Irrespective of the type of industry and scale of business, chatbots have become an integral part of businesses- be it a text or voice chatbot. This is why chatbot development has become important to resolve issues while delivering tailored user experiences. Though there are various standard development platforms available, there are no standard platforms to conduct chatbot testing. To conduct chatbot testing successfully, here we discuss various aspects of chatbot testing.
What Exactly is Chatbot Testing?
The chatbot application testing process isn’t the same as conventional application testing. Chatbot development is based on the usability and context of business operations. Also, the chatbot is meant to resolve issues based on user inputs and deliver a realistic human experience. As no two human interactions are the same, a chatbot has to be tested based on how it interacts with many different users. Though based on the client’s requirements features of a chatbot are varied, but the basic communication flow remains the same and this is one of the key components of the chatbot testing process.
How to Prepare for Chatbot Testing
Before testing a chatbot, it's important to know the answer of each of the questions listed below.
- Is a chatbot text- based, voice-based or both?
- What data will the chatbot need access to?
- Is the chatbot integrated with other messaging platforms?
- What is the core challenge the chatbot will need to solve?
- What chatbot architecture was used to build the chatbot?
- Is the chatbot improving consistently? (Check user feedback in the form of surveys taken after each chatbot interaction)
Key Considerations for Chatbot Testing Process
Purpose of the User Interaction
Any application is built to achieve specific business requirements, and this is called the intent of the application. Testing teams should make sure the application fulfills all of its intents. Similarly, check various chatbot application intents. There are many different intents for one chatbot. So, develop test cases to input various intents and study chatbot responses. For example, you may take many sentences with the same meaning to make sure the chatbot provides the right answer.
Response to Casual Conversation
Even in professional conversations we often use casual phrases. To make sure chatbots are friendly in its responses and generates better user experiences, develop test scenarios to check if chatbot responses are dynamic and don’t behave like a customer care IVR (Interactive Voice Response) that gives standard responses. The role of the chatbot should be to provide correct answers as naturally as possible.
Response to Undefined Inputs
This test case is aimed to check how the chatbot responds to unusual user questions in the user interactions. For example, the chatbot may work perfectly for standard questions, but there may be times where unusual questions are asked out of context. This might be a place to program to respond with "I don't have the answer to this question." Or a response that reiterates the purpose of the chatbot.
Navigate Through a Conversation
Check whether the chatbot understands when the user wants to skip some questions or go back to previous answers. Develop such test scenarios to validate if the chatbot grasps user needs in an interaction.
Level of Emotional Quotient
User experience is the key aspect to chatbot success. So, the chatbot should predict the emotional state of the user and respond to the user accordingly. For example, chatbots are often used for customer service. Customers are often reaching out to companies when they are upset or confused. Chatbots should be able to manage the emotions of the customer by responding appropriately.
Locate Entities to Understand User Intent
When a user converses with a chatbot, it detects the user needs based on keywords, often called entities. These keywords are stored in the knowledge base during chatbot development. Make sure to test all possible conditions using numerous sentences and verify whether it can reply precisely.
Response Time
Validate the speed at which the chatbot answers a user question by making note of the amount of time it takes for the chatbot to respond. Response times should be fairly quick for general questions.
Conclusion
Chatbots adopting various artificial intelligence capabilities, like machine learning, deep learning, artificial neural network concepts and so on. Chatbot are no longer just question and answer type machines, they have evolved to perform various intelligent tasks and are becoming the voice of business processes or system in the business. So, chatbot testing process has to be more agile and testers have to develop innovative ways to test chatbots.
