No longer a futuristic concept, artificial intelligence (AI) is now part of our daily lives. We ask Alexa for the morning news, use a GPS app to avoid traffic jams and receive product recommendations from Amazon. Businesses rely on AI for process automation and to improve customer experience (CX). According to Capterra’s 2023 CX Investment Survey, 65% of companies are using AI to support CX success.
Chatbots and generative AI (GenAI) are two types of AI that can improve CX. GenAI and chatbots both involve machine learning—a subset of AI that uses algorithms to learn from data and make predictions. Chatbots and GenAI differ in their functions and applications.
What Is a Chatbot?
A chatbot is a type of Conversational AI (CAI) that simulates conversation with humans. CAI uses machine learning and natural language processing (NLP) to understand text or voice and then respond using natural language. Conversational AI can detect a person’s intent and emotional state.
Chatbots are often used in customer service settings to answer questions and offer support. Chatbots can manage 65% of customer inquiries and routine tasks, making them a valuable investment for businesses.
Well-designed chatbots can:
- Use existing conversation data to understand the types of questions people ask
- Analyze accurate responses to those questions
- Employ machine learning and natural language processing to grasp context, improving their ability to answer those questions correctly
What Is Generative AI (GenAI)?
Generative AI is a type of machine learning that allows machines to independently create
new content. GenAI analyzes existing content to find patterns and make predictions, allowing it to create brand-new content out of the existing content. GenAI can be used in chatbots and content generation to produce new text, images, computer code and even music.
In a business setting, GenAI-powered, customer-facing chatbots better understand customer queries and respond more accurately. According to the International Data Corporation (IDC), “the primary application for early versions of GenAI is in AI-driven chatbots and agents for contact centers and customer self-service. [IDC believes] GenAI will enable more personalized product recommendations through insight analytics…and faster resolution of customer complaints.”
What Are the Differences Between a Chatbot and Generative AI?
The primary difference between a chatbot and generative AI is that GenAI generates original content when prompted, while a chatbot engages in authentic two-way interactions with people through text or speech comprehension and response.
| Chatbot | GenAI | |
|---|---|---|
| Focus | Conversation and interaction – Answer questions – Complete tasks | Creating new content – Text – Images – Audio – Code |
| Underlying Technolgy | Natural Language Processing Machine Learning | Machine Learning |
| Input | Human language | Data or user prompts |
| Output | Human-like responses | New content |
| Capabilities | Hold conversations Answer questions Complete basic tasks | Create original content |
| Limitations | Limited ability to understand complex or nuanced language | May not be able to engage in back-and-forth conversation or understand intent |
How Can Chatbots and GenAI Be Used to Enhance CX?
| CX Applications | Benefits | |
|---|---|---|
| Chatbot | Customer service Virtual assistants Appointment scheduling Information retrieval | Greater efficiency and speed 24/7 availability Provides self-service options Reduces customer effort by streamlining interactions using previous support tickets Collects data regarding customer needs and pain points that can be used to improve products and services Reduces contact center calls Eases the workload of contact center staff |
| GenAI | Content generation AI-powered chatbots and virtual assistants Voice assistants (e.g., Alexa, Siri) Personalization engines (Amazon – recommended for you) Feedback analysis (analyze survey responses, generate insights to help businesses make data-driven decisions) Social media responses (automate responses to social media comments | Includes the benefits listed above for chatbots Boosts customer satisfaction through more comprehensive, personalized interactions Offers hyper-personalization of content, recommendations and marketing messages Creates content at scale, saving staff time Gives accessibility and language support by translating content and communications in real time Prompts data-driven innovation by analyzing customer feedback and reviews to identify areas for improvement |
5 Steps To Implementing a Chatbot for CX Improvement
1. Define your goals and target audience. What do you want to achieve with chatbots (e.g., faster resolution of common issues)? You must understand the needs, behavior and preferred communication style of the customers who will be using the chatbot.
2. Design the chatbot experience.
- Functionality. What specific tasks will the chatbot handle?
- Answer FAQs
- Troubleshoot problems
- Collect customer information
- Personality and tone. The chatbot personality should align with your brand voice. Will the tone be friendly and informal, or professional and authoritative?
- Conversation flow. Design the conversation flow to be clear, concise and user-friendly. Include options for users to easily switch to a human agent if needed
3. Develop and train the chatbot. Choose a chatbot development platform that suits your needs and technical expertise. Train the chatbot with a massive dataset of relevant information, including FAQs, customer support transcripts and product knowledge. Consider using generative AI to create more natural and engaging conversation flows.
4. Integrate and test. Seamlessly integrate the chatbot into your website, mobile app or messaging platforms where your customers interact. Thoroughly test the chatbot to ensure it functions correctly, understands user queries and provides helpful responses.
5. Launch, monitor and refine. Deploy the chatbot and gather feedback from customers. Monitor chatbot performance through analytics to identify areas for improvement. Continuously refine the chatbot’s training data and conversation flows based on user interactions and feedback.
4 Steps To Implementing GenAI for CX Improvement
Identify pain points and choose a use case. Pinpoint a specific journey that could be improved using GenAI. For example, in the payment journey, bill confusion is a leading reason for billing-related calls. An AI-powered digital bill explanation tool provides a personalized bill summary that helps customers understand charges and reasons for month-to-month changes. The tool reduces bill confusion and contact center calls. Contact center agents can access a customer’s bill summary to quickly assist customers who call instead of using the self-service tool.
Start with clean data. GenAI output is only as accurate as the input data it’s trained with, so it’s essential for your data to be clean, structured and accessible. That requires effective data management and integration practices.
Initiate compliant processes. To protect data privacy, you must follow existing rules (e.g., obtain customer consent) and quickly adopt new ones as AI and the regulatory landscape evolve. Your AI compliance team must have the latest information and understand the best way to protect customer data and follow regulations.
Establish continuous monitoring. Analyze robust business metrics and key performance indicators to measure the success of your GenAI implementation and allow your teams to experiment and improve processes. To evaluate the effectiveness of a GenAI-powered bill explanation tool, monitor the number of contact center calls and average handle time.
CSG Solutions Simplify the Implementation of Chatbots and Generative AI
Chatbots and GenAI are both valuable technologies that can enhance customer experience. Through the power of continuous learning, CSG Conversational AI understands everyday speech, phrasing and context, enabling it to replicate the nuances of natural speech and deliver more human-like customer interactions.
CSG Bill Explainer uses generative AI-driven, personalized statement summaries to guide customers through their bill, helping them understand charges and month to month variations. Bill Explainer reduces bill confusion and contact center calls and encourages prompt payment.
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