A/B Testing: Methods, Examples and Method

A/B Testing: Methods, Examples and Method

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Updated on Aug 15, 2022 19:28 IST

A/B Testing is a strategy for determining how a changed variable impacts audience or user engagement. It is a typical strategy to increase campaigns and target conversion rates in marketing, web design, product development, and user experience design.

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Table of Contents

What is A/B Testing?

A/B Testing (either split testing or bucket testing) compares two versions of a website or app to see which one performs better. A/B Testing is simply an experiment in which two or more page variations are randomly presented to users. The statistical analysis evaluates which variant works better for a certain conversion target.

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Why consider performing A/B Testing?

The following reasons facilitate A/B testing:

1. Identify and remove the user’s pain point.

Visitors come to your website for accomplishing a specific goal. It might be to learn more about your product or service, to purchase a certain product, to read/learn more about a specific topic, or simply to explore. Whatever the visitor’s purpose, they may encounter certain similar pain spots while doing it. It may have unclear language or be difficult to locate the CTA button such as purchase now, request a demo, click to read, submit the review, etc.

Failure in case of not meeting their objectives results in a negative user experience. This creates friction and affects your conversion rates. To tackle your visitors’ pain points, use data acquired through visitor behavior analysis tools such as heatmaps, Google Analytics, and website surveys. This is true for every business, including eCommerce, travel, education, media, and publishing.

2. Improve the ROI from the existing traffic

The expense of gaining quality traffic to your website is enormous. A/B Testing allows you to make the most of your existing traffic and enhance conversions without spending additional money on obtaining new visitors. A/B Testing may provide a high return on investment since even little modifications to your website can significantly improve overall business conversions.

3. Reduce bounce rate

The bounce rate is considered to be one of the most important metrics to monitor when evaluating the performance of your website. There might be several causes for your website’s high bounce rate, such as too many alternatives to pick from, mismatched expectations, difficult navigation, overuse of technical jargon, and so on.

There is no one-size-fits-all strategy for lowering bounce rates since various websites serve different aims and appeal to diverse subsets of users. Running an A/B test, on the other hand, can be advantageous. A/B Testing allows you to test multiple variants of a website element until you discover the best possible version. This helps you identify friction and visitor pain spots and improves the entire experience of your website visitors, leading them to spend more time on your site and even convert into paying customers.

4. Redesign website to increase business gains

Redesigning can range from making minor changes to CTA language or color on specific web pages to totally redesigning the website. When A/B Testing, the choice to deploy one version or the other should always be data-driven. Do not stop Testing until the design has been finalized. Test other web page components once the new version goes live to ensure that the most engaging version is provided to visitors.

How does A/B Testing Work?

An A/B test involves modifying a webpage or app screen to generate a second version of the same page. This modification might be as small as a single headline or button, or it can be as extensive as a complete redesign of the website. The original version of the page (known as the control) is then shown to half of your traffic, while the updated version is presented to the other half (the variation).

Visitors’ interaction with each session is measured and gathered in a dashboard before being assessed by a statistical engine as they are fed the control or variation. You can then evaluate if the change had a good, negative, or neutral effect on visitors’ behavior.

What are the different types of A/B Testing methods?

There are majorly four different types of tests:

  • A/B Testing
  • Split URL Testing
  • Multivariate Testing
  • Multipage Testing

Since we have already learned about the A/B Testing method, let us explore the rest of the testing methods:

1. Split URL Testing

Many individuals in the testing industry mix up Split URL testing with A/B Testing. However, the two are essentially distinct. Split URL testing is an experimentation procedure that involves testing a new version of an existing web page URL to see which one performs better.

A/B Testing is typically used when you just want to test front-end modifications to your website. On the other hand, split URL testing is employed when you want to make big modifications to your existing website, particularly in terms of design. 

Benefits of using Split URL Testing

  • Ideal for experimenting with new ideas while comparing them to the current design.
  • Running Testing with non-UI modifications, such as moving to a new database or reducing your page’s load speed.
  • Effective and widely recommended testing approach for dynamic content.
  • Alter web page workflows. Workflows have a significant impact on business conversions, allowing you to test new pathways before adopting changes and see if any blocking spots were overlooked.

2. Multivariate Testing

Multivariate Testing (MVT) is an experimentation approach in which variations of many page variables are tried simultaneously to determine which combination of factors performs the best out of all conceivable permutations. It is more difficult than a standard A/B test and is best suited for expert marketing, product, and development specialists.

Multivariate Testing, when done correctly, may remove the need to perform several sequential A/B tests on a web page with similar goals. Concurrent Testing with a bigger number of variants allows you to save time, money, and effort while reaching a result in the least amount of time.

The Benefits of Multivariate Testing

  • Eliminates the need to run many sequential A/B tests with the same aim.
  • Analyze and identify the contribution of each page element with ease. 
  • Map all interactions between all independent element variants (page headlines, feature images, etc.).

3. Multipage Testing

Multipage Testing is a type of experimentation in which modifications to specific items are tested over numerous pages.

A multipage test can be done in two ways. One, you may take all of your sales to funnel pages and build new copies of each, making your alternate sales funnel, and then test it against the original. This is referred to as Funnel Multipage testing.

Second, you may test how adding or removing repeating elements, such as security badges, testimonials, and so on, affects conversions throughout an entire funnel. This is referred to as Classical or Conventional Multipage Testing.

The Benefits of Multipage Testing

  • Allows you to provide consistent experiences for your targeted users.
  • Ensures that your target audience sees a consistent set of pages.
  • Allows you to make the same adjustment on several pages to guarantee that your website visitors aren’t distracted and hop between numerous variants and designs while browsing your site.
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How to Perform A/B Testing?

  • Collect Data: Your analytics will frequently reveal areas where you may begin optimizing. To collect data more quickly, start with high-traffic parts of your website or app. Look for pages that have low conversion rates or a high drop-off rate and may be improved.
  • Assess your conversion goals: These are the measurements you will use to determine if the variant is more effective than the original version. Goals might range from just clicking a button or link to making a purchase or signing up for an email list.
  • Create hypotheses: Once you’ve decided on a goal, you can start brainstorming A/B testing concepts and hypotheses for why you believe they’ll be better than your current version. Once you’ve compiled a list of ideas, rank them in terms of predicted impact and implementation difficulties.
  • Create variations: Make the needed adjustments to an area of your website or mobile app experience using A/B testing software (such as Optimizely). This may be altering the color of a button, rearranging the pieces on the page, concealing navigation elements, or something completely unique. Many popular A/B testing programs provide a visual editor that makes making modifications simple. Ensure that your experiment is tested to ensure that it works as planned.
  • Experiment: Start your experiment and wait for visitors to join in! Visitors to your website or app will be randomly allocated to either the control or variant of your experience at this time. Their involvement with each event is monitored, tallied, and compared to assess how everyone performs.
  • Analyze the results: Once your experiment is finished, it’s time to examine the findings. Your A/B testing program will display the experiment data and show you the difference in performance between the two versions of your website and whether there is a statistically significant difference.

Congratulations if your variant is the winner! See if you can apply the experiment’s learnings to other site pages and keep iterating on the experiment to enhance your findings. Don’t be worried if your experiment yields a negative or no outcome. Use the experiment as a learning opportunity to develop new hypotheses to test.

A/B Testing Examples

Let us consider three examples of A/B testing to understand it completely.

1. A/B Testing in Media Company

A media and publishing company may aim to increase user engagement and audience, increase subscriptions, increase user time spent on their website, or increase video views and other content pieces through social sharing, among other things. You might experiment with different email sign-up modals, recommended content, social sharing buttons, advertising subscription offers, and other promotional choices.

Anyone who has used Netflix can relate to the quality of their streaming service. But not everyone understands how they do it so well. Here’s how it’s done: Netflix uses a systematic and rigorous A/B testing methodology to offer what most organizations, despite their best efforts, still struggle to deliver – a wonderful customer experience. Every modification to Netflix’s website is subjected to extensive A/B Testing before being implemented. Personalized content is one of the ways they achieve it. 

Netflix’s homepage makes extensive use of personalization. Netflix customizes the homepage based on each user’s information to deliver the best user experience possible. Based on the user’s streaming history and choices, they select how many rows appear on the site and which shows/movies appear in the rows.

2. A/B Testing in Travel Company

A/B Testing may help you increase the number of successful reservations on your website or mobile app, income from auxiliary sales, and much more. You might experiment with your home page search modals, search results page, supplementary product presentation, checkout progress bar, etc.

Booking.com outperforms all other eCommerce firms in the travel market when it comes to employing A/B Testing for optimization. They test as if it were no one’s concern. Since its start, Booking.com has viewed A/B Testing as a treadmill that produces a flywheel effect for revenue. Booking.com’s A/B testing scale is unparalleled, particularly when testing their material. While reading this, Booking.com’s website conducts roughly 1000 A/B tests.

Even though Booking.com has been A/B Testing for almost a decade, they believe there is always more they can do to improve customer experience. This is what sets Booking.com apart from the competition. Booking.com has used A/B Testing in its daily operations since its inception. They boosted their testing pace by prioritizing data above anything else. All Booking.com workers were permitted to perform tests on concepts they felt may help the company develop to enhance testing speed even further.

3. A/B Testing in E-commerce Company

Online retailers may use A/B Testing to boost average order value, optimize their checkout funnel, minimize cart abandonment, and so on. You may experiment with how shipping costs are shown, where, whether, and how the free shipping option is highlighted, text and color changes on the payment or checkout page, the visibility of reviews or ratings, and so on.

Amazon is at the top of conversion optimization in the eCommerce business, partly because of the size at which they operate and partly due to its unwavering commitment to offering the greatest customer experience. Among the numerous new methods they introduced to the eCommerce business, the most successful has been ‘1-Click Ordering.’ After considerable Testing and analysis, 1-Click Ordering was introduced, allowing consumers to make purchases without using the shopping cart.

After entering their usual billing card information and delivery address, customers must click the button and wait for the bought things to arrive. Users must not re-enter their billing and shipping information when purchasing orders. With 1-Click Ordering, users could no longer disregard the convenience of buying and proceed to another store. 

People who work on optimizing Amazon’s website do not get ‘Eureka’ moments for every modification they make. Amazon can provide the user experience it provides because of ongoing and organized A/B Testing. Every modification to the website is first tested on its target audience before being implemented. Suppose you look at Amazon’s buy funnel. In that case, you’ll note that, while it’s similar to other websites’ purchase funnels, every aspect of it is fully optimized and meets the audience’s expectations.

Conclusion

We hope that you have been able to understand the concept of A/B testing in detail through this article. Visit our articles to learn more detailed concepts.

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This is a collection of insightful articles from domain experts in the fields of Cloud Computing, DevOps, AWS, Data Science, Machine Learning, AI, and Natural Language Processing. The range of topics caters to upski... Read Full Bio