Healthy customer relations are an outcome of efficiently managed customer support channels. Leading enterprises now use chatbots on their websites and mobile apps to augment their customer service efforts. Chatbots are effective at handling routine customer interactions in real-time to improve customer relations, making them an ideal choice for CRM.
Early chatbot applications were limited in their scope. However, recent machine learning and natural language processing (NLP) advancements have increased their capabilities with new innovative features. A growing number of businesses now handle a significant volume of customer interactions by integrating chatbots into their CRM systems. This blog post explores the different ways in which the conversational features of chatbots can be enhanced.
Adding human-like features to chatbots or giving them a human name may not be enough to effectively engage customers. They must maintain a conversation back-and-forth with the person on the other end. A popular journal, Computers in Human Behavior has suggested that chatbots with human features that lack interactivity disappoint users.
Although chatbots are enabling businesses to handle a variety of interactions, several mechanisms and techniques are available to enhance their capabilities. Leading consumer brands use NLP mechanisms to analyze customer interactions and provide inputs to decision-makers. NLP enabled chatbots can assess the intent of input from users and create human-like responses with contextual analysis.
Royal Bank of Scotland uses NLP in their chatbots to enhance customer experience through text analysis. They interpret customer feedback gathered from surveys, call center discussions, complaints, and emails. It enables them to improve their services by identifying the root cause of customer dissatisfaction.
The importance of NLP for a chatbot application is in addressing customer concerns in real-time. A chatbot uses NLP to communicate with customers like human customer service agents. An effective chatbot can respond to customer queries accurately. It identifies the relevant information in the conversation to automate and accelerate customer service processes.
Eugenia Kuyda, co-founder and CEO at Luka, created a chatbot named Replika. She wanted it to stand out among the voice assistants and home robots that had begun to take root in peoples’ lives. AI chatbots are now capable of scheduling an appointment or sharing updates about weather forecast simply by sending a voice note. It uses neural networks to hold an ongoing conversation and gradually learn how to speak like a human being. More than 2 million people have downloaded the Replika app. Many individuals discovered something like friendship, a digital companion with whom to lament failures, celebrate victories, and trade weird internet memes.
The information collected daily when combined with previous data improves the work process of conversational AI. The system becomes smarter with new chunks of information as they are programmed to work in specific ways. It analyzes relevant keywords based on communication and natural language processing to learn about users’ interests and preferences. It enables Chatbots to provide a personalized customer experience.
With the developments still on, conversational AI is adding new skills to redefine user experience by solving the challenges. Further, it improves customer satisfaction and the company’s growth simultaneously.
A survey was conducted by Usabilla to figure out peoples’ preferences about chatbots. 54 percent of the respondents preferred chatbots over human customer care representatives, even if it saves ten minutes of their time.
Businesses identify the need for a system that provides more human-like responses, if not completely human. Chatbots are not here to replace human agents but to improve their work quality. Using NLP and sentiment analysis chatbots can infer customer’s tone from any text document.
Soon, it will be possible to understand higher-level interactions like emotions or sarcasm.
AI-powered chatbots have made a significant impact on businesses since their advent. Researchers are rigorously training them to effectively handle customer queries and improve customer satisfaction level.
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