A/B tests are a great way to test marketing hypotheses and increase sales. But not everyone knows how to use this tool correctly. Let’s figure out what A/B tests are and what business tasks they can help solve.
What is A/B testing?
A/B testing is a research method for assessing the effectiveness of two versions of one element. In marketing, this could be a button on a website page, a newsletter, headlines, or any other details. The idea is to show them to two audience segments over a certain period of time. Comparison of 3 or more elements is already a split test.
Let’s say you have an online store. The “buy” button is highlight in r, but you think it’s more of a deterrent than a sales pitch. How do you know if changing the button color will actually impact conversion and sales?
Here’s how: divide the audience into control and test groups, create two different pages and test them empirically. Users from each group will interact with different versions of the site. As a result, the conversion rate for one of the buttons will be higher – the study was successful and you can make changes to the site.
50% of users will see version 1 of the site, and another 50% will see version 2.
Why can’t you just change the button color to anything else?
Yes, you can. But then you won’t be able to determine how this change affect the funnel optimization. For example, you don’t like the green color, so you decide to change the green banner on your site to blue. The next month, sales increas by 5%, but there is no guarantee that the banner color affect this. Perhaps contextual advertising work so well or the seasonal factor play a role. And with A/B testing, you will get an accurate result.
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Why do you ne to conduct an A/B test?
Marketing is a process of constant improvement. You can’t just create a website/newsletter/advertisement once and think that they will bring in applications. Customers are becoming more and more picky every year, and competitors are not asleep, so it is necessary to constantly build hypotheses and test them to improve the user experience. And here, as according to Darwin, it is not the strongest who will survive, but the one who adapts better.
Here are some examples of what you can improve with A/B testing
Improve metrics
Outdat design and uninteresting content are the main reasons for bounce rates and low click-through rates. Such problems can be avoid by constantly testing elements and choosing the best solutions for each problem. Metrics are most important for marketers.
Bounce rate is the percentage of users who leave a site almost immiately (usually within 15 seconds) without performing any target actions or clicks.
Click-through rate, or CTR, is a key metric in marketing, the ratio of clicks to impressions
Improve usability
Usability is the ease of use of a website. Customers should not have to look for a shopping cart or a newsletter subscription form. Useful buttons should be visible, otherwise users will leave without making a purchase. Even if the site is convenient, believe me, there is always something to improve. A/B tests help UX designers optimize the design, make it as convenient and understandable as possible.
Increase conversion with minimal risk
Conversions are equally important how to create remarketing audiences on Facebook ads that work for both marketers and sales managers. Split tests help check how a banner or button affects conversion and test different design options. And all this – with minimal costs and almost no losses, because half of the audience still sees the old version.
There are many successful cases where A/B tests help companies achieve the desir results and increase sales. For example, the American IT company WorkZone increas the number of leads by more than a third , thanks to reviews. The changes were first test on a small group, and then add to the site.
How to Conduct Testing: 5 Steps to Success
A/B tests can become a universal tool, the main thing is to conduct them correctly. Using an example, we will show what rules to follow, how to build hypotheses and analyze the results.
Imagine that you are a marketer for a construction company and you notice that the conversion rate for newsletter subscriptions on your website is only 15%. In your opinion, it can be increas by changing the design of the form. Let’s test it?
Step 1: Define the goal and metrics
Conducting an A/B test should begin with defining the goal and metrics. Otherwise, it will be difficult to evaluate the results. Metrics can be any quantitative indicators us in marketing – average check, number of orders, click-through rate.
Let’s explain with an example. You analyz phone number my the sales funnel in the company and notic that only 3% of those who saw the email newsletter subscription form fill it out. You ne to “increase the conversion to newsletter subscription by 15%” – this will be the goal. And CR, or conversion, will help measure whether the goal has been achiev.
Step 2. Formulate a hypothesis
Hypothesis is also the basis of A/B testing. It should contain an assumption, a metric, and an end result: “If we […], then […]”. There are two types of hypotheses:
zero – the changes will not bring the expect results;
alternative – changes will help achieve the goal.
Let’s go back to the example. In our case, the alternative hypothesis might be: “If we offer a 10% discount on any purchase for subscribing to the newsletter, conversion will increase by at least 15%.” The numbers are not important, you can do without them in the hypothesis, because you will never be able to accurately calculate the benefit of any changes before the experiment. The null hypothesis would be: “If we offer a 10% discount on any purchase for subscribing to the newsletter, this will not affect conversion in any way.
