AI for Customer Experience with Chatbots and Analytics
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AI for Customer Experience with Chatbots and Analytics
This course is part of AI-Powered Customer Success Specialization
Instructors: Starweaver
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What you'll learn
Identify the potential applications of AI technologies in enhancing customer experience.
Analyze the impact of personalization, chatbots, and predictive analytics on customer engagement.
Design and implement AI-driven strategies for improving customer interactions using tools like Perplexity AI, Claude, and Google Gemini GEM.
Evaluate ethical considerations and construct guidelines for responsible AI adoption in customer experience initiatives.
Skills you'll gain
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There is 1 module in this course
Customer engagement leaders and visionaries! Ready to harness AIβs transformative power to elevate customer experiences? On this learning journey, discover how to future-proof your CX strategy.
Gartner predicts 75% of customer service interactions will be AI-driven by 2025βand early adopters already see 30% faster resolution times. Lagging behind? This is your wake-up call! Forget empty buzzwords: This actionable crash course cuts through the noise, focusing on practical AI tools reshaping CX. Dive into real-world case studies and hands-on techniques for: 1. Hyper-personalization: Craft tailored campaigns that boost loyalty. 2. Smart chatbots: Deploy , Claude, and Gemini GEM for conversational engagement. 3. Predictive analytics: Anticipate Customer behavior patterns using Deepseek, Perplexity AI and Anthropic Claude. Learn to ethically implement AI-driven workflows, measure ROI, and avoid common pitfalls. Walk away with a toolkit to: β Design AI-enhanced customer journeys. β Automate repetitive tasks without losing the human touch. β Turn data into proactive, predictive engagement. This course is tailored for business professionals who may not have a technical background but are passionate about leveraging AI to enhance customer experiences. It is ideal for Customer Experience (CX) professionals, Digital Transformation Leaders, Marketing Executives, Entrepreneurs, and Customer Service Managers who want to stay ahead in an AI-driven landscape. Whether you're leading strategy or on the front lines of customer engagement, this course empowers you to integrate AI into your workflows to drive innovation and measurable business outcomes. Participants are expected to have a basic understanding of customer engagement processes and common industry terminology. No programming or technical expertise is required, making the course accessible to a broad range of professionals. The content is designed to bridge the gap between strategic business goals and practical AI applications, ensuring all learners can comfortably apply the concepts regardless of their technical proficiency. By the end of the course, learners will be able to identify where AI can be effectively used to enhance customer experience across touchpoints. They will be equipped to analyze the role of personalization, chatbots, and predictive analytics in driving customer engagement. Additionally, participants will gain the skills to design AI-driven customer strategies using tools like Perplexity AI, Claude, and Google Gemini GEM, while also understanding how to evaluate ethical implications and create responsible AI adoption guidelines.
In this course, youβll explore the practical applications of AI in transforming customer experience (CX) strategies across industries. Through hands-on experience with tools like Perplexity AI, Claude, and Google Gemini GEM, youβll learn to implement hyper-personalization, deploy smart chatbots, and leverage predictive analytics to enhance customer engagement. Youβll also evaluate ROI, address ethical considerations, and develop actionable guidelines for responsible AI adoption equipping you to lead AI-driven innovation in customer interactions.
What's included
11 videos4 readings1 assignment4 peer reviews3 discussion prompts
11 videosβ’Total 80 minutes
- Introduction and Welcome β’3 minutes
- Introduction to Generative AI in CX β’6 minutes
- Prompt Engineering & Prompt Strategies for CXβ’9 minutes
- Case Study: Personalized Marketing in Action β’10 minutes
- Creating an Ideal Customer Persona for an E-commerce Website β’8 minutes
- Designing Conversational Customer Service Bot with Google Gem β’6 minutes
- Evaluating Chatbot Success Metrics and Recommend Improvements β’10 minutes
- Introduction to Predictive Analytics in CX β’10 minutes
- Applying Data Analysis for Sales Forecasts β’9 minutes
- Evaluating Ethical and Data Aspects in AI-Driven CX β’7 minutes
- Congratulations and Continuous Learning Journeyβ’2 minutes
4 readingsβ’Total 20 minutes
- Welcome to the Course: Course Overviewβ’5 minutes
- What is Prompt Engineeringβ’5 minutes
- Generative AI for Customer Service β’5 minutes
- Ethical Considerations in GenAI Customer Support β’5 minutes
1 assignmentβ’Total 20 minutes
- AI for Customer Experience with Chatbots and Analyticsβ’20 minutes
4 peer reviewsβ’Total 90 minutes
- Hands-On-Learning: AI-Powered Customer Personalization Workshop β’10 minutes
- Hands-On-Learning: Designing and Evaluating an E-commerce Support Chatbot Workshopβ’10 minutes
- Hands-On-Learning: Predictive Analytics for Retail Sales Forecasting Workshop β’10 minutes
- Project: Product Recommendation Gem & Performance Analysis Project β’60 minutes
3 discussion promptsβ’Total 15 minutes
- Leveraging Generative AI Capabilities for Enhanced Customer Experienceβ’5 minutes
- Metrics-Based Chatbot Evaluation: Critical Success Indicatorsβ’5 minutes
- Proactive Decision-Making Through Predictive Analyticsβ’5 minutes
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Frequently asked questions
In this course, it means using AI to personalize customer communications, support conversations, and analyze behavior across customer touchpoints. The emphasis is on building practical customer experience workflows that combine personalization, chatbots, predictive analytics, and responsible data use.
You would use it when customer interactions are repetitive, need to feel more tailored, or depend on spotting patterns in customer behavior before taking action. The course presents it as a way to improve messaging, service, and follow-up rather than handling each interaction in a generic way.
It fits after you define who the customer is and what they need, and before you measure results and refine the experience. In the course, it links persona work, conversation design, and behavior analysis into a connected process instead of separate tasks.
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