“You cannot grow unless you change.”
This statement is often repeated in the marketing world, and rightfully so. Given that many brands struggle to grow consistently, this little piece of advice offers the perfect solution.
Growth invites change. If your brand doesn't adapt to audience needs, that's reason enough for them to move to your competitors.
But how do you make the right changes?
Any decision you make significantly impacts your digital properties. Since these properties are essentially the face of your brand, any changes you make need to be positive and sustainable.
To improve your brand recognition, you can either make random changes and hope that things work in your favor or adopt a more strategic and logical approach with the help of A/B testing.
A/B testing is an experimentation process where groups of visitors are shown different versions of a webpage or campaign to determine which performs better in engagement, user experience, and other specific goals.
In simple terms, A/B testing is all about finding the best possible option with the help of data and statistical analysis.
Here, you have a “control,” the original version of a page, and a “variation,” which is the updated version. A/B testing helps display these versions simultaneously to randomly selected visitors for a specific duration.
At the end of the test, the results are analyzed to determine which version performed better in terms of the previously defined goals.
Source: UNSW DataSoc
Common conversion goals for A/B testing include increasing purchases, add-to-carts, form submissions, free trial sign-ups, and so on.
With the help of an A/B testing platform, you can randomly assign visitors to the control and variation. The version that performs better is declared the winner of the A/B test.
Since this is done by analyzing the results at the end of the test, A/B testing offers a statistically significant way to measure the impact of the changes you made in the variation.
Also, once you determine a winner, this new version can be used as the “control” variation. You can then choose to continue the A/B testing process or directly implement the changes on the page.
So, rather than relying on guesswork and intuition, you utilize data to optimize your website and drive key business metrics.
Moreover, A/B testing is an essential part of conversion rate optimization (CRO) – a process where visitor behavior is analyzed to optimize the overall page experience and boost conversion rates. A conversion occurs when a visitor takes the desired action on your website or app.
The ultimate goal of A/B testing is to improve conversions, i.e., persuade more and more visitors to take the action you want them to take. It could be anything from clicking a call-to-action (CTA) button, adding items to the cart, and scrolling beyond the 50% viewpoint of the page, to viewing a video.
You can experience the benefits of A/B testing in many ways. Let's take a look at the different methods to conduct A/B tests.
This is an experiment where two versions of the same web page are tested. In scenarios where you wish to test significant changes on an existing page, like a homepage redesign, you should opt for split URL testing.
The idea is to change multiple variables on the same page and test all possible combinations simultaneously to see which performs best. For example, using this method, you can create multiple variations of a form where changes to the headline, number of fields, and color of the CTA button are tested simultaneously.
In multipage testing, you change specific elements across several pages and determine which page performs better based on how your visitors interact with them.
Let’s say your sales funnel includes a home page, a product page, and a checkout page. With the help of multipage testing, you can create new versions of each page and test this new set of pages against the original sales funnel. Moreover, you can use this method to test how changes to recurring elements in these pages impact the entire funnel's conversions.
Regardless of the method, a well-defined A/B testing framework allows you to make data-driven decisions, improve website performance, and optimize your target audience's overall experience.
The key to growing a successful business is identifying what’s working and what isn’t. And this is precisely what A/B testing offers, along with a better understanding of user behavior, audience pain points, and website performance.
An A/B test also lets you test changes on a smaller group within a controlled environment, minimizing the risk of shipping something that doesn't resonate with your target audience. It's a cost-effective and time-saving strategy.
Ideally, A/B testing should be integral to your marketing campaigns as it helps optimize the better-performing elements while understanding what needs to be changed or improved.
Source: Finances Online
While dealing with common conversion problems like cart abandonment and page drop-offs, businesses often miss out on the core issue – bad user experience. This usually happens when visitors face problems, preventing them from achieving a particular goal on your website.
Regular A/B testing helps identify these pain points while allowing you to make calculated changes to improve user experience. Moreover, it identifies factors that impact user experiences the most, so you can further optimize key elements and improve your core conversion metrics.
A/B testing helps improve user experience and discover untapped opportunities to boost website performance. It gives you the right insights to make data-backed decisions to further boost marketing strategies.
Each A/B test gives you a better understanding of how the audience interacts with your website. It helps you visualize user journeys and identify roadblocks that prevent them from taking a specific action.
Take WorkZone, for example, which is a US-based software company offering robust project management solutions to organizations. They had a lead generation page where visitors were asked to complete a demo request form.
To build trust and reputation, WorkZone added a “What Customers Say” section next to the form. However, with the help of A/B testing, they discovered that the brand logos added in this section were distracting the visitors from filling up the form.
So, they decided to run a quick A/B test with a different variation where the color of all the brand logos was changed to black & white.
This simple change in the new version generated a 34% increase in form submissions for WorkZone. Similarly, based on the results of your tests, you can also make smart, informed decisions that boost audience engagement and improve the conversion rate.
A/B testing helps you better understand the goals, intentions, preferences, and other crucial aspects related to your target audience. With apt insights, it's easy to tweak certain elements and test various data-backed hypotheses that solve customer pain points and encourage them to take the desired action.
For instance, Northmill is a popular fintech brand from Sweden that wanted to optimize its loan application page. The original version had an application form on the side where visitors could fill in their details and apply for a loan.
The team at Northmill hypothesized that replacing the side form with a single CTA button would help visitors better understand the company’s offerings leading to more people applying for the loan.
So, in the new version, the form was replaced with a green “Apply” button at the top-right corner of the page.
After running the test for almost five months, this new version generated 7% higher conversions.
Besides improving user engagement, the data collected through A/B testing also tells why users quickly drop off or bounce off your website.
For example, Inside Buzz UK (now known as Target Jobs) noticed many visitors dropping off their home page without taking action.
They decided to update the entire page and run an A/B test to find out which version performed better in terms of engagement. The new version had a simple design with a single CTA button and only included elements considered necessary for the visitors.
The test results showed that the new variation had a lower bounce rate and a 17.8% increase in user engagement.
Every element in your conversion funnel should be optimized for your target audience. This includes images, headlines, CTA buttons, page design, etc.
When Hubstaff, a leading brand that offers workforce management solutions, wanted to optimize its landing page, it turned to A/B testing.
With continuous experimentation, the team identified elements on their landing page that were not performing well. Based on this data, they redesigned the entire page and ran a “Split URL” test to compare both versions.
At the end of the test, the new version saw a 49% increase in visitor-to-trial conversion and a 34% rise in the number of people sharing their emails.
So, A/B testing not only has a positive impact on your conversion rates, but it also boosts the overall performance of your website.
Now that you’ve seen the potential benefits, you can go ahead and start running successful A/B tests on your website, right?
Well, not exactly.
Before you run any A/B test, consider a few important factors.
Although it seems like a simple idea you can implement right away, A/B testing requires a lot of thinking, research, and analysis.
First, you must understand that A/B testing is not a one-off concept. It's a continuous process that requires proper planning, consistency, and structure.
Moreover, you can’t just make random changes to certain pages and expect positive results. A/B testing is more about creating highly optimized page experiences that can convert visitors and boost your CRO processes.
To efficiently manage these elements, you need a good A/B testing platform to run continuous tests with actionable insights about customers, traffic, performance, and other important factors.
So, here’s how you can start your A/B testing journey:
To create a successful A/B testing strategy, you must first study and analyze your website. Start by understanding its current state, the pages performing well, the type of visitors converting, and the amount of traffic coming through different campaigns.
Tracking performance lets you identify pages that drive the highest traffic or elements with a good potential to convert visitors. This is a solid starting point for your A/B testing plan. You can then shortlist these pages and identify opportunities to optimize or improve their performance first.
Once you finalize the pages you wish to optimize, perform a detailed analysis of the traffic coming through these pages. A/B testing tools offer a complete overview of visitor data through features like on-page surveys, heatmaps, and session recordings.
Apart from collecting the usual type of data like age, region, and demographics, these tools gather crucial information like time spent on a page, scrolling behavior, etc. The visitor insights help you identify common pain points in their journey and work on finding optimal solutions.
Now that you’ve analyzed the website and identified problems visitors face, research and develop data-based hypotheses for these issues.
For example, you may observe that a large number of visitors are dropping off without submitting your form. You hypothesize that reducing the number of mandatory fields will result in more people submitting the form. Similarly, you can develop other data-backed hypotheses for this problem.
You can test one or all of these hypotheses against the form's existing version (control). This brings you to the most important part of A/B testing.
Firstly, you need to choose a method for testing your hypotheses. After that, define specific goals for the A/B test based on conversion rate, number of visitors, duration of the test, and so on.
This will help you analyze the results and determine the better-performing version. Ensure that each test version runs simultaneously and for the same duration. Also, make sure that all versions' traffic is split equally (and randomly) whenever possible.
Don't forget to actively monitor the performance of all versions and run the tests for a specific duration to get statistically accurate results.
After your test concludes, evaluate the results.
This is, undoubtedly, one of the most important steps of any A/B test as you finally get a chance to analyze the results based on the previously defined goals.
If your hypothesis is proved right, you can make the changes and replace the existing version with the winning variation. However, if the results fail to deliver a winner, gather relevant insights and continue testing other factors that may lead to positive results.
A/B testing is a continuous process that requires in-depth research and analysis while giving you a chance to boost conversion rates and improve the overall site performance.
Next, start identifying page or site elements with the highest potential to drive revenue.
Creating a strong A/B testing hypothesis can be quite challenging. Here are a few A/B testing ideas for experimentation and analysis.
These ideas will kickstart your A/B testing journey and take your conversion optimization campaigns to the next level.
Although a robust A/B testing framework can boost your marketing campaigns, you might encounter a few challenges during the process.
Most organizations struggle with the A/B testing process when formulating hypotheses, especially if they don't have reliable data. To come up with effective hypotheses, conduct thorough research and identify problem areas in your website.
The sample size of the test group significantly impacts an A/B test's results. Each A/B test should have a large sample size to get accurate and statistically significant test results. If the sample size is too small, the results of your A/B test might be unreliable.
Analyzing the results correctly and making informed decisions is another key challenge. Misinterpretation often results in incorrect decisions that can hamper your business growth. So, carefully analyze the test results and remove any bias from external factors you didn't consider.
It's not always easy to make changes based solely on A/B testing. More often than not, various factors like bandwidth issues and resource limitations stand in the way. To successfully implement the changes, create a clear roadmap for your A/B testing program and prepare ahead of time.
Just because a few of your A/B tests failed doesn't mean you give up. A/B testing requires constant analysis and planning. Determining why your A/B test failed will help you uncover problem areas and gain a better perspective of the audience.
Developing an A/B testing culture that blends seamlessly with your overall marketing strategy is crucial for your website's long-term growth and improvement. Although these challenges are common for any A/B testing program, you can gradually overcome them with some best practices.
A/B testing is all about research, statistics, and analysis. But, more importantly, it requires consistency.
Here are a few tips and general best practices to keep in mind and manage a successful and efficient A/B testing program.
Before implementing A/B testing on your website, define your goals, expectations, insights, opportunities, and other important aspects of your A/B testing framework. This also involves formulating hypotheses based on reliable data and actionable insights.
Just because Amazon has a bright, orange CTA button that works well for them doesn't mean you make similar changes to your CTA button. One of the most common A/B testing mistakes is replicating successful test results of other websites on your pages. Instead, you should make calculated decisions based on your website's goals, audience, and traffic to achieve accurate results.
Deciding what to test on your website can be tricky. Based on research and analysis, you need to choose elements that significantly impact traffic and conversions. For example, start by looking at pages that register the highest traffic and identify key elements to optimize and improve conversions.
Running multiple tests simultaneously on the same page isn't a good idea. You may be unable to identify the elements that influenced your results among the tests. When you change only one variable at a time, you give yourself a better chance of understanding the results while avoiding skewed data.
What is the best duration for an A/B test?
Although there's no fixed number, you can determine the duration of a test based on the traffic, goals, and other important aspects of your website. You can use free A/B test duration calculators to better understand your test's ideal length. Running your A/B tests for sufficient time is crucial to ensure reliable and accurate results.
Suppose that your website usually sees a spike in traffic during the weekends. Running your test over multiple weekends can help account for this increase and avoid misinterpreting the test results.
As soon as the test concludes, you should focus on studying the results carefully. Apart from determining a “winner,” these results will also give you some useful insights that you can use to improve future tests and campaigns.
With the help of these best practices, you can give your A/B testing program a better chance of delivering reliable and effective results for your website.
As you experiment and try out different changes on your website, ensure that your A/B testing platform is tracking important metrics and delivering useful insights for each test.
Here are the common goals tracked during A/B tests that you should focus on while monitoring the different tests on your website.
A/B testing is a powerful concept that can help optimize your marketing efforts and drive key business metrics. Although there are quite a few factors that one must consider while running different tests, the core idea of A/B testing is to improve user experience by optimizing key conversion metrics.
Want to build the best possible version of your website? Learn how by evaluating consumer responses to multiple variables and tracking engagement using multivariate testing.
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