A recent webinar explored the value of automated chatbot testing.
Businesses can take their customer experience to the next level with technology such as voice assistants, chatbots and conversational AI. In fact, Mordor Intelligence estimates that the chatbot market will grow 34% and reach $102 billion by 2026. But even while organizations are exploring chatbots to improve customer interactions, it’s not uncommon for them to overlook quality assurance. Testing conversational AI is more complex than testing traditional software, and organizations need to be able to continuously test without overwhelming employees with repetitive tasks.
Christoph Börner, senior director, digital at Cyara, recently presented a webinar that explored these topics and the value of automated chatbot testing. His insights will help you understand why chatbots fail and what you should be testing to ensure greater success.
Avoid These Common Mistakes That Companies Make With Chatbots
“Developing bots is not hard. With the right tools you can get something up and running pretty quick,” Börner said. Testing conversational AI is what presents many issues. “A test engineer will face many new challenges,” he said, which include learning basic machine learning concepts, learning a new set of vocabulary and understanding training data.
Börner added that in his experience with clients, lack of knowledge is the most common challenge in assuring the quality of their conversational AI. Organizations often throw their IT department into this space without considering if they have these specialized skills yet. Without giving your talent the resources, technology and knowledge to develop a bot effectively, it won’t perform to the level you want.
Why You Need to Test Bots
Developing a bot is just the first step. If it doesn’t function correctly, companies lose out on the many benefits and risk negative consequences such as revenue loss, reputation loss and extra costs needed to fix the problem. Ultimately, Börner said, ”bots are software, and software needs to be tested.” While this sounds like an obvious statement, he added that it often surprises clients and makes them think harder about the importance of testing. Developing a bot is just the first step. If it doesn’t function correctly, companies lose out on the many benefits and risk negative consequences such as revenue loss, reputation loss and extra costs needed to fix the problem. Ultimately, Börner said, ”bots are software, and software needs to be tested.” While this sounds like an obvious statement, he added that it often surprises clients and makes them think harder about the importance of testing.
But before beginning to test, companies need to ask themselves exactly what users expect from their bot. Börner identified four major topics that customers want in conversational AI: accurate answers, great user experience across all preferred channels, the highest security standards and fast response times.
Companies should also consider the common reasons why bots fail. Customer inquiries made with typos can throw them off. Some bots are only capable of answering simple questions, which is problematic when they also aren’t good at handing off the request to a human. Finally, many bots are just too broad in scope. “I see a lot of bots trying to handle too many things at once and lacking proper human escalation protocols,” Börner said.
How to Test Your Bots
Testing should be done through automation rather than manually, Börner said. People simply can’t keep up with the amount of hours and work it takes to thoroughly test a bot. For example, every time a company makes a change in how the conversation flow goes, it’s necessary to test everything all over again (regression). This could mean hundreds of hours of manual work a week on a regular basis, with employees only being able to test a small percentage of total conversation flows.
There are six types of testing that must be done: regression testing, NLP testing, end-to-end testing, security testing, performance testing and production monitoring. Each of these have different purposes, from testing every potential conversation flow to making sure there’s a seamless experience on every platform to seeing how well bots behave under extreme stress conditions. The key enabler here is automation, which allows organizations to do all types of testing needed and cut back on hours of manual testing. For example, Börner said, Cyara Botium can automate up to 85% of conversational AI testing.
Begin Testing Your Conversational AI Now
Many current trends indicate why companies should focus more energy on testing their chatbots. Börner predicts that as more companies invest in the metaverse, the more they’ll focus on improving and perfecting their bots – a key feature for the metaverse to function properly. And even companies who aren’t yet putting their money here have reason to put more energy in chatbots. With more customers relying on online shopping and wanting quick answers from chatbots, organizations need their bot to make a good impression on customers so that they don’t develop a negative opinion of the brand.
Solutions like Cyara Botium can constantly monitor bots and make sure that they respond as intended – for all types of chatbot testing. The benefits of this are invaluable to today’s companies leveraging their investment in Conversational AI to provide a positive customer experience and build a good reputation for companies and the services they provide. To learn more about the importance of testing and the capabilities of Cyara Botium, check out the webinar below.
Watch the on-demand webinar now at cyara.com.
