Improve Customer Experience Through A/B Testing Customer Service

In the current era of a competitive business world, customer experience is vital in ensuring your business’s growth, development, and sustainability. Statistics are now clear that customer experience is the key factor in keeping clients and growing revenues.

These facts show how important customer experience is, and it should not be taken lightly in any business. To deliver a shopping experience expected by your clients and surpass it, you need to create a/b customer service program.

Throughout this article, we will outline how you can improve customer experience through a/b testing customer service. Read on to learn more about a/b testing and its place in delivering effective customer service.

What is a/b testing?

Usually, when marketers create product pages, landing pages, design a call-to-action, or write email copies, it can be appealing to use your instincts to predict which area will drive more conversions and sales.

However, making decisions based on a feeling can be quite detrimental to the expected results. Instead of relying on assumptions and guesswork, it is much better to run an A/B test to develop a clear picture of your business drivers.

By definition, a/b testing customer service is the process of showing two similar variants from the same website to different types of visitors at the same time to compare which part of your business will improve your customer experience and drive more conversions.

In a digital retail space, the number of visitors to your e-commerce website equals the number of opportunities needed to expand your business by getting new clients and developing relationships with existing ones.

Business needs their visitors to take action on their sites (also known as conversion), and the rate at which this is achieved is known as conversion rate. The more optimized your sales funnel, the higher your conversion rates. And one of the most practical ways to optimize your funnel in digital marketing is via a/b testing.

Generally, with a/b testing, the variant that provides higher conversion rates is taken as the winning one and can help you optimize your funnel appropriately. The conversion metrics vary depending on the type of website.

For instance, in an ecommerce website, it can be the provision of a service or sale of a product, while in B2B, it may be the nurturing qualified leads to the business.  This type of testing is one of the key elements in overarching the conversion rate optimization process.

With a/b testing, you can get quantitative and qualitative customer insights, apply them to understand your visitors and optimize the conversion funnel based on the received data.

Reasons for performing a/b test

Suppose B2B businesses are currently not happy with unqualified leads. In that case, ecommerce stores are struggling with a high rate of cart abandonment. On the other hand, publishing and media houses also are dealing with low viewership rates.

A/B testing customer service

Author credit: By Philip Forrest – The International Customer Service Institute, Attribution,

These conversion metrics are usually affected by various common problems including, drop-offs in the payment page, leaks in conversion funnels, etc. Here are the reasons you need an A/B testing to help you address these challenges effectively.

  • Solve visitors’ problems

Visitors come to your website to seek solutions to the problems they have in mind. This can be to make a purchase, enquire about your services or products, and learn more about the desired topic, or just browse your site.

Regardless of their goals, visitors may experience some pain points during their interactions with your website to achieve the desired goals. This might include a hard time finding the CTA button, request a demo, or request help with a confusing copy.

If customers are unable to achieve their goals, it depicts a poor customer experience which increases friction between the business and customers hence affecting your conversion rates.

Use the insights collected by customers’ analysis tools like Google Analytics, Heat maps, and website surveys to address customer’s pain points. This analogy is valid across all industries, be it travel, SaaS, ecommerce, or education.

  • Minimize bounce-back rates

Bounce back rate is an important metric used to gauge the performance of a website. There are several underlying reasons for a high bounce-back rate like expectation mismatch, availability of too many alternatives, and so on.

Since there are different sites serving different purposes to different clients, there is no one-size-fits-all approach to reduce bounce-back rates. One of the proven practical ways is to do A/B testing.

With A/B testing, you can perform tests with various variations in your website until you find the most appropriate version and optimize it effectively. Doing this will help keep your visitors on the site for long, increases their experience, and eventually reduce bounce-back rates.

  • Get a better ROI from the existing visitors

Since marketers have come to terms with the facts about the expensive lead acquisition, A/B testing allows you to get the most from your existing traffic without spending too much on getting new traffics.

With A/B testing, you get high ROI even from the most little change on your website by optimizing the area that is the most conversion driving factor.

  • Make low-risk changes

Make slight incremental modifications to your website pages using A/B testing instead of changing the entire website. Doing this will reduce the risks of compromising the current conversion rates on your website.

A/B testing customer service

Author credit: By Images –, CC BY 2.0,

Doing A/B testing allows you to direct your resources to provide maximum results with minimal changes leading to increased ROI.

One of the typical examples maybe product description modifications. You can do A/B testing when you want to update or remove a product; however, you may not know how your clients will react to the changes.

Another practical example of a low-risk change is introducing a new feature change in a product or service. Before getting the new feature introduced, running an A/B test on the new component can precisely predict how it will perform once it is included on the web page.

  • Get statistically proven improvements

A/B testing is a totally data-driven approach without the room for guesswork, instincts, or gut feelings. You can spot a high-performing and a low-performing variant entirely based on statistically significant improvements from various metrics like the time spent on a page, click-through rates, Cart abandonment, demo request, and so on.

  • Redesign your website profitably

Redesigning a website may range from a small color tweak to a minor text change on the CTA button to completely rebuilding your web page. The final decision on implementing one version instead of the other needs to be based on data-driven A/B testing.

Do not stop the A/B testing process before finalizing the design. Once the new version is live, run the test on other web page components to ensure that visitors can view the most engaging version.

How to do A/B testing

In any given marketing campaign, A/B testing provides a systemic way of identifying what works best for your business and what doesn’t since most marketing strategies aim to generate traffic to your website.

Practical A/B testing can make your marketing efforts more rewarding by addressing crucial problems that need optimization backed by data-driven insights. The test is progressively evolving into a continuous and more structured action instead of a standalone activity once in a while.

It needs to be done via a well-outlined CRO process. In general, A/B testing involves the following steps.

  1. Do research

Before setting a test plan, one needs to do thorough research on the current performance of their websites.  You will have to gather details on which pages drive more traffic, how many visitors are coming to your site, and the different goals assigned to each web page.

The perfect testing tools at this stage include quantitative analytics tools like Mix panel, Omniture, Googler analytics, etc. These tools will come in handy in identifying the most visited pages, pages with high bounce back rates, and ones with the most time spent.

After this, you will need to do a qualitative aspect of your website using tools like Heat Map, which is among the leading technology in checking web pages where users spend more time or their scrolling habits.

You can also use another insightful tool called website user survey, which directly links your website and the end-users.  This tool has the potential to highlight factors that might have been missed in average data.

Moreover, you can get qualitative insights from session recording software that gathers visitors’ behavior information to identify breakdowns during a customer journey. Coupled with form analysis surveys, session recordings can be helpful in finding why a visitor does not fill out a particular form.

As it can be noted, qualitative and quantitative analysis can help you plan for the next move in the process, providing actionable insights for the next step.

  1. Observe and create a hypothesis

Get closer to your business objectives by formulating research observations and creating a data-backed hypothesis aiming at increasing conversion. If you don’t have these, your test campaign will lack direction.

The research tools discussed above will only help you collect visitors’ behavior insights. It is then squarely on you to analyze and synthesize these data. The perfect way to utilize these data is to keenly analyze every bit, make an observation and then draw website and user information to formulate a practical hypothesis.

Once the hypothesis is in place, test them against different variations like its effect on macro-goals, the level of confidence you have in it, and how easy it is to set up.

  1. Create variations

Based on your hypothesis, the next step of your testing campaign should be creating a variation and A/B test it against the current version as a control. A variation is another version of the existing version having changes you would like to test.

You can run multiple variations against the control to identify which one addresses your concerns, be it generating traffic, conversions, or retaining clients. Ensure the hypothesis is based on what works best from a visitor’s perspective.

  1. Run the test

To start with, there are four types of testing methods, namely: multipage testing, Split URL testing, Multivariate testing, and A/B testing you can perform on your site for a specific target.

Once you have decided on which type of test and approach you want to follow, you can proceed with the test and wait for the specified time to receive data-backed results.

However, regardless of the method you choose, keep in mind that the results will only be determined by the statistical accuracy and the method used. For instance, the duration and timing of the test need to be on point for accurate results.

Calculate test duration knowing your average site visitor, current conversion rates, number of variations including control, minimum expected improvement in conversions, and so on.

  1. Result analysis and deployment

Though deployment is the final step of your test campaign, result analysis is equally fundamental. Since A/B testing needs constant data gathering and assessment, it is in this stage that your test result unravels.

Once you are done with the test campaign, analyze your results keeping in mind metrics like your confidence level with the results, percentage increase, expected impact of the outcome, direct or indirect, etc.

After assessing these numbers and ensuring the test is successful, deploy the winning test result straight away. In case the test is inconclusive, learn from the insights gained and apply them in your subsequent tests.

How to improve customer experience through A/B testing customer service

A/B testing is a technique used to identify which campaign performs more than the others on your marketing inventory. This testing campaign can also be used to check landing pages, ad copies, or even call-to-action click buttons that perform best.

Doing this is easy and straightforward- website managers pick one or multiple variations of the components they need to optimize ad copies, landing pages, etc., and make them available to a random element for the web page and website visitors within the same demographics.

A predetermined metric is tested, and a variation with the worst metric result is discarded, and a better-performing one is adopted.

A/B testing is also a helpful technique to gauge customer service experience and satisfaction rates. Let us have a look at how we can improve these factors through A/B testing customer service.

  1. Tracking Net Promoter Score. (NPS)

NPS is one of the best methods to evaluate and improve customer experience and satisfaction rates. However, the duration and timing of the tracking can affect your ratings. For example, asking for feedback soon after a customer completes a purchase could trigger higher ratings than enquiring soon after making a call to your customer support.

It is advisable to differentiate NPS scores generated from customers at different stages of their purchase journey and track them independently. It is also easy to identify hold-ups in providing an excellent customer service experience. The aim should be to fix CX problems at any stage of the customer purchase journey.

  1. Implement live chat

If you are operating an online store, a live chat feature can be a handy in helping clients during their shopping journey.

There are two methods of implementing a live chat feature on your website. You can link to a live chat page on your website or simply activate a live chat message immediately after a visitor enters your page.

In the former scenario, a client cannot notice the option unless they are seeking a support system to get in touch with your business. All the same, both the methods have their pros and cons you need to know about.

When you actively trigger a live chat option, you allow your customers to interact with you more frequently hence keeping them hooked to your website for long. However, this could be distracting and potentially bring down the conversation.

In a different scenario, clients do not usually get distracted by a live chat message though the opportunity can be missed by a customer who bounced away very first. Measuring the conversion and engagement from the two alternative variations should give you an insight into what works best for you.

  1. Apply scientific methods

Astrophysicists and anthropologists apply thorough testing procedures to get a clear insight into whatever they are trying to approve or disapprove. However, they simply create enough variables and minimal resources and time not to be overrated. Web-based tests need to be different.

  • Begin with a direct question and develop a hypothesis.
  • Do the test without changing it until a data-backed number of users is identified.
  • Test various versions simultaneously to control external variables.

So, a simple target of significant newsletter sign-ups may lead to the formulation of a hypothesis that “people are not seeing our fill-in form.” So you have a focus on what to run a test for and the predetermined results.

  1. Optimize phone support

According to an American Express survey, almost half of customers hang up their phones if they cannot speak to a real person. Setting up phone support is a significant component of any business, especially an online store.

Anything your customer support says or does during an interaction with clients always determines customer satisfaction rates and directly affects any future engagement with your business. A well-trained customer care team will follow predetermined guidelines to understand customers’ concerns and helps solving them.

One possible way of approaching this is by developing different script variants and address some of the most common customer requests.

For instance, if you are running a clothing store, you can set variations from customer complaints like “loose fittings,” “wrong size,” damaged apparel, etc. Then test these variations and measure their effectiveness to address the concerns and improve NPS score ratings.

CX and customer satisfaction management are continuous processes; hence testing best performing features and scripts is also a never-ending procedure.

  1. Design a process of implementing the best-performing scripts

After identifying the best-performing variant, please work with your team of developers and implement it in the system. Generally, suppose you discovered a way of increasing your conversions by only 5%. In that case, you should not hesitate to include it in your operations for better results.

Doing this also provides you with insights for future tests and prevents subsequent performance problems from affecting the implemented script.


From contents, devices, positions, color, and even navigations, the options for marketers to improve customer experience and satisfaction are bewildering. However, A/B testing various web pages and components provide statistically significant results than most of the available options for improving customer service.

A/B testing is the method of comparing one or multiple components or variations to identify the best performing in terms of preset expected results.

Therefore A/B testing customer service aims to find which section of customer care needs improvement for effective customer experience and satisfaction.

Fortunately, achieving a satisfactory customer experience through A/B testing customer service is relatively an easy task. Website admins and developers pick one or several variations and run the tests against an existing variant or control, making them accessible to random pages and components that are visited most.

To achieve the best customer experience using A/B test customer service, you need to do a couple of things like tracking the net promoter score, implementing live chat, optimizing phone support, and designing an implementation plan using a scientific approach.