Best practices Ecommerce

Testing your E-commerce

Florencia López Flamengo 05-28-2020 - 15:44

AllBest practicesEcommerce

Currently, the large e-commerce companies that have been successful use specialized marketing strategies to capture the attention of potential clients and users. These e-commerce stores such as Amazon, eBay, Alibaba and recently Wish, have positioned themselves worldwide as people’s favorites, which is why they must keep up with trends.

But you will ask yourself how they know these strategies work, and that’s because before publishing their news in the e-commerce site, they carry out some tests to know what could give them better results and I will talk about this below.


A / B testing

One of these tools is the so-called A / B test; used to show by means of some variables, which version of the e-commerce is located achieves a higher degree of user interactions. Although it is not the only test that we could do, it is one of the most important ones, since by studying the results we can significantly enhance the performance of our e-commerce and multiply our profits.

To perform this test, a specific group of users is exposed to two versions of the same website with changes made; although, at first glance, they are not so easily detected, they will help us to compare the information and analyze the different results.


How to think about A / B testing for your ecommerce

When we are organizing ourselves to carry out this type of test, we must be clear about what we want to test on our website, for e-commerce the ideal is to determine which of the test models gives a higher sales figure. In this way we can compare different designs, images, call to action buttons, forms and many other components of the site.


How to create the test

To create the test the first thing we must be clear about, is the problem that is occurring and why we want to make changes in our ecommerce. For this, we can use different tools to analyze what users do when they use it, through these results we can formulate a hypothesis about the changes we will make and the effects this will bring.

After we have the hypothesis, we can proceed to design the test based on it, keeping in mind the objectives and the time we will be applying it; as well as the number of users we need. Having the above we will have to establish what types of changes we will make and with these changes we can carry out the next actions.

Some of the changes you could make for your ecommerce could be, redesigning the header to make it more appealing to users, creating call-to-action buttons that stand out more, associating the social networks of interest, applying a system to filter the searches made by users, offering various forms of payment and concentrating everything about it on the same page to avoid distraction when buying, in short, the possibilities of making changes are many and will depend on the hypothesis you have previously made.

To carry out the test we can use different tools, some free and some paid, among which we find Google analytics; Free tool easily accessible, but it is recommended to use not only one but several such as Optimizely, Sitespec, AB Tasty and others. 

All this information will also help us to identify what type of test we want to apply to reach the results we hope to obtain and increase the success of our e-commerce. One of the most used is the A / B test, since it is a simple tool and that provides valuable data to complete our stated goals.


Types of A / B testing

A / B testing may vary depending on the type of modifications made on the website; for this reason, we can implement any of these two types of tests, Split testing or multivariate testing

Split testing consists of presenting two different versions of the website, in which the same creative concept is explored in two different ways; using the same basis for design, content such as forms, information, buttons is maintained and objects are arranged differently within the space.

To perform this test, two landing pages must be created with the differences mentioned above; in this way, 50% of traffic from the site will be sent to model A and the rest will be sent to model B, and the results obtained from each will be evaluated.

The multivariate testing, unlike the split, does not use two different landing page models to collect the data to be analyzed; for this, the same design of the site is used as a base since the changes will be made on the page that is currently online. The changes are made only in the different sections and elements that the site contains to determine which of these combinations generate the desired result.


Split testing advantages and disadvantages

Without a doubt we can name as some of the advantages of this type of test, to be able to obtain results with a smaller sample of users; in addition to being associated with Google analytics, we can demonstrate whether or not making significant changes in the general design of our ecommerce site favors us in our sales. However, the results are general and this represents a disadvantage if we want to try something more specific within the site, as well as consuming more time and resources.


Multivariate testing advantages and disadvantages

By being able to evaluate more specific sections of the page, we have much more detailed information to be able to apply analysis metrics and deduce that it is convenient for us to keep, and that it worked better for us without changing; all this without generating major changes at the level of design and programming which is a great advantage. However, as it is so specific, it needs more traffic to obtain results that can be analyzed about all the different combinations that can be used in it.


It does not matter which test model you carry out, as long as you get the results that will make your e-commerce exploit the potential it has.

Lo último sobre
Ecommerce

Encuentra todas las novedades sobre ecommerce y marketing digital para llevar tu negocio al próximo nivel. ¡Recibe nuestro contenido!


Es hora de pasar a
la acción

Empieza a vender más con Inteligencia Artificial en tus anuncios de Google, Facebook e Instagram
SOLICITA UNA DEMOSTRACIÓN!