What is A/B Testing?
A/B testing is a method of website optimisation whereby two different versions of a website or app are tested by participants. The results are then compared and analysed in terms of their performance to decipher which website is most successful in relation to achieving a specific conversion goal, such as increasing lead generation (Armour, 2015). Essentially, A/B Testing removes the element of uncertainty which often lurks during business decisions regarding website renovation, as the results provide a measure of the impact that updates have across specific metrics. As displayed in the infographic below, ‘A’ is usually the current, control version of the page whilst ‘B’ contains the variation for comparison of results.
Why use A/B Testing?
At present, approximately just 52% of online businesses employ testing to improve website conversions. However, when executed correctly, A/B testing can increase conversion rates by up to 300% (Allen, 2015). As such, when considered in combination with the cheap nature of such testing, this is a marketing avenue which should be explored by businesses of all natures to assess the extent of the positive impact that it can have on value creation.
Allen (2015)
Rather than being a one-off test, A/B Testing can be used regularly to assess minor changes to your website in order to achieve a continuum of improvement in customer experiences and Conversion Rate Optimisation (CRO) (Chaffey and Smith, 2012), thus enhancing the appeal of your business to potential clients (Heimes, 2016), as depicted in the infographic below.
Cebeci, 2014.
How to effectively use A/B Testing
In order to ensure that you’re A/B tests are beneficial for your business, there are four imperative steps which will keep you on the path to success. These are buyer persona, goals, hypothesis and document (Baadsgaard, 2016).
Persona – the buyer persona relates to your target demographic; it is essential to have sufficient information on the type of client that you are trying to attract, i.e. age, gender, budget, goals etc.
Goals – prior to testing, it is important to be aware of what you are seeking to achieve or it is unlikely that the results will be beneficial to your business. Once you have clear, specific goals, you will be able to undertake the tests and analyse the metrics which relate to your objective. If you are approaching A/B Testing from a sales perspective (as many are!), try to consider who your ideal customer is, which elements convert a visitor to a paying customer, how the test will help you to achieve your goal, etc.
Hypothesis – Once you’re equipped with your goals and a knowledge of your buyer persona, you are ready to create a hypothesis. Here, you will need to identify points of incongruence between what your business wants, and what your customer wants. Once these points have been identified, incongruences will need to be reduced. Incongruences can be caused by numerous factors, such as your website not evoking the appropriate emotion for the product/service, the call to action not being salient enough, appearing untrustworthy, etc.
Document – Documenting and learning are the most important aspects of A/B Testing; once you have analysed your results, you should be able to see which website alterations were conducive of positive reactions amongst customers and alter your website accordingly. This information can then be used again to focus further and test more changes to achieve the greatest conversion rate.
Potential drawbacks of A/B Testing
Despite the aforementioned benefits that A/B Testing can provide, it can prove to be costly and time consuming when not utilised efficiently.
In order to achieve the best results from A/B testing, it is important to ensure that your website has sufficient visitors for the practice to be worth implementing, as the goal of this method is to increase conversion amongst current website visitors, rather than attracting more visitors to your website. (If you are seeking advice on how to generate more traffic for your webpage, please read the link in ‘further reading’ on SEO).
It is also important to remain conscious of the fact that things change over time. For example, version A may have performed better than version B in 2015, however version B may now be more effective.
Furthermore, A/B testing measures events quantitatively, rather than qualitatively. As such, version B may be deemed to be more successful as it creates more sign-ups or sales, however this does not necessarily mean that it is more valuable than version A, as version B may be attracting the ‘wrong’ type of customer; for example, they may be more willing to sign up for information but less willing to spend money on your website. As well as this, quantitative goals such as improving brand reputation are immeasurable through testing whether or not a customer clicked a particular button or assessing the length of time that they spent on the page.
Summary
Further Reading
http://www.smartinsights.com/search-engine-optimisation-seo/
https://blog.optimizely.com/tag/ab-testing-ideas/
References
Allen, R. (2015). A newbies guide to AB testing [Infographic]. Available: http://www.smartinsights.com/conversion-optimisation/ab-multivariate-testing/newbies-guide-ab-testing-infographic/. Last accessed 24th Apr 2017.
Armour, H. (2015). What is A/B Testing? Available: http://digitalmarketingmagazine.co.uk/articles/what-is-a-b-testing/2597. Last accessed 26th Apr 2017.
Baadsgaard, J. (2016). How to Create a Winning A/B Testing Strategy. Available: https://blog.kissmetrics.com/create-a-winning-ab-testing-strategy/. Last accessed 25th Apr 2017.
Cebeci, U. (2014). The A/B Advantage [Infographic] . Available: https://blog.optimizely.com/2014/01/08/ab-testing-advantage-infographic/. Last accessed 26th Apr 2017.
Chaffey, D. and Smith, P.R., (2012). eMarketing eXcellence: Planning and optimizing your digital marketing. Routledge.
Heimes, S. (2016). Everything you need to know for successful email A/B testing. Available: http://marketingland.com/everything-need-know-email-ab-testing-167692. Last accessed 26th Apr 2017.