The Definitive Guide on Chatbots A/B Testing

Every time you are surfing onto a new website you must be getting those ‘Pop’ sounds where a bot starts talking to you out of somewhere. In the current time, the chatbots have created much hype in the business world by improving customer experience. Chatbots are used to bring real-time tangible business results by generating more leads and sales to gain customer trust.

The chatbots are basically running according to the trends, marketing sales and support strategy by running experiments on them which can offer several benefits. Hence, you can improve your ROI from the channel with the A/B testing as native functionalities allow businesses to run experiments to figure out the best performing messaging, sequences and triggers.


The right optimization process is crucial for running meaningful CRO experiments for your chatbots. Here’s how you can take a leap.

Why do you need A/B testing for your business chatbot?


Basics of all, select the right metrics before carrying out any experiment on your chatbot. When you want to increase your sales with the help of Chatbot then your metric can be the number of leads who-opt in after a successful chatbot interaction.


Alternate to this, you can also use chatbots for boosting sales by changing your metric to the number of trial leads which improves engagement score because of chatbot interaction. After you have identified your correct metric for better optimization, you can begin to work on your chatbot experiment.

Crafting the Hypothesis

Similar to another website or mobile app experiments, chatbot experiments begin up with a very clear hypothesis. For instance — Magoosh which is an online test preparation organization decided to run an onboarding experiment with some clear hypothesis of sending welcome onboarding message when they log-in to the trial customers to make them purchase the premium accounts in the future. Magoosh performed this test to check if they increase conversion rates or not. Here, hypothesis concerns with some specific gains which you want to achieve from your chatbot.

Creating different experiments

Just as you do A/B testing or CRO experiment, you need to create your chatbot experiments. In this phase, you need to translate your hypothesis with a set of changes to test. If you made hypotheses to become more popular chatbot for getting better results to your marketing team. You will have to see what elements of your chatbot are branded in a better way in order to tone or simplify the visual interface.


When opting for the A/B testing, you need to focus on every minute detail of your product as it may happen that the element that seems normal to you might not be appropriate for your users. Therefore, creating different experiments will help you to analyze which prototype suits the best for your product or what features are required to focus more on.

Learn from Experiments

After you are done with your experiments, it is the time to analyze your findings. Looking at the outcomes for any optimization experiment; you need to check out which technique works the best to achieve your goals. When you are going for a split-test or A/B testings, it is essential to know which strategies are suiting you the best for optimization and boosting your sales. This can be achieved with the help of the A/B testing as it helps you to enhance the customer experience.


Your hypothesis becomes validated and changes bring about a positive impact on the numbers. The results vary according to your users and sometimes your hypothesis gets rejected by bringing negative impact on your conversion rates. Hence, try to learn from your various tests as it helps you to know more about the likes and dislikes of your customers.

Wrapping up!

If you are a tech-savvy person then you can definitely take your chatbot experiments to a whole next level by testing it with the content you feed your chatbot for proper functioning. You can also try your hands on some different learning algorithms for performing these tests. Chatbots are here to stay for a long time to improvise customer experience and with the rise of machine learning skills, they are going to act as the first touchpoint with large segments of your prospects. Keep Learning!


About the writer: Charles Richard works as a Business Analyst at software development company based in London. Apart from his daily job Charles likes to explore e-commerce trends and best practices. He has published authorship bylines in many major publications, including Quirks, Search Engine Watch, YourStory and more.

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