What is A/B Testing?
A/B testing is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. In digital marketing, A/B testing of split testing is a process of showing two variants of the same web page to different segments of website visitors at the same time and comparing which variant drives more conversions.
The number of visitors on your website equals the number of opportunities you have to expand your business by acquiring new customers and build relationships by catering to existing ones. And it is your digital sales funnel that decides whether your website gets good traffic and if it converts more visitors.
Brands want visitors to take action (also known as a conversion) on their website, and the rate at which a site can drive this is called its “conversion rate.” The more optimized your funnel, the higher is the conversion rate. And one of the most important ways to optimize your website’s funnel in digital marketing is A/B testing.
Typically in A/B testing, the variant that gives higher conversions is the winning one, and that variant can help you optimize your site for better results. The metrics for conversion are unique to each website. For eCommerce, it may be the sale of the products, while for B2B, it may be the generation of qualified leads.
A/B testing is one of the components of the overarching process of Conversion Rate Optimization (CRO) using which you can gather both qualitative and quantitative user insights and use them to understand your potential customers and to optimize your conversion funnel based on that data.
How Does It Work?
To understand how A/B testing works, imagine you have two different designs for a landing page — and you want to know which one will have a better conversion rate. After you create your landing pages, you assign one landing to one group and you send the other version to the second group. Then you see how each landing page performs in metrics such as traffic, clicks, or conversions.
If one performs better than the other, great! You can start digging into why that is, and it might inform the way you create landing pages in the future. Once you've determined the formula that works for your brand and target audience, you now have an optimised digital marketing campaign and is ready to scale up to reach your goals.
Many people think that you can get away with a single A/B test. In reality, you should be continuously testing so you can optimize your marketing and advertising creative for your audience. - Crazyegg
A/B testing allows individuals, teams, and companies to make careful changes to their user experiences while collecting data on the results. This allows them to construct hypotheses, and to learn better why certain elements of their experiences impact user behaviour. In another way, they can be proven wrong — their opinion about the best experience for a given goal can be proven wrong through an A/B test.
More than just answering a one-off question or settling a disagreement, AB testing can be used consistently to continually improve a given experience, improving a single goal like conversion rate over time.
For instance, a B2B technology company may want to improve their sales lead quality and volume from campaign landing pages. In order to achieve that goal, the team would try A/B testing changes to the headline, visual imagery, form fields, call to action, and overall layout of the page.
Testing one change at a time helps them pinpoint which changes had an effect on their visitors’ behaviour, and which ones did not. Over time, they can combine the effect of multiple winning changes from experiments to demonstrate the measurable improvement of the new experience over the old one.
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