While intuition gets a lot of companies and blogs off the ground, expert marketers use data to guide their results. This data can come in many forms, but one of the most common Is to constantly test and iterate key pages across a website, in a process known as A/B testing.
In this post I’ll go over the basics of the testing process, including some of the key elements you should be looking at and tweaking during your tests.
What is A/B Testing?
A/B testing is the process of using different versions of the same page to test which page performs better against a pre-specified objective. This objective could be anything from number of clicks to time on on page to a more serious conversion like an email registration form or a product purchase.
To do this process well, one needs to consider all aspects of the page, including the following elements:
- Page layout
- Affiliate link placement
- Number of affiliate links
- Headers and subheaders
- Page text
How to A/B Test Different Page Elements
Ideally, an accurate A/B testing process is both rigorous and scietnfici. While small companies often ut corners do to budgeting and/or traffic limitations, larger and more sophisticated sites use comprehensive tests to look at virtually ever element on the page.
When A/B testing an element, one important thing to consider is that you can only make accurate determinations and extrapolations about the results of the test if there is only a single element altered during the testing process.
For example, imagine I wanted to A/B test the placement of an affiliate banner in a sales page. While I might also want to try reorganizing the page and adjusting some of the content to match the different placement of the banner, this would ultimately make it harder for me to know confidently whether or not my change produced any significant results.
It is possible that, if I change the page layout as well as the banner placement, that the page layout altered the user’s behavior and not the banner placement. The same is true for any other item changed on the page during the test.
This means that A/B tests are necessarily laborious, since they wind up testing lots of variations in the page. If I have 3 possible banner placements, 4 possible headers, and 2 possible page layouts, it means I have to test 24 pages to get accurate results!
The good news is that there is software out there to help you with this process, and if you have a relatively new site, you’re going to have to restrict the scope of your tests to fit the amount of traffic you’re generating of your site.