Predictive Customer Analytics (Udemy.com)
Build predictive machine learning and forecasting models in Excel to build customer decision and customer behavior
Created by: Start-Tech Academy
Last updated April 2026
What you will 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.
How it compares
Against the other 107 rated Udemy courses in Sales on CourseDuck:
- Rating4.6 out of 5higher than 64% of them
- Reviews136#91 of 108 by number of reviews
- Length3.5 hourslonger than 66% of them
- Last updatedApril 2026more recently than 70% of them
Course 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 regression
Building predictive models using XLSTAT and Excel Macros
Clustering customer data for segmentation analysis
Implementing time series forecasting to predict sales
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 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!
Instructor Details
- 4.6 Rating
136 Reviews
Start-Tech Academy
Start-Tech Academy is a technology-based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.
Our top quality training content along with internships and project opportunities helps students in launching their Analytics journey.
Founded by Abhishek Bansal and Pukhraj Parikh.
Working as a Project manager in an Analytics consulting firm, Pukhraj has multiple years of experience working on analytics tools and software. He is competent in MS office suites, Cloud computing, SQL, Tableau, SAS, Google analytics and Python.
Abhishek worked as an Acquisition Process owner in a leading telecom company before moving on to learning and teaching technologies like Machine Learning and Artificial Intelligence.
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Reviews
By Luleka Righteous Khumalo on 9/21/2026
Clear and concise and engaging
By Hoàng Anh Lê on 2/1/2026
Clear explanation of the concepts and excel tools as well
By Tracee Fry-Annan on 1/23/2026
I am enjoying it so far - explanations are clear and easy to follow
By M Ruslianor Maika on 8/7/2025
Detail dan easy to understand
By Prashant Auti on 5/29/2025
Great course! What I loved the most about this course is direct hands on experience on various analytics techniques by demonstrating an example. I have a constructive suggestion - Please use free plugins or do entire calculations in excel so that students can also follow the steps. And don't worry about the time (for Excel calculations) - even if the video gets a bit lengthy, it is fine.
By Shweta Sharma on 2/6/2025
It's a good course but quite limited. Can be a good resource for beginners.
By Amy Dang on 2/6/2025
Good content. The problem is the course use XLSTAT, I don't think many people want to spend extra money to buy that if they only use them for work. So, basically, topics that use XLSTAT have no use for students
By Amantle Mphoeng on 1/17/2025
Well articulated & well structured lectures... i learnt a lot
By Bashir Halilu Ibrahim on 12/18/2024
Interesting course
By Anonymized User on 11/22/2024
Very informative training!
Quality Score
No CourseDuck member has rated this course yet. Taken it? Give each part a thumbs up or down.
Overall Score : 92 / 100












