How to Improve Your Website Conversion Rate by Using A/B Testing.

(Courtesy of Mil8)

Although there are many ways you can test changes to your website, none of them are as simple and as effective as A/B Testing. It’s important to remember, however, that A/B testing – even with all its positive features – will not always be suitable to use. In fact, the first step in ensuring its success is to determine if it is the right testing method to use for the kind of problem or situation you are dealing with.

What Is A/B Testing Anyway?

It’s important that you have a correct understanding of what A/B testing can and cannot do, and that means understanding its definition thoroughly.

A/B testing involves testing two elements.

The first one is your “control” or the element that currently exists in your website. The second element involves the new change that you want to introduce in your website.

A/B testing must be conducted under the same circumstances.

Say you have a website for kids. Running tests to determine the success rate of Element A from 4:00 p.m. to 8:00 p.m. is a good idea because that’s the time when kids are likely to be home. It would not, however, be a good idea to conduct the same tests for Element B from 9:00 a.m. to 1:00 p.m. because your target market – grade school students – is still likely in school at that time.

The best way to go about this is to test A and B on the same time slot but on different weekdays. You can also do the same on different days of the weekend.

Use the right and best metric tools to determine the results.

You can’t rely on guesswork or your “instincts” to determine how effective A is over B or vice versa. You need quantifiable results, and you can get that from metric or conversion tools. Naturally, which tools you should use would be determined by the type of conversion you are interested in.

The most commonly used conversion rate is sales.

Element A brought in 100 visitors and 10 of those made a purchase. That means Element A has a 10% conversion rate.
Element B brought in 100 visitors but only 5 of those made a purchase. That gives Element B a lower conversion rate at 5%.

Sales conversion rates can also be made more specific or detailed if you don’t just base it on the total number of visits your website received. You can also base it on the number of visits Element A drew in per hour.

There are also other types of conversion rates that may be ideal to use.

Newsletter sign-ups or subscriptions
Leads or getting contact information from prospective clients
Amount of revenue generated by affiliate links
Amount of revenue generated by click ads
Amount of time spent on a particular page

When Is A/B Testing Ideal to Use?

The list below is just an example in which A/B testing has proven to be effective. Other areas not listed here may also benefit from A/B testing, but it ultimately depends on the number of changes you are proposing to introduce. Anything more than one would make multivariate testing more suitable.

Here are other parts of your website that are likely to benefit from this type of test.

Types of buttons used for call to action
Use of online trust and trade association seals and logos
Number of images used
Headlines

The sky’s the limit to what you can discover with A/B testing, but it all boils down to figuring out what’s wrong with your website first.

Lastly, most people mistakenly assume that methods such as A/B testing are only good for evaluating your website and all its components. In reality, you can apply this test as well to marketing methods you may be performing “outside” your website. A good example of this would be your email campaign, and most of its elements may be subject to A/B testing as well.

Want to learn more about A/B testing? You can find more information on the Maxymiser guide to AB testing. You might also be interested in “What’s the Difference Between Quantitative and Qualitative Research?” on the 60 Second Marketer blog.

Ruben Corbo is a freelance writer that writes about technology, gaming, music, and online marketing especially topics about A/B split testing and how to run multivariate tests. Ruben is also an avid gamer and music composer for short films and other visual arts.