Smarter A/B Testing: 4 Steps to Meaningful Results
The online business landscape is ultra-dynamic, always shifting, and emerging trends keep marketers on their toes, making them seek ever more optimal ways to boost conversion rates. In recent years, A/B testing has been the thing – to the extent that some came to regard it as a sort of Aladdin’s lamp, something to try out once and immediately get breakthrough insights and spectacular results. In practice, however, nothing works out on its own just because a testing tool yielded some evidence. A random testing method as it is, it does not presuppose that you would do with random changes here or there. Only with the bigger picture in mind can you arrive at meaningful conclusions and get tangible results. Below, we share four tips that will help you implement A/B testing smarter.
1. Employ Visitor Segmentation and Targeting
It is a matter of fact that your business website sections have different goals aimed at various groups of customers. For instance, what works well for regulars will likely be lost on first-time visitors who are merely doing research on a product or service. So single out various audience segments, define what the desired effects are in each case, make variations, and run A/B tests across each group. Target the winning treatments accordingly – this way you will minimize the risk that reaching a particular goal might hinder achieving other website goals.
2. Mind Your Website Traffic
Budding businesses often get poor A/B testing results (either insignificant or invalid) due to one simple reason: their website traffic (or its quality) is low. Hence the sample size necessary to run a proper experiment cannot be reached. In such cases, it is important first to single out the most crucial elements that need treatment (as there’s simply no scope – or real need – for testing everything) and, second, to make the distinction between variations prominent, lest you get the negligible statistical difference. Moreover, if you run a growing business, opt for custom solutions by QA professionals who’ll take into account every factor significant in your particular case, and do not forget about mobile application testing.
3. Remember – Haste Makes Waste
A/B testing software, being merely a tool, calls for proper use. By no means stop the experiment as soon as statistics started showing ‘significant’ results. Most importantly, determine a fixed sample size (e.g. 1000 observations) before you even begin, and take into account only the results that the testing yields as it reaches this threshold. Moreover, keep from surveying halfway test results and acting upon them, as they are premature and misleading. Be patient and thorough; any other approach would give data as accurate as three blind men judging what an elephant is by touching its tail, leg, or ear.
4. Do Not Discount Iteration
Suppose you have tested several sets of alterations yet none of these showed all that exciting conversion boost potential. Should you ditch all these variants because they are ‘useless’? Not really. The improved copy or design elements might be right each on their own, but some other aspects might require a tweak to make the whole deliver a genuinely significant impact. You would be wise to try altering the new treatments some more and keep an eye on when they click together.
A/B testing is certainly a handy tool for evaluating and enhancing the effectiveness of your CRO efforts. You would be ill-advised to rest on your laurels once the tests have shown this or that treatment led to the desired conversion boost. E-commerce is by no means a static domain – so keep an eye on the ball and be ready to come up with new solutions that the environment might call for at any moment.
