Description
Predictive Customer Analytics is a course on using data analytics and machine learning techniques to understand customer behavior and make data-driven business decisions, published by Udemy Online Academy. Designed for data analysts, business analysts, marketers, data scientists, and customer success professionals, this course teaches how to transform customer data into actionable insights to improve acquisition, retention, and revenue. Individuals will learn about customer segmentation, predictive modeling, churn prediction, customer lifetime value (CLV), recommender systems, forecasting, feature engineering, data visualization, and model evaluation using real-world datasets. What sets this course apart is its focus on practical, easy-to-implement techniques that don’t require programming knowledge. You’ll learn how to use advanced Excel features to quickly achieve accurate, actionable results.
Predictive customer analytics helps you stay ahead of your competition by predicting customer decisions, improving customer retention, and driving targeted marketing strategies. This course will teach you how to use Excel as a powerful tool to build machine learning predictive models and forecasting techniques, even if you’re not a data science expert. Using Excel, a tool that most professionals are already familiar with, you can gain deeper insights into customer data and enable better decision-making without the need for advanced technical skills. From forecasting sales trends to retaining key customers, predictive analytics is a game-changer for businesses looking to grow and scale.
What you will learn in Predictive Customer Analytics:
- Master the use of linear regression in Excel to predict customer behavior.
- Explore the use of logistic regression to predict customer churn and retention strategies.
- Analyze customer data using clustering techniques to segment customer groups.
- Build sales forecasting models using Excel Solver and time series analysis.
- Implement XLSTAT for advanced statistical analysis of customer forecasts.
- Develop and run logistic regression models using Excel macros for automation.
- Predict future customer behavior with incremental and multiplicative time series models.
- Interpret the results of regression and clustering models for actionable business decisions.
- Evaluate the effectiveness of your forecasting models in improving customer retention and business strategies.
- And…
Course specifications
Publisher: Udemy
Instructors: Start-Tech Academy ,Pukhraj Parikh and Abhishek Bansal
Language: English
Level: Introductory to Advanced
Number of Lessons: 29
Duration: 3 hours and 23 minutes
Course topics on 2026/4
Predictive Customer Analytics Prerequisites
A PC/ laptop with good internet connection and MS Excel installed on it
Pictures
Predictive Customer Analytics introduction video
Installation guide
After Extract, watch with your favorite Player.
Subtitle: None
Quality: 720p
Downloadly link
Rapidgator link
File password (s): www.downloadly.ir
Size
1.4 GB