How to Use A/B Testing to Improve Your Website’s Conversion Rate

Intro

Many marketers may think they have a good handle on what works and what doesn’t. But the truth is, gut instincts can lie. That’s where you should take the guesswork out of the equation and conduct A/B testing.

A/B testing is the process of analyzing the effectiveness of your strategies in real-life and in real time. You can see how certain elements, like headlines or calls to action, and pages perform. You can observe the visitors’ reactions. The result of the A/B testing is your understanding of what to introduce or remove from the website.

Another benefit of A/B testing is its ability to increase the website’s conversion rate. But what is A/B testing, what types exist, and how to start? In this article, we’ll study the basics of A/B testing and provide tips for successful implementation to begin testing with confidence.

Understanding a conversion rate and its importance

What is a conversion rate?

Suppose you start a business to sell your products or services. You create a website or app and expect visitors to consume your content and do some actions. These actions are conversions, and you need to continuously increase their number. That’s where we should define conversion rate optimization (CRO).

What is conversion rate optimization all about? CRO is the process of increasing the number of people who perform the desired action (convert), such as:

• schedule a call;
• buy a product;
• subscribe to an email newsletter;
• book a demo, etc.

You can improve the conversion rate for any business or focus on the eCommerce conversion optimization. In any case, you need to simplify the path visitors need to take to purchase goods. It may include untangling navigation or displaying certain links, anything to show customers the way.

Why does a conversion rate matter?

Conversion rate is one of the most crucial metrics because it illustrates what users are looking for, what they like, and what prevents them from proceeding to other pages. The possible reasons for a low conversion rate are endless, such as:

• poor usability;
• sluggish performance;
• ad ineffectiveness;
• inconvenient button placement;
• small sizes of links to tap with one finger, etc.

Imagine you have 100 visitors to your website, but only one makes a purchase. That’s a conversion rate of 1%. But, with CRO tactics in place, you can potentially increase that conversion rate to 2% or even higher!

A deep analysis of the conversion rate and tweaking of various website components can improve the design. That means more sales and revenue for your business and enhanced customer satisfaction, and who would refuse that? That’s why you should boost this metric.

What is A/B testing, and why should you consider it?

What is A/B testing?

A/B denotes comparing two versions of website features. You create versions A and B of one element and display them to users. Note that you should split the traffic evenly to see the right results.

Suppose you want to check whether the text is visible enough and make it bigger. The new text would be version B. The second half of visitors would see a standard text on your website (version A). Then you compare key performance indicators (KPIs) and metrics on each page and determine the winning option.

Benefits of A/B testing

A/B testing is a reliable way to define how your website should look to bring more conversions. According to data, 58% of businesses employ A/B testing for CRO. It also provides the following advantages to companies:

• making informed decisions;
• increasing revenue;
• removing friction on the purchase journey;
• addressing customers’ pain points;
• improving the user experience;
• preventing people from leaving the website (reducing a bounce rate);
• making smaller-scale modifications and reworking the websites step-by-step.

What types of testing exist?

Split URL testing

There is a lot of confusion between the words split testing and A/B testing. Split testing compares one version of your website—the control version—against another—the “variation” page—to see which one website visitors respond to the best.

These pages should have the same goal, such as encouraging people to purchase. But the design should differ more significantly compared to A/B testing, which involves minor, single modifications made to the control on the front end. Plus, pages in split testing should reside on different URLs.

Multivariate testing

This type of testing refers to testing several combinations of items simultaneously. You alter multiple items on a page, so the final product’s appearance may fluctuate significantly across versions.

Multipage testing

A multipage test comes into play if the element is present on several pages but isn’t the same, appears somewhere else, or has a different name. You can do it in two ways:

• Funnel Multipage Testing: redesigning the whole sales funnel to produce a new version;
• Conventional Multipage Testing: changing or replacing particular elements, such as buttons, banners, badges, reviews, etc.

A/B testing process in detail

1. What are your goals?

Identify your business and website purpose. What do you consider conversion, and what brings the most profit? You may aim at increasing the number of orders, the average order value, subscriptions, or only clicks on ads. You should also prioritize pages to test. How? Identify the best and worst performing pages regarding traffic and search engine rankings with tools like Ranktracker’s Website Audit.

2. What motivates and concerns your audience?

To clear up roadblocks in your visitors’ marketing funnel, determine the issues and driving forces behind their behavior. For example, if you want to boost sales on an eCommerce website, possible consumers’ concerns can be:

• free/paid shipping;
• the ability to return goods;
• the availability of various payment methods, etc.

3. What is your hypothesis?

The next step after the previous two stages is to formulate a hypothesis. Which aspects of your website should you test to give your clients better service? Specify what you plan to achieve and consider external factors, e.g., holidays, promotions, collaborations with influencers, etc. A case in point is boosting sales. A possible hypothesis can be the following: if I display more payment options at checkout, people will be more likely to buy via the preferred method.

4. Launch A/B tests

Now it’s time to transform research into practice. Create an A/B or multivariate (with several options) test for each hypothesis. Use the theory to guide any design adjustments while drafting your variant page. You can leverage dedicated tools to run the test and track its results, which we’ll discuss later.

Coming back to the previous example with payment services, you may integrate more options like Apple Pay, Google Pay, Samsung Pay, or even cryptocurrency. Divide the traffic in half so that one half sees the old design and the other one the new one.

5. Track and analyze the results

Did you manage to achieve your objectives set at the beginning of the test? Measure the test results, such as:

• a conversion rate;
• a bounce rate;
• an increase in revenue.

Determine the difference in conversion rates between the two groups and compare them with your average parameters. It will let you measure the real-world usefulness of the findings.

6. Implement the best alternative

Deploy the winner and ensure it’s the only option displayed on the website. You now have actual statistics showing what your visitors like on your website. If you haven’t seen much change, reevaluate the hypothesis and start over. Even perceived failures may lead to achievements. Learn from them and reconsider what will or won’t produce the outcomes.

A/B testing tools

As mentioned earlier, using an A/B testing tool will streamline the process. Your sales/marketing software likely has built-in testing capabilities, depending on what you pursue. These tools enable you to tailor your testing campaigns by analyzing user behavior using heatmaps and recording/replay.

But, specialized A/B testing systems provide more than just the bare minimum. For instance, many come with pre-set test scenarios. That’s why they are so popular, with around 75% of leading online retailers using such software.

The most effective A/B testing tools can speed up, scale, and help you develop your experimentation program. The two most typical types of solutions are as follows:

• Quantitative tools based on precise, numerical data: The best use of these technologies is to gather information in quantifiable, numerical form, such as:
  1. the number of people who utilized your website, app, or product;
  2. the proportion of users who became leads or customers;
  3. the frequency of button clicks.

Such solutions are VWO and Omniconvert.

• Qualitative tools that are user- and product-centered (PX): They combine user experience, user behavior, and product experience insights to discover why people act in a certain way. Hotjar, Usersnap, and CrazyEgg are some examples of such software.

It’s better to utilize both tools to get the maximum value for your website.

Best practices for effective A/B testing

Here is what you should remember when drafting your A/B testing processes:

• Test variations of a single variable at a time. Suppose you change the button color and the text size. How will you identify what influenced your conversion rates and to what extent? You need to take only one element for one test.
• Focus on relevance. A/B testing may provide insights into more relevant content for your target audience, attracting and converting visitors into leads.
• Develop a repeatable process. It entails using what you learned to run further tests and selecting whether to maintain, remove, or scale each test concept.
• Ensure your objective is clear. SaaS, B2B, and eCommerce businesses may have different goals: purchases, free trial signups, or lead form submissions. Your task is to find your own one.

Mistakes to avoid while A/B testing

The topic of A/B testing would be incomplete without discussing possible mistakes along the way. These are:

• Neglecting proper planning. You should research to establish a hypothesis. It will determine the elements to change, expected results, and priorities. A wrong assumption at the beginning may misguide the whole testing process. You should also follow your own path rather than rely on what worked for others. That’s why identifying your audience and requirements is critical.
• Testing multiple elements at once. Choosing several features for testing at a time is confusing and requires more detailed analytics. Set your priorities and test each piece step-by-step.
• **Determining incorrect test duration. **The final results will rest on various factors as you run the test on actual users. For example, you may have different conversion rates depending on the season, weekday, or promotion. That’s why a recommended test duration is one or two weeks.
• Not balancing traffic. You should not only divide the traffic evenly but balance it in terms of existing and new clients to get the correct conversion rates.
• Stopping after one test. You need evidence to support a hypothesis to continue testing it. That’s why you should collect diverse data to support the findings to be more confident in the thesis. It means conducting several tests, for example, for six months, to find the most suitable version.

Conclusion: Enhancing the website through A/B testing

Are you looking for ways to maximize conversions? A/B testing may help you with this task. Statistics show that it’s the second most-used strategy in conversion optimization after analytics. And 97.6% of companies report doing A/B tests. You can test various website components while relying on research to optimize the user experience. Thus, you make accurate predictions, leading to more sales and revenue.

We’ve discussed crucial steps to launch your first A/B test and possible mistakes to steer clear of. Choose one element to test, specify your goals, and learn from the results.

Also, employ A/B testing tools to make this process more manageable. They are versatile and powerful and vary in complexity, pricing, and the data type used during testing. So you can find what suits you best, whether you’re a small agency or a fast-growing company.