Predictive Customer Analytics

Build predictive machine learning and forecasting models in Excel to build customer decision and customer behavior

What you'll learn

Discover how to preprocess customer data for predictive modeling using Excel.

Master the application of linear regression in Excel to predict customer behavior.

Explore the use of logistic regression for customer churn prediction and retention strategies.

Analyze customer data using clustering techniques to segment customer groups.

Build sales forecasting models using Excel’s Solver and time series analysis.

Implement XLSTAT for advanced statistical analysis in customer predictions.

Develop and run logistic regression models using Excel Macros for automation.

Predict future customer behavior with additive and multiplicative time series models.

Interpret the results of regression and clustering models to make actionable business decisions.

Evaluate the effectiveness of your predictive models in improving customer retention and business strategies.

Requirements

A PC/ laptop with good internet connection and MS Excel installed on it

Description

Are you an aspiring data analyst or business professional looking to make data-driven decisions that impact customer behavior and retention? Do you want to leverage Excel to build predictive models without the complexity of advanced coding? If yes, this course is for you.In today’s competitive market, understanding customer behavior is key to business success. Predictive Customer Analytics helps you stay ahead by forecasting customer decisions, improving retention, and driving targeted marketing strategies. This course will empower you to use Excel as a powerful tool for building predictive machine learning models and forecasting techniques, even if you’re not an expert in data science.In this course, you will:Develop a solid understanding of linear and logistic regression techniques in Excel to predict customer behavior.Master clustering techniques for customer segmentation, identifying key groups within your customer base.Build sales forecasting models using Excel’s Solver and time series methods.Implement real-world solutions with case studies, such as predicting customer churn and segmenting customers for better marketing strategies.Why is Predictive Customer Analytics so important? By using Excel, a tool most professionals are already familiar with, you can unlock deeper insights into customer data, enabling better decision-making without needing advanced technical skills. From forecasting sales trends to retaining key customers, predictive analytics is a game-changer for businesses looking to grow and scale.Throughout the course, you will complete hands-on exercises in Excel, including:Preprocessing customer data for linear and logistic regressionBuilding predictive models using XLSTAT and Excel MacrosClustering customer data for segmentation analysisImplementing time series forecasting to predict salesWhat sets this course apart is its focus on practical, easy-to-implement techniques that don’t require programming knowledge. You’ll learn how to utilize Excel’s advanced features to get accurate, actionable results quickly.Ready to transform your customer insights? Enroll today and start building your own predictive models in Excel!

Overview

Section 1: Introduction

Lecture 1 Introduction

Lecture 2 Course resources

Lecture 3 The Importance of Predictive Customer Analytics

Lecture 4 Types of Predictive Models

Lecture 5 Sneak Peek into the Course

Section 2: Fundamentals of Linear Regression

Lecture 6 Introduction to Linear Regression

Lecture 7 Conceptual Understanding of Linear Regression

Lecture 8 Understanding the output of Linear Regression

Lecture 9 Understanding the Data for Linear Regression

Lecture 10 Data Preprocessing for Linear Regression

Lecture 11 Interpreting Linear Regression Outputs

Lecture 12 Making Predictions with Linear Regression

Lecture 13 Implementing Linear Regression using XLSTAT

Section 3: Customer Retention and Logistic Regression

Lecture 14 Customer Retention: Key Insights

Lecture 15 Introduction to Logistic Regression

Lecture 16 Understanding the Confusion Matrix

Lecture 17 Case Study: Logistic Regression for Customer Churn

Lecture 18 Implementing Logistic Regression using XLSTAT

Lecture 19 Logistic Regression using Macros

Section 4: Customer Segmentation with Clustering

Lecture 20 Introduction to Clustering

Lecture 21 K-Mean Clustering basics

Lecture 22 Case Study: Clustering for Customer Segmentation

Lecture 23 Implementing Clustering using XLSTAT

Section 5: Forecasting Techniques

Lecture 24 Introduction to Forecasting

Lecture 25 Sales Forecasting

Lecture 26 Additive time series model in Excel

Lecture 27 Multiplicative time series model in Excel

Section 6: Conclusion

Lecture 28 About your certificate

Lecture 29 Bonus lecture

Marketing professionals who want to use data to predict customer behavior and enhance targeted campaigns.,Sales managers looking to forecast sales trends and improve customer retention strategies.,Data analysts who want to build predictive models in Excel without needing complex coding skills.,Small business owners aiming to make data-driven decisions to optimize customer acquisition and retention.