Designed to enhance the overall customer experience, AI-powered chatbots are widely used across industries, including financial services and insurance, telecommunication, Ecommerce and healthcare. Chatbots today are experiencing tremendous growth, and this is only expected to continue. The global chatbot market is projected to grow at a compound annual rate of approximately 25% through 2026. While such tools carry great benefits for businesses, simply introducing technology for technology’s sake is not the answer – there is a need to take a more strategic approach. Here are several best practices to consider when developing and deploying AI chatbots, for the ultimate customer experience.
1. Avoid empathy overload
As AI continues to increase in prominence and insert itself into everyday life, researchers are working to better comprehend the subtleties of human emotion, and developing AI systems that attempt to accurately mimic or mirror them – this is known as empathic AI, or synthetic empathy. Have you ever asked Alexa if she is having a good day, and she responds with ‘hmm, I don’t know how to answer that?’
Unlike engaging in friendly banter with Alexa, though, the purpose of an AI chatbot in customer service is to swiftly resolve issues and provide answers, so endowing it with too much humanity may end up annoying the customer. Too often, synthetic empathy simply adds unnecessary friction and winds up slowing down the resolution of a problem. Why rid the AI of its superpower – which is to quickly and effectively get things done? My flight was canceled, I don’t need an apology from an AI (that is not a human, as I am aware), I just want to get rebooked on the next flight and move on with my day. Achieving the right balance of both the human touch and the efficiency that AI allows is tricky, yet crucial.
2. Let your chatbot become a customer advocate
“Until you understand your customers — deeply and genuinely — you cannot truly serve them,” said Rasheed Ogunlaru, Author of Soul Trader.
AI chatbots are information sponges. They can learn and retain information about you, your likes and dislikes – your travel history for this past year (your favorite and not-so-favorite aspects). They can suggest your next great read, based on books that you recently read and enjoyed, or alert you when a table is available at your favorite restaurant. In this sense, AIs are our strongest advocates. They can also prevent us from making bad decisions – an airline may be having a seat sale next month and is headed to your preferred destination. Instead of booking today, an AI suggests to this super loyal customer that a sale is approaching and it may be best to wait. This level of detailed insight – the deep knowledge base that the AI has formed – results in an enhanced customer experience, which in turn leads to improved customer satisfaction, advocacy and loyalty. Design AI chatbots that get to know and understand your customers on a deep level and then proactively advocate on their behalf.
3. Concentrate on strategic conversational design
Humans are complex creatures, as are the languages we speak. Consider the English language itself – full of oddities, silent letters and seemingly identical words with vastly different meanings (a minute is 60 seconds, but something minute refers to a very tiny object). Consider these nuances, when in conversation with an efficient and highly technical AI chatbot, when attempting to get a refund from an airline for a canceled flight.
The solution to this? Keep it simple, and focus on the diverse needs of both humans and machines. When designing conversations for a virtual world, ensure the dialogue between the AI and the customer is natural and persuasive, and, above all, is helpful to the customer. Ensure that prompts are clear and compelling, for instance, pose multiple questions, one at a time (‘do you prefer an aisle or window seat’)? Using simple acknowledgements is also recommended, in order for the conversation to flow more naturally (‘got it, let me see what else is available’). Such a technique also makes the customers feel that they are being listened to, and their concerns are being heard.
4. Create chatbots not for the sole purpose of replicating human behavior, but to really take advantage of the true power of AI
The Turing Test has been regarded as the go-to guide for developing conversational bots – in 1950, mathematician Alan Turing proposed that, if it can mimic human responses under certain conditions, then the computer can be said to be intelligent. As mentioned above, the primary goal of modern AI is to solve problems. Therefore, when building chatbots, we need to focus on the end goal, which is efficiency, not necessarily coming off as a human. After all, a fast and accurate resolution to their problems, in a friendly and respectful manner, is what customers desire the most, not being fooled that they are engaging with a human and not a machine. Design AI chatbots with this in mind.
We also need to be cognizant of the differences that exist between the two – that AIs will make a different set of mistakes than humans do, and will subsequently learn from these mistakes differently. This means we need to have different measures of success for each, as AIs and humans each have their own distinct qualities and defining features. For an AI for instance, such measures may include its ability to decrease resolution time, and to handle an infinite number of tickets concurrently.
5. Recognize that AIs can’t solve everything, and always have a back-up plan in place
Will an AI be able to comprehend all of these complexities, the ins-and-outs of the human language? Probably not, and that’s ok. As intelligent as they are, AIs can’t do it all, which is why offering an escalation path to human agents, based on topic, customer profile, or when a customer asks to converse with one – is key. If a customer is growing increasingly angry or frustrated, for instance, a human agent may need to intervene. Similarly, it may need to do so if the AI is unable to grasp a certain turn of phrase. As mentioned, the goal of the AI is not to replicate human behavior, but to work alongside human agents to solve customer problems quicker and more efficiently.