AI for Executives: AI for Customer Relationship Management

This course is part of AI for Executives Specialization

Instructor: Prof. Ernesto Damiani

Access provided by Ecole Supérieure des Industries du Textile et de l'Habillement

5 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

5 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Build unified customer profiles; apply predictive analytics for churn, next-best-action, and customer lifetime value.
Design personalized engagement using recommendations, intelligent virtual assistants, and LLM-powered support.
Implement responsible AI in CRM—privacy, security, fraud prevention—and create an executive roadmap aligned to business goals and change management.

Skills you'll gain

Tools you'll learn

Fraud detection

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

5 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business

logos of Petrobras, TATA, Danone, Capgemini, P&G and L'Oreal

Build your subject-matter expertise

This course is part of the AI for Executives Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 5 modules in this course

AI for Customer Relationship Management (CRM) shows executives how to use artificial intelligence to deepen customer insight, personalize engagement, and scale service—without coding. You’ll build richer customer profiles by integrating behavioral, transactional, and external data; explore graph-based community modeling to understand relationships; and apply predictive analytics for churn, next-best-action, and customer lifetime value. You’ll practice sentiment and voice analytics to capture the “voice of the customer,” then design personalized experiences with recommendations, targeted campaigns, and human-in-the-loop programs. The course also covers intelligent virtual assistants and LLM-powered support, sales enablement (lead scoring, cross-sell), dynamic pricing, and fraud detection with security and compliance in mind. Finally, you’ll develop an AI-driven CRM strategy—roadmapping technology choices, aligning initiatives to business goals, managing change, and addressing ethics and governance. By the end, you’ll be able to evaluate use cases, choose appropriate techniques, and lead responsible AI adoption across marketing, sales, and service.

This module grounds executives in CRM fundamentals and how AI elevates engagement, personalization, and measurement across the customer lifecycle. You’ll connect CRM components with outcome metrics, surface near‑term AI opportunities, and examine privacy/security trade‑offs. A light introduction to graph‑based community modeling helps you visualize customer networks for segmentation and outreach.

What's included

6 videos5 readings1 assignment1 discussion prompt

6 videosTotal 20 minutes

Introduction to the Specialization2 minutes
Definitions and Components of CRM4 minutes
The AI Promise3 minutes
Enhancing Customer Engagement Through AI5 minutes
Using LLMs for CRM4 minutes
LLM Applications for CRM2 minutes

5 readingsTotal 50 minutes

Definitions and Components of CRM Briefing Document10 minutes
The AI Promise Key Concepts10 minutes
Enhancing Customer Engagement Through AI Briefing Document10 minutes
Using LLMs for CRM Key Topics10 minutes
LLM Applications for CRM Key Topics10 minutes

1 assignmentTotal 30 minutes

Module 1 Quiz30 minutes

1 discussion promptTotal 10 minutes

Design a Simple Ranking Rule (EdgeRank‑style)10 minutes

Focus on the data foundations of AI for CRM: what to capture, how to integrate, and how to safeguard quality and governance. You’ll interpret outputs from predictive models (e.g., churn) and run a practical sentiment/voice‑of‑customer workflow—including multilingual considerations—to turn unstructured feedback into action.

What's included

1 video1 reading1 assignment

Translate AI capabilities into engagement levers: personalization, assistants, and sales enablement. You’ll experiment with content/recommendation strategies, design and assess chatbot/voice‑assistant experiences, and apply LLM prompt design and specialization—all tied to revenue outcomes via lead scoring and cross/upsell.

What's included

2 videos2 readings1 assignment1 discussion prompt

Learn where automation moves the needle: dynamic pricing, revenue optimization, and fraud/security in customer interactions. You’ll estimate price responsiveness, design fraud‑prevention workflows with human‑in‑the‑loop review, and specify process KPIs to quantify efficiency and risk reduction.

What's included

1 video1 reading1 assignment

Bring it all together into an executive‑ready plan. You’ll align AI initiatives with business goals using a Goal–Question–Metric (GQM) approach, produce a technology roadmap, and address change management, ethics, and risk so your AI‑CRM strategy is viable, governable, and future‑proof.