Master Sales & Service Data: From Insights to Actionable Strategies

What you will learn:

Data Analysis Techniques
Data Acquisition & Cleaning
Sales & Service Data Analysis
Sales Forecasting & Performance Metrics
Customer Behavior & Retention Strategies
Data-Driven Decision Making
Proficiency in Excel, SQL, Python, R, & Tableau
Customer Segmentation & Analysis
Churn Prediction & Prevention
Improving Customer Service Efficiency

Description

Unlock the power of data to revolutionize your sales and service strategies!

This comprehensive program equips you with the essential skills to analyze sales and service data, transforming raw information into actionable insights. We go beyond basic data analysis, focusing on practical applications for driving sales growth, enhancing customer experience, and optimizing business processes.

You'll gain hands-on experience with industry-leading tools like Excel, SQL, Python, R, and Tableau, mastering techniques for data collection, cleaning, statistical analysis, visualization, and predictive modeling. Learn to perform customer segmentation, sales pipeline analysis, churn prediction, and much more. This program isn’t just theory; it's designed to make you a confident, data-driven decision-maker.

Developed by the MTF Institute, a global leader in business education with partnerships like IBM, Intel, and Microsoft, this course is taught by Dr. Alex Amoroso, a renowned expert in research methodologies and business strategy. Benefit from her years of academic and industry experience, transforming your career and your organization's performance.

Who should take this course? Sales professionals, customer service managers, business analysts, marketing professionals, anyone aiming to leverage data for improved business outcomes. No prior data analysis experience is required; we start with the fundamentals and build your expertise incrementally.

Enroll now and start your journey to becoming a true data-driven expert!

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Curriculum

Introduction

This introductory section sets the stage for your data analysis journey. The "Onboarding to the Learning Process" lecture guides you through the course structure, while the "Welcome to MTF" lecture provides an overview of the MTF Institute and its commitment to excellence in business education.

Data Analysis Fundamentals

This core section lays the foundation for your data analysis skills. Lectures cover data collection and acquisition, data cleaning and preparation, exploratory data analysis (EDA), statistical analysis, data visualization, predictive analytics, data interpretation and reporting, data privacy and ethics, and the essential tools and software (Excel, SQL, Python, R, Tableau). You'll also learn how to build a compelling data analyst portfolio and understand current career trends. Finally, practical exercises solidify your learning.

Hands-on Tool Proficiency

This practical section dives deep into industry-standard tools. You'll engage in hands-on exercises using Excel, SQL, Python, R, and Tableau. Each tool section includes a lecture providing an overview and practical tasks to test your understanding, covering data manipulation, analysis, and visualization techniques. This ensures you're confident using these tools for real-world data analysis challenges.

Data-Driven Decision Making

This section transforms your data analysis skills into impactful decision-making capabilities. Topics covered include understanding the data landscape, descriptive, diagnostic, predictive, and prescriptive analytics, building a data-driven culture, and leveraging technology for effective decision-making. Case studies illustrate real-world application of these principles.

Sales & Service Data Analysis & Analytics

This specialized section applies your data analysis skills to the sales and service domains. You'll learn to identify key metrics and KPIs, analyze customer feedback and support data, understand sales trends and patterns, perform sales pipeline analysis and conversion rate optimization, analyze customer lifetime value (CLV), conduct sentiment analysis, implement personalization strategies, predict and prevent customer churn, optimize workflows, and improve customer support efficiency. Lectures also cover data sources and quality management within the sales and service context.

Interactive Conclusion

This final section provides an interactive review and wraps up the course with guidance for your next steps in your data analysis career. It reinforces the key learnings and provides resources to continue your professional development.