A/B testing

Introduction

A/B testing is a popular, tried, and true research methodology that is extensively used in marketing, web design, and development, as well as in UX/UI development. The methodology is helpful in determining which version is the best and will help draw favorable results. However, there’s more to A/B testing than testing alternative options. This blog covers everything you need to know about A/B testing, how it works, the benefits, and why you should consider it.

What is A/B Testing?

A/B testing or split testing is when a version of an element (which can be a web page, a piece of code, an ad campaign, etc) is tested against each other to find the most effective version. The test is conducted by showing the two versions to a segment of the audience at the same time and tracking their response to both versions. The variant that is able to draw maximum traction is considered to be the best version and is then implemented on a larger scale. A/B testing takes away the guesswork associated with the efficiency of an element by allowing real-time testing of multiple variants. A/B testing makes it possible for marketers, developers, and designers to make data-backed decisions and not solely work on guesswork. Due to this, A/B testing is a time and cost-efficient method to understand if your efforts will yield results when implemented for a wider audience.

How A/B Testing Works

Let’s take a web page as an example. To start with the A/B testing process, two or more web page versions will be made by introducing slight variations. These differences do not have to be massive. For instance, the placement of an offer can be in the form of a call-to-action button at the hero space in variant ‘A,’ whereas, in the ‘B’ variant, the offer can be placed as an announcement bar. Web pages with these variants (A & B) can then be shown to two different segments of traffic. The engagement rate on both pages can be measured and then subjected to statistical analysis to understand which page version was able to draw the most engagement.

Why should you consider A/B testing?

As marketing teams, designers, and developers are constantly analyzing the market, they are most likely to come up with a plethora of ideas with the potential to scale the business. A/B testing makes it possible to test variations of these ideas to understand if the newfound ideas are worthy of implementation on a larger scale or if there are further changes that can turn the wind in your favor. Here are more reasons to conduct A/B testing frequently:

• It can improve user experience on the website 

As A/B testing allows the testing of multiple combinations at once, it saves time in identifying elements that can potentially draw the target audience's interest. These alternatives can range from ad copy, visual media used, placement of interactive objects, color and font preferences, and the language your potential users find easy to take a desirable action in. This helps fine-tune the existing model by including elements from a potentially high-performance page.

• Significantly lowers the bounce rate

A/B testing aims to find the most engaging and interactive elements that can be included on a web page. This is implemented with the intention of maximizing attraction without the browser losing interest in the web page. A lower bounce rate has SEO benefits as it signals to search engines that your website has valuable information, resulting in people staying for longer.

• Improves the quality of your content

A/B testing for ads involves showing different ad sets to different target audience segments. This allows marketers and advertisers to come up with variations in the ad copy to gain the most traction. Alternatively, the same can be implemented in the case of a landing page, where different copies can be tested to gauge the effectiveness of the content, call-to-action buttons, and other factors. With this, your business will always be putting its best foot forward.

• Driver higher conversion values

With A/B testing, you get to experiment with different versions, eventually adding to datasets that can be referred to in case a similar campaign has to run. It will save a plethora of time without compromising on the quality of the result. Once the campaign goes live using historical data, minor adjustments will ensure you are able to attract higher traffic and, eventually, conversions without spending too much of your budget on running campaigns.

• It gives room to experiment 

Making sudden, significant changes can be risky and go either way. No business should take that risk, and A/B testing ensures you are able to test the waters before making a final decision. It adds the confidence of making a decision that is backed by real-time data derived from testing the variations. This ensures you are able to make changes without compromising on the elements your brand is known for.

• The analysis is easy

Determining a winner is an easy and straightforward process with A/B testing. There are no complexities involved. With both the variants tested on the same set of parameters and metrics, it becomes significantly seamless to understand the parameters favoring which variant. This takes away the stress of having to dive into deeper insights to find a desired result.

• Benefits ecommerce stores 

Cart abandonment, showing announcements, or presenting tempting, hard-to-miss offers are merely some struggles that ecommerce businesses have to go through on a regular basis. With A/B testing, a brand can test multiple variations of presenting an offer and finding the best possible solution to gain attention and have successful checkouts.

A/B Testing Process

Before starting with A/B testing, here are a few steps that must be taken for a successful run:

• Make a clear list of appropriate items that you need to test. Be specific with the elements to test their effectiveness. Having too many elements for testing can cause confusion and produce large datasets that can become difficult to analyze.
• Determine the sample size you are looking to work with. A large sample size will produce complex results, whereas an overly small sample size produce inconclusive results. Setting parameters that yield a successful outcome will ensure you are able to pick a sample size appropriate for testing.
• Measure the results from the testing to determine the effectiveness of the process. A statistically significant number will help estimate which sample set yields the best results.
• Timing your tests to ensure both variations are exposed to the same influx of traffic is crucial to ensuring accuracy in data collection. Without the right exposure to traffic, there will be inconsistency in results, making it challenging to determine if the test was a success or if you need to conduct the testing for more extended periods of time.
• Avoid testing too many elements at once, as doing so can significantly impact the intended audience’s behavior. These behavioral changes can be drastic, making tracking and pinpointing challenging. Instead, focus on testing one element at a time to ensure that you are able to measure the results and take action on it.
• Analyzing the datasets is a crucial step to determine if the available data corresponds to the nature of the information you were looking for. It also makes it possible to really understand what your target audience is looking for and their changing behavior towards the range of products or services your business has to offer. This information will also help you determine if other strategies need to be adjusted to accommodate the changing consumer behavior or not.

Now that you have everything you will need to get started with A/B testing, here is how to conduct the testing:

• Choose a variable you intend to test

While you are measuring your website, ad campaign, or email performance, you will come across multiple factors you might want to test. However, the focus should be on identifying an independent variable to test and measure. Once you have picked an element to put to the test, create versions you believe will be impactful in drawing desired results (more appointment bookings, eBook downloads, subscription to a free service, etc). Using a heatmap tool can be advantageous as it will help you understand where your target audience is spending most of their time and which areas of the design are getting the least interaction. Placing your offer or important content in the hot zones will enable you to attract more conversions.

• Keep a goal in mind 

Throughout the testing, you will be measuring several metrics. However, it is crucial to identify the key metrics that you want to focus on. Ensure you prioritize this dependent variable at the beginning of the testing. These variables will change their properties when the independent variables are altered, giving you the chance to track a wide range of results and identify any potential opportunities.

• Spilt the testing groups at random

Splitting the testing groups is crucial to noting how your target audience reacts to each set and how you can leverage the best-performing features from the available sets to your advantage. This step can be vital in determining how a random sampling of visitors is responding to the subject.

• Identify statistical significance

Tracking the goal metric is vital to ensuring your testing yields valuable results. However, it is equally important to determine if the metrics you are tracking will govern significant changes in your current, existing version. Avoid deciding to change all elements of your current version to the best-performing test variant, as it can take away the elements that were already working but needed a slight boost to perform better. Building your test variants on an original version is thus helpful in ensuring that you have a basic framework in place that only needs to be optimized for conversions. Taking statistical data into account will ensure you are able to improve your current standing without losing out on the initial essence of your strategy.

A/B Testing Examples

Here’s an example of how A/B testing benefitted media giants like Netflix: Netflix is known for offering an impeccable streaming experience to its users. However, this was not achieved overnight.

Here’s how Netflix achieved this:

• They created and followed structured, rigorous A/B testing with the aim of delivering a smooth user experience.
• Every change that was to be made on their platform underwent extensive testing to identify the best version and implement it for enhanced user experience.

For instance:

• Netflix focuses on customizing the homepage experience based on individual profiles.
• This customization helps users find shows or movies that align with their interests by showing an array of available titles based on their streaming preferences and history.
• It eventually results in people finding new releases in the genre they are interested in or fascinated about.

A/B testing & SEO

Search engines like Google encourage A/B testing as it can help a website improve the quality of user experience being offered to its visitors. Here are a few things to keep in mind when conducting A/B testing:

• Use the rel="canonical" attribute to point variations of the page back to the original source.
• Prefer using a 302 redirect to take the visitor to the variation of the URL from the original URL.
• Avoid cloaking and adhere to showing the same content to search engines that you will be showing to your target audience.

A/B testing for a better, improved browsing experience 

A/B testing is the key to finding elements on your website or email templates that can strike the right chord with your target audience. However, it is important not to change your online presence wholly based on the statistical data. Instead, you must focus on creating a seamless, wholesome, and action-oriented implementation that helps your potential customers convert quickly. Still in doubt? Get in touch with our experts today to find out how we can make A/B testing win your business. A/B testing can help break the ice and enable you to attract, nurture, and convert more customers. But how do we conduct testing and choose a variant? Read here!