Introduction
With changing customer expectations, companies are shifting their customer support, sales, and marketing workflows toward artificial intelligence. As manually handled operations are often prone to delays, error, and inefficiency, AI-powered applications like chatbots redefine customer experiences.
Conversational AI is advancing to produce near-human conversational capabilities, which allows AI chatbot features to foster customer loyalty through better personalization to address customer concerns exclusively.
Chatbots have also been efficient at automating routine tasks and assisting agents while handling common queries. This increases the turnaround time for query resolution and thus offers a better customer experience. Data shows that chatbots can finish 69% of chats without human assistance.
So, if you are thinking of investing in a chatbot for your customers, check out our 10 AI chatbot features that you should consider for improving customer experience.
10 Must-have AI chatbot features for an exceptional customer experience
We all must have at some point interacted with a chatbot while shopping or searching for services. Previous chatbots were limited in their support for dynamic queries with their rule-based input response capabilities, due to which they failed to leave a mark. However, today’s chatbots have come a long way to transform the customer experience.
It is essential to know what AI chatbot features to look for while planning to implement them in your business. Specific capabilities allow chatbots to have a broad impact on customer
experience and business productivity. Let’s have a closer look at each of the features that make a great chatbot;
Advanced conversational capabilities
Along with understanding and conversing fluently, it is essential for a chatbot to have natural language processing to decipher the contextual meaning behind a sentence in multiple languages. Contextual awareness allows chatbots to maintain a more natural conversation flow and offer an appropriate response that resolves customer concerns. A chatbot should also be able to identify the intent behind a customer query to resolve a query completely.
Entity recognition
A chatbot should be able to identify entities that will provide logical information. With the help of entity recognition, a chatbot identifies named entities among an unstructured text and categorizes them into pre-defined categories such as name, company name, location, region, time, quantity, etc. Advanced chatbots with conversational capabilities can ask clarifying questions that can lead them to the information needed to resolve a query effectively. Chatbots are efficient at social listening, monitoring online reputation, and gathering market trends. Chatbots can identify critical information and categorize it; chatbots can be a powerful tool in brand reputation management.
Sentiment analysis
Emotional intelligence leverages humans against machines. However, recent advancements in conversational AI are allowing chatbots to recognize complex emotions, sentiments, and conversation tones to interact accordingly. Sentiment analysis has been vital in personalizing and responding with empathy for the chatbots.
Independent thinking
A chatbot should be capable of performing complex thinking without human intervention. It requires chatbots to train on various reasoning techniques for logical thinking based on facts, inferring from observations, and explaining their observations with logical hypotheses. Such capabilities allow chatbots to be applicable in sectors such as healthcare, research, finance, autonomous driving, etc. In a customer support department, autonomous thinking is helpful while text summarization or engaging in complex conversations.
Omni-channel conversations
A chatbot should be able to interact with users across multiple digital channels. They should be accustomed to different content formats and prompts. With entity recognition capability, a chatbot can acquire critical customer information to consolidate the data in a user-friendly format.
CRM integration
Ensuring a superior customer experience with a brand involves integrated workflows that work together. A chatbot can impact various functions within a CRM. It can automate routine tasks and follow-ups, schedule reminders, and clarify customer movement through multiple stages of a purchase journey.
Knowledge acquisition
A chatbot should be able to expand its knowledge base by searching and processing a vast amount of data. It should be capable of presenting logical information from structured and unstructured data.
Pre-trained
A chatbot should be pre-trained to understand industry-specific terminologies and contextual information for easy scalability, even before they are configured to support a specific industry.
Live-chat handover
Though data shows that chatbots can resolve around 70% of queries independently, they have limitations, like the complexity of the chat when human interference is required. Additionally, when a user requests to connect with a live agent, a chatbot should be quick and seamless while handing over the chat to an available agent. It offers immediate specialized attention to users, which can boost customer experience.
Data privacy and security
In this information age, user data is critical. The customer-business relationship balances the trust between both. Interactions with a chatbot should remain confidential, and companies should safeguard user information. For this, companies should be vigilant to collaborate with chatbot providers who adhere to strict data security protocols.
Conclusion
The above ten essential AI chatbot features are the foundations for the success of your chatbot functionality. Every feature is crucial for smooth conversation, personalization, and accurate information acquisition to enhance customer experience and efficiency of various operations.
Kenyt is a leading conversational AI platform for accelerating sales, marketing, and support operations with superior customer experience. Kenyt AI chatbots have proven to bring 5X engagement with its 95% accuracy rate for simple to complex queries. Kenyt’s no-code AI agent redefines customer engagement across multiple digital channels.
Frequently Asked Questions
While chatbots offer numerous advantages, they do have certain limitations, like;
• Language ambiguities
• Lack of contextual understanding
• Lack of emotions
• Intensive training requirement
To train chatbots to handle complex queries, it is possible to employ the following steps;
• Extensive training
• Vast resources
• Advanced NLP applications
• Structured conversation flow
• Advanced machine learning
• User Feedback
It is possible to improve the accuracy of chatbot responses through;
• Quality training data
• Advanced NLP
• Regular monitoring and correction
• User testing and feedback
• Clear conversation flow
Nisha Sneha
Nisha Sneha is a passionate content writer with 5 years of experience creating impactful content for SAAS products, new-age technologies, and software applications. Currently, she is contributing to Kenyt.AI by crafting engaging content for its readers. Creating captivating content that provides accurate information about the latest advancements in science and technology has been at the core of her creativity.
In addition to writing, she enjoys gardening, reading, and swimming as hobbies.
