Why We Love Chatbot (And You Should, Too!)

What is a Chatbot?

A chatbot is a computer software that mimics human communication with a user. While not all chatbots have artificial intelligence (AI), contemporary chatbots increasingly use conversational AI methods like natural language processing (NLP) to comprehend user inquiries and generate automated answers.

Think about conversing with a machine that mimics the sensation of speaking with a customer support representative. Software created to mimic human interaction, whether speaking or typing, makes chatbots so magical. As AI develops further, chatbots are becoming more and more essential to corporate processes and customer experiences.

According to our research, chatbots are now used by 58% of consumers for basic customer support activities, up from 43% in 2020. Let's examine chatbots, their effects on customer service, and doable ways to include them in your company to fully utilize this technology.

What are Chatbots used for?

Consumers frequently utilize chatbots to get prompt answers to inquiries about goods or services, as well as assistance with basic duties like scheduling appointments or keeping track of orders. Chatbots can also be used by customer support staff to answer standard questions, freeing them up to concentrate on more complicated client requirements. This improves customer service metrics like customer satisfaction score (CSAT), deflects cases, lowers agent burnout, and streamlines procedures.

Types of Chatbots

Around the world, hundreds of thousands of companies are creating various types of chatbots to improve customer service. This section describes the different kinds of chatbots, their applications, and which chatbot software would be best for your business.

1. Social messaging Chatbots

Organizations can now use an AI algorithm across all of their customers' preferred message channels thanks to the emergence of new social media interfaces. This covers messaging apps like WhatsApp and WeChat in addition to Facebook Messenger, Instagram, and Twitter. Without increasing the workload of a contact center, it allows for a more enjoyable online experience for consumers and higher engagement for the business.

2. Voice bots

A voice bot is a communication channel that uses artificial intelligence (AI) and natural language understanding (NLU) to convert voice to text and text to speech. AI technology helps choose the best conversational answer and recognize important voice signals. After that, the text-to-speech (TTS) engine turns the message into voice or audio to finish the interaction.

These automated systems are designed to perform speech comprehension and response tasks in a way similar to that of a human. Interactive voice response (IVR), self-service, and online knowledge bases are just a few of the customer support solutions that can easily incorporate the advanced communication paradigm offered by voice assistants or speech chatbots.

3. Skills Chatbots

A skills chatbot is another kind of bot that can perform a certain set of tasks; it can be improved using pre-made skills software. For example, the chatbot may be able to deliver weather information, switch off lights in your room when connected to a smart home appliance, and shop for groceries online. With access to the skill's source code, developers can build their chatbots for skills and integrate them with other platforms.

4. Keyword-based Chatbots

In contrast to menu-based chatbots, keyword-based chatbots can listen to the entry and provide accurate responses. These chatbots recognize action triggers in the discussion and know how to react to the customer by using customized keywords and natural language processing. These chatbots might not perform well, though, when confronted with numerous similar queries. Keyword repetitions across multiple related queries may cause the chatbots to stumble.

Because of this, chatbots that mix keyword recognition with menu or button-based navigation are growing in popularity. Users can enter commands directly using clickable navigation buttons in chatbots like these if the keyword detection feature isn't working or if they need more assistance finding an answer. This works well when the bot is unable to identify keywords in the input that has been typed.

5. AI-powered contextual Chatbots

Contextual chatbots can understand the context of a conversation and interpret user inquiries correctly. Additionally, it can remember previous exchanges and apply that knowledge to stay relevant when speaking with returning clients. Contextual bots can ensure a consistent experience for recurring consumers. To make sure that the context of the discussion meets the demands of the customer at every touchpoint, it may also keep data on user intent collected across many platforms and channels.

Contextual chatbots are linked to a website or application's centralized database, usually a customer data platform (CDP) or customer relationship management (CRM) system. This allows individuals to access important details about a person they are speaking with, such as that person's name, location, or past purchases.

6. Transactional bots

Whether for lead generation, appointment booking, or money collection, transactional chatbots may support businesses in enhancing their sales and marketing initiatives. Without the need for human assistance, users can interact with the chatbot and complete transactions immediately.

The capacity to facilitate transactions and promote business around the clock is its greatest advantage. A transactional chatbot is hence different from other kinds of bots, such as support or informational bots. By providing a quick and simple route for a specific purpose, its goal is to accomplish a transaction and optimize the user experience. It is made to do a limited set of specialized activities.

How do Chatbots work?

Either basic rules or more sophisticated AI are used by chatbots to manage interactions through scripted dialogues intended to complete particular communication tasks.

Rules-based chatbots work by extracting important terms or phrases from user inquiries and comparing them to preset answers. For instance, a rules-based chatbot can identify the term "hours" and obtain details on operating hours when you ask it, "What are your store hours?" These chatbots converse simply, adhering to a linear script in which the exchange rigidly follows pre-established guidelines. Due to its inability to handle differences in question phrasing, this approach may have limitations.

AI-powered chatbots can comprehend the underlying intent of a user's message by using natural language processing (NLP) and machine learning (ML), which goes beyond simple keyword recognition. This enables them to have more intricate conversations that are tailored to each individual and evolve according to the situation and past interactions. These chatbots improve their capacity to carry out smooth, end-to-end conversations that closely resemble human contact by learning and developing from every engagement. Because of this, they are highly advanced virtual assistants that can handle complex and nuanced user conversations.

The Chatbot Revolution

Nowadays, chatbots are a crucial component of corporate operations, simplifying internal and external communications. To respond to consumer inquiries, basic chatbots employ a straightforward rules-based navigation system. AI, ML, and NLP are used by more sophisticated systems to comprehend the particular context of each consumer and offer an efficient solution. Companies may offer a lot of clients excellent help by integrating chatbots with their current contact center and digital platforms.