choose a metric that will be used to evaluate success. An example of a metric is the percentage of users who click a specific link or respond to a particular call to action. While it is possible to test more than one metric in an A/B test, it is easier to design, test, and evaluate a single metric per test. So, if you have more than one metric you want to test, it is recommended to run several tests, with one metric per test.
Identify Your Control
In an A/B test, the version A is your control to which version B is compared. A is the current state of your webpage. A/B tests must be run at the same time, showing the two versions of the webpage. Doing so prevents any variability caused by seasonal fluctuations, traffic spikes, promotions on your website.
Divide the Users
A/B tests are also called “split tests” because in this process, you will be diverting some of the traffic that would normally visit the control page so they see the variation page which you are testing. The usual split is 50-50 but as long as you gather enough data points to be statistically significant, you can decide to have a different ratio. Note that having too few data points would leave your data unreliable. You might want to review your statistics textbook or online references for more information about testing for statistical significance.
Record the Results and Draw Your Conclusions
Once you have run your A/B test, the next step would be to evaluate the results. Make sure that your experiment was valid by checking if the test showed an improvement and if there was a significant change that justifies the implementation of changes in the product. Then, document your conclusions and double check that your data supports them.
Repeat the Steps Starting from Step 1
Attend a product management training course and you’ll realize that product improvements should be done continuously as the needs of your market changes. So after an A/B test has successfully been run and changes have been made to your product, continue making improvements and testing them before you launch a new product into the market.