In the e-commerce world, customer satisfaction is the ultimate priority. As per the report of Statista, 44.5% of online businesses believe that the customer experience is a major differentiator or a deciding factor. But creating a flawless user experience is not an easy task and it goes through multiple stages. One such important stage is A/B testing. A/B plays an inevitable role in a successful user experience. In this article, we will go through all the aspects of A/B testing and how this step is worth it for your business.
What is A/B Testing?
In simple terms, A/B is a method for identifying which website design, content, functionality, or anything else is attracting or more popular with your site visitors. In this testing, you check the different variations and elements of your page and how they are affecting your customers’ behaviour.
Some basic examples of A/B testing are quite popular such as changing button colors and CTA copy, but this is not even the scratch. There are many e-commerce businesses who don’t know how to conduct A/B testing effectively, and we are going to discuss the same in this article. If executed well, A/B testing can improve the highly important metrics or KPIs of your online business. Let’s understand the roadmap of A/B testing in this article.
How does A/B Testing Work?
A/B testing is basically an experiment in which we test two different versions of a website, app, or just a web page. With this, we identify the differences in user behaviour which leads to understanding user response. We collect and analyze statistical data to determine which version performs better.
It compares two versions of a web page. Variation A is the control version and variation B is the change that we are testing. It is also called Random Controlled Testing (RCT) as it ensures sample groups are assigned randomly.
It involves sending the exact same iteration of a web page to every visitor and using JS to make changes in the page within the visitor’s browser just before the visitor is shown the resultant page.
For e.g. you can send 50% of your incoming traffic to variation A and the rest 50% to variation B. After that, we analyze the performance of each variation.
Importance of A/B Testing:
As we mentioned, if properly implemented, you can deliver a better customer experience with A/B testing which ultimately leads to high click-through rates, high conversion rates, increased customer loyalty, and much more. Thus, even after developing an astonishing e-commerce store, if you are suffering from a low conversion funnel, then you can execute A/B testing to identify the cause. Some common conversion funnel leaks are:
- Baffling CTA buttons
- Poorly qualified leads
- Complex layouts of webpages
- Extreme friction on high-value pages leading to abandonment
- Checkout bugs
You can test various landing pages and other elements with A/B testing and identify the encountering issues. Here are the major important factors for conducting A/B testing:
1. Solve visitor pain points:
There are certain purposes of visitors when they land on your Magento store like:
- Know more about your discounts or deals offerings
- Explore the catalogue of your products
- Direct make a purchase of the decided item
- Reading or watching content about a particular product
Even casual e-commerce browsing is also a purpose. The hindrance in casual browsing can make it difficult for the visitor to meet their goals. For instance, a user may land on a different page which doesn’t match the PPC ad they clicked on, or a CTA button is difficult to find or not working at all. All such occurrences lead to high frustration which degrades the user experiences and lowers the conversion rates.
To get statistical data for understanding this user behaviour, there are multiple tools available like heatmaps, funnel analysis, session replay, etc. This data helps you know the source of pain points and start fixing them.
Analyze a problem using both quantitative and qualitative evidence. This will assist in identifying the problem and determining its root cause. No matter whatever tool you use, make sure you merge both types of data.
2. Increase ROI from existing traffic:
If there is already a good influx of traffic on your Magento store, then you can increase the ROI with A/B testing. The statistical data will also help businesses maximise existing traffic ROI. A/B testing helps to determine which adjustments improve UX and conversions. This strategy is frequently more cost-effective than investing in fresh traffic.
3. Reduce bounce rate:
Bounce page refers to how frequently a visitor comes to your website, views a page, and then leaves. Numerically, it is single-page sessions divided by the total number of user sessions on the website. There are several ways to define bounce rate, but the crux of them is the same: disengaged users.
Such frictions are always necessary for testing using A/B testing. You can identify the exact pages from which customers are bouncing and change things that seem problematic. Then, employ A/B testing to track the performance of different versions unless you observe some decline in the bounce rates.
4. Make low-risk modifications:
Making major changes to the website is always associated with high risk. You may spend thousands of dollars on improving a low-performing campaign. But there is no sense in spending such a huge amount if you don’t find any return on this investment. Thus, a better way to implement changes is by employing A/B testing rather than implementing a total redesign. So that, if a change fails you lose much less money and time.
5. Achieve statistically proven results:
It should be noted that the desired results can be achieved with A/B testing only if the sampling is statistically significant. It will not work if the concluded tests are based on random guesses or assumptions.
Statistical significance signifies the meaningfulness and reliability of A/B testing. The higher it is, the more reliable the result is.
6. Redesign websites to improve business margins:
If you want a full revamp or redesign of your website, A/B testing can be highly useful. As we follow the A/B testing method, there will be two versions of your Magento store. Then, you will measure the results statistically after receiving a significant number of visitors.
Make sure you don’t end the A/B testing after your Magento store goes live. Instead, you should use A/B testing to refine the elements within your site and test those.
What type of things you can test using A/B testing?
The main objective of the A/B testing is to remove consumer pain points. As the consumer journey frictions are reduced, it reflects an increase in the overall sales and profits.
In regards to a Magento store or an e-commerce store, these are the common elements that you can test using A/B testing:
- Page layouts of web pages
- Homepage and landing page
- Product pages, category pages, and product descriptions
- Social media posts
- Reviews, Testimonials, or other social proofs
- CTA button and copy
- Product images and other images of websites
- Push notifications
- SEO methods like meta descriptions and keyword volume
The best thing about A/B testing is that it can systematically work through each segment, incrementally and consistently improving each one to increase conversions.
Different Concepts in A/B Testing:
There are different strategies to consider for A/B Testing such as Multipage testing, Split URL testing, Dynamic allocation, and multivariate testing. Let’s discuss each one of these in detail:
1. Split URL Testing:
This testing is employed to make changes in a webpage in a scenario when you don’t want to make any changes in the existing URL. In the split URL testing, the testing tool will send a portion of your incoming traffic to one URL (variation A) and the remaining portion to another URL (variation B). At the basic, it is a complete redirect.
Split URL testing is useful when you don’t want to impact the user interface. For instance, if your purpose is to optimize page loading time or make other behind-the-scenes modifications. It is also useful to test workflow changes. If there is dynamic content on your site web pages, then you can test changes with split URL testing.
2. Multivariate Testing:
Multivariate testing is quite a complex form of A/B testing. It refers to tests in which page elements have multiple variants that are implemented and tested at the same time. The testers can find out which combination of page elements works best.
Multivariate testing reduces the need to run several A/B tests on the same web page when the objectives of each change are similar. Thus, it saves your time and resources by delivering results in a shorter period.
Let’s suppose instead of a simple A/B test on a page, you want to run a completely new multi-page experience. You have to perform step 1 to variate A or B, and step 2 to variate C or D.
In a multivariate test, you would be running multiple combinations of these variations:
- A then C
- A then D
- B then C
- B then D
In simple words, a multivariate test is a better way to perform several A/B tests at once. Since there are more tests or variations in multi-variate testing, it will require a much higher amount of traffic for statistical significance. Thus, it may take also more time to get the desired results.
3. Multipage testing:
In multipage testing, you make the changes on a specific element which is present on multiple pages and the test is performed on multiple pages, such as every page within a particular workflow. You use the sales funnel to identify the results. Then, you test the new pages against the control. This method is called “funnel multipage testing”.
4. Dynamic allocation:
In this method, you can quickly eliminate test low-performing variations. It not only saves time but also streamlines the testing process. It is also called the multi-armed bandit test. Suppose you want to launch a flash sale on your Magento store and want maximum traffic coming to your site to see your product on sale. For this, you show them a CTA colour which can get maximum clicks – blue, pink, or white.
A dynamic allocation test will help you determine which variation (colour in this case) is getting maximum clicks and automatically show that variation to the users. Thus, you get as many clicks as possible with this method.
Since the traffic is not in proportion, the dynamic allocation doesn’t give statistical significance and doesn’t yield any information or learning to use in future.
How to perform A/B Testing?
The objective of A/B testing is to identify which changes or variations can give us the desired results and which do not. The A/B testing consists of multiple stages:
- Observe and formulate a hypothesis
- Variations creation
- Test running
- Analyze Results
- Deploy the changes
Let’s discuss each stage in detail.
We must set a performance baseline before conducting any tests or making any changes. Both qualitative and quantitative data must be collected to understand how our website is performing in its current state.
Quantitative data consists of elements like bounce rate, views count, traffic count, subscriptions, averages added to the cart, purchases, downloads, etc. This data is easily available through analytical tools.
Qualitative data includes information collected based on UX and overall services through polls and surveys. When used with quantitative data, it gives a better understanding of the site performance.
2. Observe and formulate a hypothesis:
In this stage, we analyze the data that we have/collected and note down the observations that we make. It is the best method to create a hypothesis which will lead to more conversions. Thus, A/B testing is hypothesis testing.
3. Create Variations:
In this stage, we create variations which are the newer versions of a current page having any changes that we want, and that we need to test. These changes could be anything like a CTA colour change, CTA button change, change to copy, headline change, etc.
4. Test run:
You will choose the selection method based on your goal and factors like expected traffic. The test length also depends on the level of accuracy we want. Always remember, that a higher statistically significant result is more reliable but requires equally more time and traffic.
5. Analyze the result and deploy the changes:
By this stage, you will have results on your hand and now you have to draw conclusions. You would be able to determine which version could outperform the other and thus you can decide which change to deploy.
But that is not always the case. You may be required to run additional changes to gain additional insights. Additionally, you may elect to proceed to test modifications in another portion of the procedure. A/B testing allows you to iterate through all of the pages in a customer journey to enhance UX and increase conversions.
At Ceymox Technologies, the best Magento development company in India, we have expertise in developing Magento stores from scratch, that are carefully curated as per the standard results of the A/B testing. We first understand client requirements, conduct deep research, provide the best consultation, and deliver a fully-fledged product. Let us know your requirements.