Speaker

Meera is Tech Lead – QE at Litera. An enthusiastic QA professional with over 8 years of experience. I have experience in various testing functions like Functional testing, designing automation framework, desktop application testing, API testing etc. I am interested in exploring various tools and technologies for automation frameworks.

Title: Ai-chatbot-testing- Best practice  and strategy

Today, businesses leverage advanced technologies like Artificial Intelligence (AI), Machine Learning (ML), Robotic Process Automation (RPA), and Natural Language Processing (NLP) to develop software bots and chatbots. These AI-based conversational bots interact with customers in real-time and enable human-like interactions between systems and humans. For businesses, these AI conversational bots continue to be a faster mode of communication with their customers as it delivers a greater customer experience (CX). 

What is an AI Chatbot? 

A chatbot is a text or voice-based interface that is built and deployed on the website or apps to simulate a conversation with users and seamlessly support users. These are self-learning bots and are programmed with AI, NLP, and ML technologies. There are many benefits with these bots; they can automate tasks, understand words and phrases, frame appropriate responses, and can learn from the received inputs. Thus, these conversational bots are effectively being used to replace a repetitive task that a human would do. Moreover, AI conversational bots differ from traditional rule-based bots and can understand language outside pre-programmed commands. 

Important chatbot testing concepts? 

Chatbot provides 7 broad categories for testing: 

  • Personality: Does the chatbot have a clear voice and tone that fits with the users and with the ongoing conversation? 
  • Onboarding: Are users understanding what is the chatbot about? and how to interact with him from the very beginning? 
  • Understanding: Requests, Small talk, idioms, emojis… What is the chatbot able to understand? 
  • Answering: What elements does the chatbot send and how well it is doing it? Are they relevant to the moment and context? 
  • Navigation: How easy is to go through the chatbot conversation? Do you feel lost sometimes while speaking with the chatbot? 
  • Error management: How good is the chatbot dealing with all the errors that are going to happen? Is it able to recover from them? 
  • Intelligence: Does the chatbot have any intelligence? Is it able to remember things? Uses and manages context as a person? 
  • Response time: Customers want fast responses, faster responses can keep customers more engaged with bots.

Chatbot Testing Tools

Since chatbot testing needs to offer a pleasing user experience to anyone visiting the website, working on the various domains and practices needs access to the right tools. Here are a few good tools that you may consider for your chatbot testing project:  

  1. Botanalytics   
  2. Chatbottest   
  3. Dimon   

Chatbot Testing Techniques 

  1. Industry Standard Cross-Validation 
  2. Blind Testing 

How Can You Create a Perfect Test Set Without Current Data?   

The testing of interactive AI and implementation entirely depends on the data set used. Therefore, certain rules can be followed by the person developing the test cases to ensure optimal results:  

  • Scenario-based test sets reflect on possible scenarios that anyone using the website may encounter. This usually involves intent-based questions.   
  • The detailed descriptions offer solutions to the user interacting with bots while incorporating user type, query expression, and difficulty.   
  • Align questions and interpretations in a systematic order.  
  • Offer well-phrased and value solutions to the corresponding queries.   
  • Have the best data source to answer questions asked by users in real-time.  

Common Chatbot Testing Scenarios That You Must Necessarily Consider 

  1. A chatbot should be loaded with the website on which it needs to be implemented.   
  2. The chatbot should load clearly when a user lands on the website, either with pop-up or sound.  
  3. The chatbot should greet the user based on their time zone.  
  4. If an already registered user visits the website, the chatbot should call them by name.   
  5. The chatbot should answer queries using the name of the user in between the chat.   
  6. If required, the chatbot should ask for the contact details of the user.  
  7. It should recognize male and female users well.   
  8. The chatbot should identify possible spelling mistakes.  
  9. The chatbot should understand currencies and numbers.   
  10. The chatbot should verify contact, date, and time for programmed format.   
  11. The chatbot should be able to deal with confusion caused due to intricacy.   
  12. The chatbot should respond well to pasted text-based queries.   
  13. The chatbot should store conversation history and forward the same to the repository if trained to do so.   
  14. Chatbots should perform well for simultaneous queries asked from different users at the same time.  

Conclusion 

Since many chatbots are designed to learn and will update themselves continuously, it’s important to keep testing it to deliver a quality experience every single time! You can have a weekly, monthly or quarterly testing to regularize the checks. Communicate with your chatbot team and let them know that you must see how the bot is responding every now and again.