Customer Data Analytics & Management Course

Course Overview:

This training course is designed to equip participants with the knowledge and skills required to effectively manage, analyze, and derive valuable insights from customer data. The course will cover various aspects of customer data management, analysis techniques, and industry-standard metrics. Additionally, participants will learn how to interpret and analyze qualitative customer feedback data to enhance decision-making processes.

Duration: 5 Days -Class Based

                    7 Days- Online -Instructer-Led

Location: Westlands Nairobi, Kenya

Training Objectives

1. Understand the Importance of Customer Data: Participants will grasp the significance of customer data in driving business decisions and improving overall customer experience.
2. Learn Customer Data Management Techniques: Participants will acquire skills in organizing, storing, and managing customer data efficiently and securely.
3. Master Customer Data Analysis: Participants will learn various techniques and tools to analyze customer data effectively, extract actionable insights, and make informed business decisions.
4. Familiarize with Customer Analysis Metrics: Participants will gain knowledge of key metrics used in customer analysis, including customer acquisition cost (CAC), customer lifetime value (CLV), churn rate, and others.
5. Analyze Qualitative Customer Feedback Data: Participants will develop the ability to interpret and analyze qualitative customer feedback data to extract valuable insights and identify areas for improvement.

  Target Audience:

• Customer Relationship Managers
• Business Intelligence Specialists
• Customer Service Representatives
• CRM Specialists and Managers
• IT Professionals with Data Management Roles Data Analysts
• Marketing Professionals
• Business Analysts
• Entrepreneurs and Business Owners
• Anyone interested in leveraging customer data for business growth and innovation.

Training Calendar:

⏱15th April 2024 – 19th April 2024

⏱ 6th May 2024 – 10th May 2024

⏱15th June 2024 – 19th July 2024

I. Introduction to Customer Data Analysis

• Overview of Customer Data Management (CDM)
• Importance of Customer Data Analysis in Business
• Role of Customer Data Analysts

II. Fundamentals of Customer Data Management

• Types of Customer Data (Structured, Unstructured, Behavioral, Demographic, etc.)
• Data Collection Methods and Tools
• Data Cleaning and Preprocessing Techniques
• Data Storage and Security Best Practices

III. Customer Analysis Metrics

• Key Performance Indicators (KPIs) in Customer Analysis
• Customer Lifetime Value (CLV) Calculation and Analysis
• Customer Churn Rate Analysis
• Customer Segmentation Techniques E. RFM (Recency, Frequency, Monetary) Analysis

IV: Customer Journey Mapping

• Importance of customer journey mapping in understanding customer behavior
• Techniques for mapping the customer journey across various touchpoints
• Analyzing customer journeys to identify pain points and areas for improvement

V. Customer Data Analysis Techniques

• Exploratory Data Analysis (EDA)
• Descriptive and Inferential Statistics for Customer Data
• Data Visualization Tools and Techniques
• Predictive Modeling for Customer Behavior Analysis
• Machine Learning Algorithms for Customer Data Analysis

VI. Advanced Topics in Customer Data Management and Analysis

• Sentiment Analysis of Customer Feedback
• Text Mining Techniques for Qualitative Data Analysis
• Social Media Analytics for Customer Insights
• Predictive Analytics for Customer Personalization E. A/B Testing and Experimentation for Customer Experience Optimization

VII. Qualitative Customer Feedback Analysis

• Understanding the importance of qualitative customer feedback
• Techniques for collecting and categorizing qualitative feedback data
• Analyzing qualitative feedback to extract actionable insights

VIII. Integrating Quantitative and Qualitative Analysis

• Strategies for integrating quantitative and qualitative customer data analysis
• Case studies demonstrating how combining both types of analysis can lead to deeper insights
• Best practices for incorporating feedback into decision-making processes

IX: Implementing Data-Driven Strategies

• Developing data-driven strategies for customer acquisition, retention, and loyalty
• Creating actionable insights from customer data analysis
• Practical exercises in developing and implementing data-driven strategies

X. Case Studies and Practical Applications

• Real-world Examples of Successful Customer Data Analysis Implementations
• Hands-on Exercises Using Customer Data Analysis Tools (e.g. Excel, PowerBI, Tableau)
• Group Projects to Apply Learned Concepts to Specific Business Scenarios

XI. Ethical Considerations in Customer Data Analysis

• Privacy Regulations (GDPR, CCPA, etc.) and Compliance
• Data Governance and Ethics in Customer Data Handling
• Bias and Fairness Issues in Customer Data Analysis

XII. Future Trends in Customer Data Analysis

• Emerging Technologies Shaping the Field (AI, IoT, Blockchain, etc.)
• Predictions for the Evolution of Customer Data Management and Analysis
• Continuous Learning and Professional Development Resources

XIII. Conclusion and Next Steps

• Recap of Key Learnings
• Actionable Steps for Implementing Customer Data Analysis Practices
• Resources for Further Learning and Skill Development

Delivery Method:

The course will be delivered through a combination of lectures, interactive discussions, hands-on exercises, case studies, and group projects. Virtual or in-person training sessions can be organized based on the participants' preferences and logistical considerations.

Certificate:

Participants will receive a career certificate upon successful completion of the course.

Note: The course outline can be adjusted based on the specific requirements of the training participants and the available time

For inquiries and registration, please contact us: