Also known as split testing and bucket testing, A/B testing is the procedure of contrasting two versions of a web page or an app to ascertain their performance levels and decide the optimum one. Once we create two variations of the web page, they can be tested against one another. This results in generation of data which can be collected and utilized for changing the structure of the page. The primary intention is to stimulate visitors into potential customers and eventually, towards becoming buyers.
The process of A/B testing generally begins by creating a second version of an original web-page. The kind of changes made will depend on the nature of products being sold and target audience. The alteration could range from a single sentence to restructuring of the entire site. This is followed by division of the traffic equally to both the versions: half to the original one (called ‘control’) and the remaining half to altered version (called ‘variation’). Responses of visitors to both these pages are recorded and used to measure the effectiveness of the versions. Predictive analytics can be employed to estimate the performance of each version. This would permit to glimpse whether the change would bring negligible, positive or negative impact on your conversion rates.
Traditionally, websites were designed and put out on basis of intuition of the developers. Such an intuition was determined by the general idea about what audience expects and how this could be fulfilled by the product displayed. A/B testing is the next evolutionary leap in the domain of web designing and implementation. By formulation of websites which are optimized for visitor-to-customer conversions, the companies are in control of their estimated sales and demand. Data is the basic unit of A/B testing which tells you the exact ways in which each element of your page is being perceived and the impact it has on the sales and marketing.
The topping to the ground of data-driven changes is that it positively influences the work-space culture where instead of blindly following hunches, data and statistics are used to direct creation of the page. Three departments which are significantly impacted and thus, can extract benefits from A/B testing are: marketing, IT and designing communities.
The general mechanism of A/B testing begins with the gathering of data about the status of your original web page. Find out the places on your page which bring in the least amount of conversions and work on them. While the primary intention might be to drive visitors to become buyers, you need to have secondary goals. These goals should generally take the form: target number of clicks for a button, newsletter subscriptions, visits to a certain page and so on. Once you have determined your goals, you can begin generating A/B testing ideas. Rate each of these ideas depending on the impact they could have and the level of complexity involved in implementing it. Prioritize between these ideas on the basis of the ratings. Use your A/B testing app to create changes in the website or mobile software. Launch the modified version of your page and decide the target timeline to collect data. Use analytics’ tools to determine the performance of each version and decide on the version which is inherent with the capacity to bring about the highest amount of conversion rates.
Here are 10 ways in which you can increase the conversion rate of your visitors into buyers through A/B testing: