Over a million developers have joined DZone.

How to Test Your Chatbot

DZone's Guide to

How to Test Your Chatbot

What do you need to do pre-launch to prep your chatbot for the real world? And what should you do post-launch? Learn the answers to all these questions and more.

· AI Zone ·
Free Resource

Insight for I&O leaders on deploying AIOps platforms to enhance performance monitoring today. Read the Guide.

Chatbots are obviously a huge trend for 2017. Such AI programs are not just an opportunity for companies to make a big profit but also a great benefit for customers and prospects, who don’t have to wait for human assistance. The bot can service plenty of customers simultaneously, handling orders and simple questions right away.

Basically, a business must QA test its chatbot well so that it can bring real profit. Though having such a bot in your service arsenal may be a thoughtful marketing coup to attract IT-interested people, the interest will inevitably fade away if your bot can't handle what a customer really needs from your company.

Since AI chatbots have recently become rather smart, more and more companies have adopted them in their business. Nevertheless, “smarter” means more complicated coding, therefore more bugs and errors. You don’t want a crazy Tay bot who posts something like “kill all humans,” right? 

Give Up Treating Your Chatbot Like a Human

Last year summer there were many speculations that chatbots are rather stupid because they don’t deal well with Turing test. WTF, man? Chatbots are not a toy for lonely kidults — they are functional instruments to achieve a certain programmatic goal. Chatbots don’t need to act a real human but reply with the right answers and in the right time.

Sure thing, that would be nice (and highly recommended) to add some humanization features. For example, a bot may reply with the heart emoji once a caller says “I love you.” Things like that would be a good bonus for customers because they create a personal connection with your company. Your customer and your company will have a common history — it would be rather difficult for them to turn their eyes to your competitors. Emotion clearly rules both in life and in business.

Use Suitable Tools for Your Chatbot

Before the start, we must choose the instruments we will work with. Bots are not usual software, and their QA testing requires specific tools. How exactly should they work?

The main task for a chatbot is to understand the context of the conversation flow and properly deal with an issue a user needs to resolve. An adequate tool will deeply examine these features (especially as it concerns routine controlling) and provide a clear review that provides actionable insights.

Good testing tools would surely ease the whole process if they're implemented correctly. However, you can’t only rely on testing automation.

Basic Chatbot QA: A Bot Should Do Its Bot Job

So, where should you start? You should obviously check what the chatbot is specifically created for. You don’t want your bot to answer with the "right" answers to the wrong questions.

Let them handle the expected inputs and see the result. If something goes wrong, you know what to do since you or your coders have coded the reactions on those inputs directly.

This stage can be compared with the process of proofreading your Facebook status before you post it. Make sure your bot functioning well on the most basic tasks before you show your AI bot to more people. Note that it’s obligatory to test your bot on all channels that it’s been implemented for to avoid any issues with integration compatibility.

You may involve professional QA testers at this stage. The whole analysis would be even more efficient if the testing team works with you from the very beginning so that they can grasp more basic details of your project.

Pre-Launch: Chatbot Beta Testing

The best way to ensure that your bot will be launched ready to serve is to beta-test it. Once you are done with the basic QA and the chatbot works as planned, you need to open it to a wider audience. That must be a closed group of users. They will literally try to break your bot and then give you an account of what comes of this.

The beta tester will test the chatbot with unexpected inputs. These usually include slang, jargon, and colloquial language. Moreover, the chatbot will be treated like an entertainment and besieged with completely irrelevant inputs.

Every beta testing review is valuable since each individual treats the chatbot in a personal, unique manner. You need to consider how to deal with the users’ human behavior, which doesn’t fit any patterns, to improve your chatbot according to the considerations.

Quick tip: It’s helpful to define the main problems (i.e. no response; invalid response; response on the wrong topic; etc.) in the early QA testing stages. Then, ask your beta testers and users in the future to report with relevant tags. Voilà! You’ve got an ordered list of the main issues you need to work on. Such classification would make it much easier to operate the errors, set priorities, and find and fix critical bugs ASAP.

How to Get Beta Testers

Sometimes, you have no idea who you should ask to try out the beta version of your bot. Don’t worry! There are always certain ways to recruit people to pre-check your chatbot, even for free. Let me share with you the most common.

First of all, you may go with crowd-testing communities, inviting people there to test out out your new chatbot. The most popular resources are the TestMyApp subreddit and the Beta Family community, where innovation fans can try out your service and review it (in the first one for free, though it’s not so “crowded” there). The downside is that you can never be sure about the skills of the testers. Do they have enough analytical consciousness to plunge into testing deeply and properly? Who knows?

What about something more skill-oriented? In this case, freelance platforms will do. You can easily sign up on Upwork or Freelancer and search beta testers with the relevant skills. The resources’ deal protection ensures that the experts meet your deadlines and finish their work with a clear conscience (or else you're compensated). Nevertheless, freelancers may not be as reliable and organized as regular workers. 

Finally, if you want to get a real quality service, full-time outsourcing QA teams are waiting to assist you in every aspect. You will surely need to pay more than for the freelancers. Nevertheless, it’s quite fair to compensate higher rates to receive professionalism, systematic workflow, and adequate management. You’ll get 100% output: the QA testers will review the overall program, code, and algorithms and then provide you with the exact mistakes you've made along with advice on how to fix them. Some QA companies have developers in their state who do offer to fix all the bugs for additional fees.

Post-Launch: Real Users Reporting on Your Chatbot

After you've improved your chatbot according to the beta testing reviews, it’s time to launch!

Forget your fear of screwing up and give users the opportunity to report your chatbot if they think something’s wrong with it. Whether a user is concerned about the dumbness or just wants to advise you on usability, they must be able to do so right away within the chat. The chatbot gathers users’ complaints and concerns and sends this info to your QA specialists. Remember to thank your users for every report, because every thoughtful consideration makes your AI customer assistant a little better.

Once the chatbot is accessible to everyone, here even more unexpected inputs. You must be on the ball and react promptly to make the conversation with your AI rep smarter, more interactive, more human-like, and possibly amusing.


These points will help your virtual customer assistant work perfectly for your clients. If you have any further questions, feel free to ask me in the comments below. And hey, and keep sharing if you consider this content helpful — let’s do our part to make AI a little bit better and anticipate the future we want so much!

TrueSight is an AIOps platform, powered by machine learning and analytics, that elevates IT operations to address multi-cloud complexity and the speed of digital transformation.

chatbot ,bot development ,ai ,machine learning ,tutorial ,qa

Published at DZone with permission of

Opinions expressed by DZone contributors are their own.

{{ parent.title || parent.header.title}}

{{ parent.tldr }}

{{ parent.urlSource.name }}