In the world of eCommerce, A/B testing and experimentation can bring in some of the most important competitive advantages. A/B testing or split testing is the process of comparing two versions of the same webpage against each other, to determine which one performs better.
Controlled experimentation allows the marketers to iterate and research fast, leading to a data-informed decision. It is one of the most widely employed techniques for augmenting the performance of websites, mobile applications, emails, and much more. If implemented correctly, it can set the foundation for a data-driven marketing strategy, boost conversions, increase sales, improve overall customer acquisition and lead generation results.
In this blog, we are going to deep-dive into some key tactics that can help you create a more effective experimentation strategy.
In A/B testing procedure, you should start by deciding what it is you want to test and your objective behind running the test. Then, you need to create two different versions of the selected element or control group. Next, you will show these versions to two similarly sized audience groups and examine which one performed better over a period of time.
Some of the best elements to run A/B testing are: Headlines, CTAs, Pop-ups, images, audio, videos, subject lines, product descriptions, social proof, dimensions such as color, size, location, placement, email marketing, landing pages, etc.
You want to find out if changing the size of your subscribe button can increase click-through rates. To A/B test this, you would design an alternate subscribe button of different sizes. Then, you will expose these versions to a predetermined percentage of site visitors, that are equally divided. After the testing period, you can analyze your results by measuring which button size caused more visitors to click.
You want to see if adding social proof to the product detail page will affect the add-to-cart rate. To test this, you will create an alternate version. Version A is the current page, without social proof. Version B is the new page, with social proof. Then, you will expose them to the sample sizes and collect the data. Finally, you will conclude whether adding social proof increased the add-to-cart rate or not.
A/B testing is a very powerful strategy to drive eCommerce growth. When employed correctly using the above-mentioned steps & tactics, it can hugely impact your KPIs. The goals of A/B testing are a major driving force behind the entire process. Some of these goals include:
Let’s get to the technical part now. Following are some tips and tactics to undertake effective A/B testing for your eCommerce website:
During the process of optimization, you may find out that there are several variables that you want to test such as the design, color, size, placement, etc. But for an effective evaluation, you need to isolate a “single variable” and measure its performance. Otherwise, it becomes difficult to determine which variable was responsible for the change in performance.
Even the simplest variables make a big impact, therefore, it is recommended to test one variable at a time. For example, you want to drive newsletter sign-ups on your website. Then your variable will be – the design of the sign-ups.
If the traffic to your website is high, you can also select more variables. But, then you need to create all possible variants of those variables. For instance: with 2 variables, you will need to create and test 4 variants.
A/B testing is always based on a goal. Every brand has different goals. For instance, the goal can be increasing ‘Add to Cart’ actions, or increasing the order value, or decreasing cart abandonment, and so on.
So, your next step should be to identify the problem you want to resolve and decide on a measurable goal. For example, you want to increase the click-through rate of the newsletter sign-ups on your website. This will enable you to send your newsletters out to a larger audience and ultimately improve the lead generation results.
Once the goal is identified, create a suitable hypothesis about what is going to improve your original page and examine your results based on this prediction.
For instance, your hypothesis can be “By testing alternate designs for the sign-ups on the homepage, our brand can discover what resonates best with the audience. We can then deploy that winning variation which will most likely result in more sign-ups.”
Now that you have your variables and your goal defined, use this to set up your “control” and “challenger.” Your unaltered version, or version A, is labeled as ‘control.’ In this case, the current design of the sign-up is your control.
And, your alternate version, or version B, is labeled as ‘challenger.’ So, the new design of your sign-up is your challenger.
For conclusive results, you need to split your audience randomly into equal-sized groups. The size of your audience groups will depend on the element you are testing. For example, if you are A/B testing your emails, then you will probably want to send them to a smaller group to get significant results. However, if you are testing something that doesn’t have a finite audience like newsletter sign-ups, then the test time will affect your sample size.
Some other key points to keep in mind while determining the sample size and time are:
Draw conclusions based on which variable won: the control or the challenger. Once you understand which version your audience liked, you can implement that variation.
For example, if you find that using version B drives more newsletter sign-ups than version A, you might want to consider using that variation on your homepage.
However, if none of the versions is statistically better, you can conclude that the variation doesn’t have a significant impact on the metric you are tracking. In this case, stick with the original version, or you can even run a new test.
All in all, A/B testing and experimentation have a profound impact on not only conversion rates but the entire experience of your website. Constantly conducting A/B testing helps you iterate site changes and provides you a competitive advantage. By employing the above-mentioned techniques strategically, you can increase your topline as well as bottomline significantly.
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