📝 General Introduction

In today’s data-driven business landscape, understanding customer behavior is no longer a luxury—it’s a necessity. Successful organizations don’t just serve customers; they analyze how customers think, act, and interact across touchpoints.

Analytical tools empower teams to collect, interpret, and act on behavioral data to improve customer experience, personalize services, and drive loyalty.

From tracking digital interactions to segmenting behavioral patterns and predicting future actions, data analytics transforms raw information into strategic insight.

This workshop is designed to help participants master the use of analytical tools to decode customer behavior, uncover hidden needs, and build smarter service strategies.

Over five immersive days, attendees will explore data types, behavioral segmentation, predictive analytics, and performance measurement through hands-on exercises and real-world applications.

🎯 Target Audience

• Customer service and experience managers
• Data analysts and marketing professionals
• Digital transformation and product leaders
• Contact center and support team supervisors
• CRM and customer insights specialists
• CEOs and operations executives

🎯 Expected Outcomes

• Understand the importance of behavioral analytics in customer experience
• Learn how to use digital tools to collect and interpret customer data
• Analyze interaction and purchase patterns to identify needs
• Apply predictive analytics to forecast customer behavior
• Build data-driven strategies to improve satisfaction and loyalty

📚 Scientific Topics

Theme 1: Introduction to Customer Behavior Analytics

Session 1: Why Behavior Matters

• Data-driven decision making
• Behavior and loyalty connection
• Market case studies

Session 2: Types of Customer Data

• Digital interaction data
• Purchase and frequency data
• Satisfaction and feedback metrics

Theme 2: Digital Analytical Tools

Session 1: Popular Analytics Platforms

• Google Analytics
• CRM-based analytics
• Behavior tracking tools

Session 2: Choosing the Right Tool

• Tool comparison
• System integration
• Data management and reporting

Theme 3: Pattern Analysis and Behavioral Segmentation

Session 1: Interaction Pattern Analysis

• Customer journey mapping
• Identifying engagement points
• Measuring time and frequency

Session 2: Behavioral Segmentation

• Categorizing customers by behavior
• Building targeted segments
• Personalizing messages and experiences

Theme 4: Predictive Analytics and Performance Measurement

Session 1: Forecasting Customer Behavior

• Purchase prediction models
• Identifying potential churn
• Enhancing retention strategies

Session 2: Measuring Satisfaction and Loyalty

• Emotional performance indicators
• Feedback analysis
• Linking data to business outcomes

Theme 5: Practical Application and Personal Development

Session 1: Real-World Data Exercises

• Analyzing actual datasets
• Building behavioral reports
• Presenting actionable insights

Session 2: Personal Growth Planning

• Analytics skill assessment
• Identifying improvement areas
• Creating a sustainable development roadmap