Artificial intelligence has revolutionized the face of customer service worldwide – especially during a pandemic – with artificial intelligence chatbots and other virtual agents that are at the center. The growing need to provide a streamlined holistic customer experience is the primary reason why more and more companies are aggressively investing in modern technology to improve their customer support. However, traditional, people-based customer service methods proved to be laborious from both the employee and customer perspective.
While customers (especially millennia and gen-z users) were tired of pressing buttons to take advantage of different services, service managers also felt that answering the same questions repeatedly was monotonous. That’s why most organizations have recently decided to move to virtual agents that use artificial intelligence, ML, and other tools to develop and deliver customized responses to different types of customer requests and queries.
However, complete dependence on such virtual agents is not yet possible, and recent studies have revealed that most customers are not very happy with their experience with bots.
Customers have two big problems to deal with chatbots:
1.Before making critical decisions (for example, by purchasing a highly participatory product), customers often look for answers to complex brand questions, which usually involve several follow-up questions. Robots do not deal with this category of questions – which take longer to resolve depending on the degree of complexity or the amount of information.
Virtual agents either give up and refer the client to human service agencies or show links through which clients can wade in to resolve their issues themselves, which they may have already tried. Therefore, it can be concluded that bots are not able to identify tasks that customers have already performed through other channels on the website, and this is one reason why bots may fail to handle complex customer issues.
2. Another area where virtual customer service representatives do not work well enough is an accurate understanding of people’s feelings. We cannot ignore the fact that even the most advanced artificial intelligence tools cannot reproduce complex human emotions. With the recent integration of opinion analysis, companies have been able to solve this problem to some extent. Chat chat robots, supported by opinion analysis technology, can determine the emotions and tones that are hidden behind a customer’s message (voice or text) and, accordingly, frame and give the right answers.
However, moods are highly subjective in nature and vary from person to person, which often impairs the accuracy of the analysis of opinions. This tool cannot be used to understand emotions such as irony, sarcasm, humor, etc., which leads to the customer leaving the organization and creating a negative impression of the brand. Case: Indigo’s (unintentionally) funny response to a disgruntled customer’s tweet full of sarcasm. (For the inexperienced, you can read about the fiasco here).
Such problems require organizations to use a combination of human and virtual customer service agents. While most of them would like to talk to chat bots to get their problem resolved quickly, customers also need to know that human agents are available if their queries are too complex to solve chat bots. There should be a logical transition from robots to human agents. The handover must be scheduled so that it occurs as soon as the bot is unable to resolve the customer’s problem a second time.
The HR representative should also receive a summary of any tasks the user has already performed while chatting with the chatbot in order to be updated and removed. This avoids repetition and thus saves time. This kind of practice assures customers that the company or brand really cares about them. An example of an effective chatbot could be one whose problem-solving ability is clearly defined for the customer before he or she starts using it. If chatbot makes it clear to the customer at the outset that in the event that the customer is unable to resolve the issue, they will be automatically referred to employee representatives, it can earn the customer’s trust. Therefore, the customer is more likely to be disappointed by setting the right expectation.
Customer support is the part where a company has more control in creating a positive brand image in the minds of customers. By designing effective bots and training service personnel to communicate with users in a way that is fully consistent with the brand’s overall value proposition, the company is able to retain satisfied customers and reassure them to continue using its services.