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Learn about what conversational AI is, how it works, and its benefits. Experience the best conversational AI platform for your business with Freshchat.
Conversational AI is the technology that enables chatbots or virtual agents to have human-like conversations with users by recognizing user inputs and interpreting their meanings. It is a subset of artificial intelligence that leverages concepts like neural networks, machine learning, and NLP to build conversational AI chatbots.
Conversational AI has two key components:
1. Natural Language Processing (NLP) - It is an AI-driven capability that allows bots to understand the meaning from written or spoken text by associating them with recognized words and phrases. Think of a question like "Where is my order?". There are so many ways humans can express this and NLP can process them in real-time and recognize the underlying intent.
2. Machine Learning (ML) - It is a set of algorithms, features, and data sets that helps bots to continuously learn from user behavior, and improve themselves with this experience. As the user input grows in these algorithms, the machine learning algorithm gets better at recognizing patterns and making predictions.
While a conversational chatbot will understand different variations of a user query and respond in an appropriate way, a conventional rule-based chatbot won’t be able to recognize and respond to other variations of the same question and will lead to user frustration.
Conversational AI uses Natural Language Processing (NLP) to help software understand the text or voice and then uses machine learning to train software to become more accurate at predicting outcomes without being explicitly programmed to do so.
Here’s the step-by-step process of how conversational AI works.
1. Input gathering: The user provides input through a website or an app where the format of the input can either be text or voice.
2. Input analysis: Based on the type of input, different technologies are used for input analysis.
3. Response management: During this stage, Natural Language Generation (NLG), a component of NLP, formulates a response for the query.
4. Response refinement: Finally, machine learning algorithms use this input data to refine chatbot responses over time to ensure accuracy.
The global conversational AI industry is expected to grow at a CAGR of 22% during 2020-25 and currently, chatbots top the use of conversational AI technology. Some of the use cases of conversational AI across industries include,
Customer support: As more people are becoming digital-first, the number of queries related to order confirmation, tracking, cancellation, and refund has seen a huge spike. Using AI chatbots to automate these queries can save a considerable amount of the agent’s time and help you provide 24X7 customer support.
Accessibility: Companies can become more accessible to their customers by deploying conversational AI chatbots on different messaging channels such as WhatsApp, Apple Business Chat, and Facebook messenger. This reduces friction in customer service and makes it convenient for users to engage with your business.
Agent training: Companies can leverage conversational AI to accelerate agent onboarding and optimize the employee training process. Agent-facing conversational AI chatbots can help new agents with training resources, connect them with the right team for any help and keep track of their performance.
Lead Generation - Lead generation is a critical and time-sensitive process and its success depends on how quickly and effectively the conversation can be initiated between the user and your business. Conversational AI chatbots can help businesses initiate a conversation proactively with a user visiting their websites, apps, or stores and nudge them to take the next steps in exploring your product or collect their details for further communication.
Feedback collection - Chatbots powered by conversational AI give customers a convenient way to share their suggestions and feedback. This is done by using a conversational AI chatbot to trigger a survey or feedback question at the end of any interaction. This feedback helps businesses better understand customer expectations and find out areas for improvement.
Better customer engagement - As Conversational AI chatbots can understand user intent and don’t rely on rule-based answers, they can proactively engage with a user and start a conversation. Once the conversation is initiated, a conversational AI chatbot can further help users with related resources, additional product information, and the next possible steps. This way conversational AI chatbot helps businesses proactively engage with customers and improve the overall customer experience.
Personalization - Personalization features within conversational AI help chatbots learn from the historic context and remove the need for a customer to repeat themselves now and then for the same issue. It also provides chatbots with the ability to provide recommendations to end-users, allowing businesses to cross-sell products that customers may not have initially considered.
Consistent customer experience - Since most interactions with support are information-seeking and repetitive, businesses can program conversational AI to handle various use cases, ensuring a comprehensive and consistent customer experience. This creates continuity within the customer experience and allows valuable human resources to be available for more complex queries.
Scalability - Adding support infrastructure using conversational AI is cheaper and faster than hiring and onboarding new employees. This helps businesses scale the support function quickly especially when products are expanding to new geographical markets or during unexpected short-term spikes in demand, such as during holiday seasons.
Cost efficiency - Staffing a customer service team can be quite costly, especially when you seek to answer customer queries outside office hours. Using conversational AI chatbot software, businesses can build intelligent bots that will help reduce support costs, can respond instantly, and provide 24X7 support to their potential customers.
Freshchat’s support and sales bots are built on top of AI and ML that detect the intent of prospects and learn from the questions asked over time.
Freshchat’s chatbots understand user intent and instantaneously deliver the right solution to your customers. As a result, customers no longer have to wait in chat queues to get their queries resolved.
Freshchat allows you to proactively interact with your website visitors based on the type of user (new vs returning vs customer), their location, and their action on your website. That way, you don't have to wait for your customers to initiate a conversation, instead, you can let AI chatbots take the lead in proactive engagement.
Our intelligent agent handoff route chats based on the skill level and current chat load of your team members to avoid the hassle of cherry-picking conversations and manually assigning it to agents.
Our conversational AI chatbots can pull out customer data from your CRM and offer personalized support and product recommendations.
You can easily integrate our smart chatbots with messaging channels like WhatsApp, Facebook Messenger, Apple Business Chat, and other tools for a unified support experience.
With a real-time dashboard and custom reports, you can analyze your chatbot performance against various metrics and optimize it to perform better.
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There are two key components of Conversational AI:
1. Natural Language Processing (NLP) - An AI-driven capability that can extract meaning from written and spoken text.
2. Machine Learning (ML) - A set of algorithms that continuously improve themselves with input data.
The use of Natural Language Processing (NLP) and Machine Learning (ML), to interpret the meaning of user input and continuously improve algorithms to respond in the most human way, differentiates it from traditional chatbots and other technologies.
Conversational AI is mostly used in chatbots to help businesses provide assistance to their users and internal teams. Some of the major use cases include
1. Providing 24X7 customer support and automating FAQs
2. Providing users accessible channels of communication to contact your business, by deploying conversational AI chatbots on messaging channels such as WhatsApp, Facebook Messenger, and Apple Business Chat.
3. Accelerating the agent onboarding and training process by using agent-facing conversational AI chatbots.
4. Generating leads by proactively initiating a conversation with a user and nudging them to take the next steps or collecting their details for further communication.
5. Collecting user feedback to better understand customer expectations and improve CSAT score.
Major benefits of conversational AI include
Better customer engagement
Consistent customer experience
Freshchat is powered by world-class AI, NLP, and ML technologies which make it a truly conversational AI platform. Along with this, Freshchat offers
Conversational AI chatbots that learn
Intent detection and faster resolutions
Proactive customer engagement
Intelligent agent handoff
Personalized customer conversations
Integration with messaging channels and other tools
Real-time data insights
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