Have you ever wondered what effect changing the position or wording of a link or button would have on increasing your job board's conversion rates? Are you always thinking about ways to improve the performance of your job board – job views, applications, JBE sign ups? A/B testing is a really great way of getting answers to questions like these and achieving better site performance.

What is A/B testing?

A/B testing, or split testing, is a great way to test changes you want to make to your web pages against the current design to determine which one produces the best results. It’s a way to make decisions about design changes confidently and quickly.

An A version (or the control) is tested against the B version with live traffic to measure the effect each version has on your conversion rates. Traffic is split equally between the designs. The test finishes only when you reach statistical confidence that one variant is consistently achieving better conversion rates than the other version. Once a winner is established then this design can be used immediately, safe in the knowledge that it is the best performer.

Example A/B testing to measure if changing position of sign up will increase conversions

By taking out the guesswork and testing alternative versions of the web page or component you can accurately decipher which will have the best return or conversion rate. By measuring the impact that changes have on metrics such as applications, job views and click throughs you can ensure that the changes will create positive results for your business.

An example of a simple A/B test would be to test button text. You could test an existing ‘Apply’ button against a new button with the text ‘Apply now’ and divide your web traffic equally between the two versions to measure which button produces the highest application rate.

A/B testing can be used to test different content and design elements such as:

  • Web page layout
  • Button and link wording and styling
  • Headlines
  • Email content
  • Pricing and promotions
  • Images

Why and when you should use it?

The aim of A/B testing is to gain insight into your visitor’s behaviour and therefore enable you to make well informed design decisions, rather than decisions based on guesswork, hunches or personal preference.

Every website is different and each has its own unique audience that have different wants and needs from a sites specific design. This means a one size fits all approach does not work, A/B testing helps us understand the different needs of each sites audience, providing us with the opportunity to explore and compare a variety of different options, using a sites own users to provide the answers. Testing in this way eliminates guesswork, teaching that personal preference does not always translate into conversions.

Not only does each site have a unique audience but they also have varying amounts of traffic and usage, comparing niche and generalist job boards is a good example of this. A/B testing is a flexible tool that allows us to test almost a range of sites with differing amounts of users, ensuring that the end result is a page which converts as well as it physically can.

A/B testing can be used at any point in your sites lifetime. It’s a great tool to harness in the early stages of a sites development to ensure layout and design are working to the optimum levels, as well as later on to test whether you can increase your conversion rate with various design changes.

A/B testing is incredibly dynamic, it can measure huge changes such as entire web designs, as well as something as simple as the wording on a button. The smallest changes to a web page can have high statistical significance and possibly have a big impact on conversion rates.

It also produces incredibly valid data due to the testing conditions; users are tested unknowingly in their natural environment. The data produced is therefore an accurate representation of how your site is used, meaning you no longer have to predict your users behaviour. This allows us to challenge conflicting guidelines within the industry with statistical evidence of what works for your sites users.

What can we learn?

A/B testing does not only help us to make well informed decisions about design and content, but it also provides useful data such as conversion rates and total visitors over a period of time. With such a wide range of data we can not only deduce which variant converted better, but we can also measure which days and times converted best. This can provide insight for other strategies such as social media and editorial content placing, ensuring you are posting content at the optimum times.

Some A/B testing tools also provide click heat maps. These maps show where on the page your visitors are clicking, giving you a wider picture of your user’s time on the site, therefore providing you with further statistical evidence to build your design decisions upon. Used wisely the results can build towards a perfectly optimised site, built for premium conversion ability.

Heat maps show where users are clicking on the page

Whilst A/B testing provides us with the tools to ascertain which elements convert best, it does not allow us the depth to find out why these elements convert as they do. It’s fantastic to get quick and statistically reliable results; however it must never replace user testing. Whilst A/B testing provides us with the opportunity to test a bigger range of people in a small amount of time, it provides us with baseline behaviour results only. User testing takes a much smaller test group, but it creates a conversation with the user. It provides us the opportunity to test what’s not on the page, and unveil consumer’s requirements and expectations in an on-going dialogue.

Tips when using A/B testing

  • Have a clear idea of what you want to achieve from the beginning
  • Keep it simple, it’s always best to test for one critical aspect at a time
  • Calculate how long the test will take. Your traffic may not be high enough to produce clear results. Having too many variants may dilute traffic and the test will take longer.
  • Test simultaneously over weeks if necessary to get confident results, allowing for seasonal, time of day and other factors that can skew results
  • Plan well and use it to continuously improve your business

Case Study: Guardian Jobs

We chose to test different variations of the job layout page to see if a change would make a positive change to the conversion rate. Four different layouts were tested over a period of time; the end result saw the winning layout show an 8% increase in job application rates.

The Guardian also decided to use A/B testing to compare the wording on their navigation menu. Five options were tested including ‘sector insight ‘, ‘sector advice ’and ‘industry analysis’. The winning variant ‘insight from your sector’ saw a huge increase with an increase of 224% click-through rate.

“A/B testing is important to The Guardian for making both large and small design decisions. We’ve tested many elements on our job board from the layout of a job detail page to the wording of a button or link and these have translated into really positive changes in terms of conversions. Small changes can often make a big difference."

"A/B testing measures the behaviour of customers in the real-world and enables us to make user-driven decisions, but we always back this up with clear objectives and upfront planning.”

Nigel Bicknell, Director of Business and Product Development, The Guardian

How can Madgex help?

Now that you have read about the benefits of A/B testing, perhaps it’s time to take action and start optimising the effectiveness of your job board and campaigns. You may already have questions or even hunches about things and would like to gain answers. A/B testing may be the perfect way to achieve this.

If you have custom pages then it’s possible to optimise their effectiveness by testing certain elements to see if they have an impact on conversions. Madgex have the tools and procedure in place for setting up A/B tests quickly and cost effectively for our clients.

If you have any questions or you’d just like to talk to someone about A/B testing, Madgex are happy to provide advice and expertise on the subject.

For more information please call +44 (0)1273 775 100

Other articles you may like...