Chatbots

What is a chatbot?

A chatbot is software that uses artificial intelligence (AI) and natural language processing (NLP) to simulate human-like conversations with customers through multiple channels, like messaging apps, website chats, voice assistants, and customer contact centers.

An efficient chatbot can understand and respond to real-time customer queries in a near-human tone and provide relevant resolutions under minimal supervision. You can also optimize chatbots to achieve set objectives like collecting customer data and agent feedback or delivering personalized customer service.

Important: chatbots are also known as conversational AI, chatterbots, virtual assistants, and conversational agents or interfaces.

How do chatbots work?

Powered by AI technology, chatbot software is programmed to deliver conversation through a chat interface such as voice or text. Agents can feed chatbots pre-approved responses based on a rule-based workflow and automate the query-resolution process, which enables live agents to focus on complex queries. As the popularity of chatbots grows, multiple industries like healthcare and education have started adopting chatbots to improve customer support and experience.

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Types of chatbots

There are three major types of chatbot software, categorized by their level of sophistication and purpose.

1. Rule-based chatbots

Rule-based chatbots (or decision-tree chatbots) use if-then logic to formulate follow-up questions with predetermined options until customers are provided with reliable solutions.

This type of chatbot analyzes every word of a message — including its placement and synonyms based on predefined rules to understand the query and provide a relevant response.

You can use rule-based chatbots for task-specific queries like placing an order, checking delivery status, or collecting agent feedback.

33% of users prefer using chatbots to make reservations and order online

Source: outgrow.co

2. AI chatbots

AI-powered chatbots use machine learning (ML) and NLP to understand customers’ language, intent, and sentiment behind a message to provide personalized, human-like interactions.

Popular examples of AI chatbots are virtual assistants like Amazon’s Alexa, Apple’s Siri, and Google Assistant. They can study customer patterns and tend to be more conversational and personalized.

A good AI chatbot can also categorize customer interactions by complaints, leads, inquiries, and compliments — helping your support team streamline workflows and prioritize customer messages that require an immediate response.

Learn more: How Conversational AI helps brands be human@scale

3. Hybrid chatbots

Hybrid chatbots, like rule-based chatbots, are simple to implement but smart like AI chatbots. They execute conversation flows based on predefined rules while understanding the intent of customers' messages.

Also, hybrid chatbots allow ML integrations to aid areas where a rule-based approach is difficult to create or implement. For example, internet providers may use hybrid chatbots to diagnose network connectivity.

What are the benefits of using a chatbot?

Using chatbot technology, businesses can provide 24/7 customer support for simple queries that do not require an agent’s immediate attention. Here are some additional benefits of chatbots.

Benefits to customer support teams

1. Increased engagement

When customers begin a chat with support, chatbots can respond in real time — regardless of your agent’s availability.

Chatbots can interact with multiple customers simultaneously and reduce the burden on your support team while improving your customer engagement.

Chatbots can answer almost 80% of all standard questions.

Source: outgrow.co

2. Improved sales

Chatbots are smart. Driven by advanced algorithms and powered by AI, chatbots can understand your customers’ queries and share relevant responses.

After consistent data analysis, chatbots can uncover cross-sell and upsell opportunities by introducing your products to customers. In fact,47% of users are open to purchasing items via a chatbot.

Learn more: Why chatbots are needed in call centers?

3. Save time and money

You can optimize chatbots to handle complex queries and ensure seamless support across customer touchpoints.

As a chatbot evolves, it can provide reliable solutions to most common queries and keep your agents from being overwhelmed. Chatbots can also cut down live agents’ interaction time by sharing only those queries that require their attention.

By 2023, chatbots will save businesses and consumers an estimated 2.5 billion hours. In 2021, chatbots cut operational costs for companies by up to 30%.

34% of executives say that chatbots save time and allow them to focus on deep thinking and creation.

Source: outgrow.co

4. Automation

A well-constructed chatbot can automate the support process and make it more efficient — you can provide customers with self-service options, collect agent feedback, and submit support tickets.

Learn more: AI Automation for Customer Service Agents

5. Multilingual capabilities

Your customers can hail from across the globe. Some may be proficient in English but not in Chinese. Advanced chatbots can interact with customers in their native language and even translate their responses for your agents. This way, your support teams can resolve customer queries from numerous locations seamlessly.

Benefits to customers

1. Quick responses

75% of customers expect a company to respond within five minutes, making it essential for support teams to provide quick resolutions. Chatbots can interact with thousands of customers simultaneously, with everyone receiving personalized responses leading to a solution. This also improves your first contact resolution (FCR) rate.

Learn more: Improve Customer Response Times and Your Bottom Line

2. Around-the-clock support

51% of customers expect their favorite brands to be available 24/7, which is challenging for agents due to their fixed working hours. Chatbots do not have such limitations — they are available around the clock to provide immediate support and streamline communications to minimize wait times and frustrations.

3. Personalized interactions

Customers grow impatient when they have to explain their problems multiple times to agents, resulting in a dissatisfied customer experience — 96% of customers will leave you for bad customer service. That’s where chatbots help you retain your customers.

Chatbot technology can store data related to the customer (e.g., name, email, ticket number) and their chat history to deliver a personalized experience across channels.

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Getting started with chatbots

1. Identify the goals for your chatbot

You can use chatbots for various purposes such as sales, marketing, or support. With a set objective in mind, you know where to focus your efforts. Study your customers and identify their pain points: are they frustrated with long wait times, or are they looking for 24/7 support? Based on the analysis, implement a chatbot, and you’ll notice an improvement in your customer satisfaction (CSAT) score.

Learn more: The Top 7 Messenger Bots By Brands (And Why They’re Awesome)

2. Choose the right chatbot type for your business

After determining your goals, select the best chatbot type for your business. You can choose from the three main types previously covered:

• Rule-based chatbots

• AI chatbots

• Hybrid chatbots

Implement the chatbot type that can handle your customers’ most troubling pain points.

3. Ensure that your chatbot platform is brand compliant (with a personality)

Give your chatbot a personality that matches your brand voice, image, colors, and website design and also resonates with your audience. Provide a functional user experience with interactive CTAs and buttons, but keep the responses simple and easy to understand.

4. List common customer queries for automation

Create an automated workflow for common customer pain points and queries that a chatbot can resolve without the involvement of support agents. You can create FAQs or knowledge base (KB) articles on those common pain points and instruct your chatbot to fetch relevant KB articles or FAQ pages for customers.

5. Create a workflow for queries requiring agents’ attention

Create a workflow for queries that are too complex for chatbots to handle and thus require an agent’s attention. Provide customers with an option to connect with an agent when needed. Also, optimize chatbots to collect the relevant information (if required) and route the chat to an agent skilled in handling the query.

6. Optimize your chatbot messaging

During customer interactions, not only do you have to stay brand compliant, but you also need to ensure that your messaging is clear, regardless of intent. There are three major stages during customer interaction that need optimized messages for chatbots.

• Greeting
  Use compelling messaging to begin an interaction with a visitor or customer. You can inform them about new products and offers or send them the standard, “Hey [first name]! How can I help you today?” message. Try to keep your message concise and motivate the customer to take action.
  

• Fallback
  Sometimes chatbots won’t understand a customer's query and thus won’t be able to help them. That's when you need a fallback response to keep customers engaged.
  
  Try and avoid using generic responses like, “I don’t understand. Can you please share more details?” as they are inconclusive and can frustrate customers.
  
  Descriptive responses that resonate with your chatbot personality like, “I am sorry, I don't understand. Did you mean that you want to [task]?” are a much stronger choice.
  
  If that doesn’t work for you, inform customers that you are routing them to another agent with a message such as, “Please give me a moment. I will connect you with an available agent.”
  

• Closing
  Both live agents and chatbots need feedback to improve, so before ending your conversation with customers, request their feedback with a message like, “How do you rate this conversation?” followed by a star or emoji rating request.
  
  Also, it’s a good idea to add an optional section for customers to share detailed feedback. After customers have shared their feedback, you can send a personalized thank you message based on the feedback (negative or positive).

Learn more: Three keys to mastering the art of Conversational AI

7. Measure and improve

Finally, analyze the performance of your chatbots to improve the quality of interactions. Keep an eye out for your customers’ patterns and behaviors to understand whether they interact more with chatbots or live agents. It will help you decide where to focus your efforts.

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Improve your customer service using Sprinklr’s Conversational AI and Bots

Chatbot software is excellent for care agents seeking to cut down average handling time (AHT) and average response time (ART) while delivering personalized experiences.

Sprinklr’s Conversational AI and Bots, powered by advanced algorithms and ML capabilities, ensure seamless support to every customer. And as the world’s only Unified-CXM platform, Sprinklr allows you to integrate Conversational AI and Bots on 30+ channels and deliver a consistent experience compliant with your brand guidelines, in addition to:

• Handling multiple, changing topics with smart automation
  With smarter dialog automation, Conversational AI can resolve multiple queries within a single interaction or even switch topics completely mid-conversation — responding in ways that make customers forget they’re not talking to a person.
  

• Deploying bots across languages
  Traditional bots only handle one communication channel at a time — which means redundant effort and costs if you offer chat, social media, and messaging support. Sprinklr Conversational AI creates a single chatbot flow you can easily customize for each channel.
  

• Managing all channels with a single bot
  Sprinklr Conversational AI analyzes your customer data, identifying the top categories and intents with the biggest impact on your business — eliminating the human guesswork in deciding which conversational flows to build.
  

• Discovering the top reasons why customers contact your brand
  Sprinklr Conversational AI analyzes your customer data, identifying the top categories and intents with the biggest impact on your business — eliminating the human guesswork in deciding which conversational flows to build.
  

• Continuously improving the accuracy of your AI bots
  Conversational AI pulls customer data from more than 20 channels, 500 business-specific models, and 100 million data training points — providing the best accuracy at resolving cases at scale and making each automated response more precise and helpful.