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Instructor

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Dr. Carol Hargreaves

Dr. Carol Hargreaves, is the founder of Business Data Analytics Solutions Pvt. Ltd. Born leader with a passion for solving business problems using analytics & machine learning techniques, she has built several data driven systems that deliver organic revenue growth and enable decision making within businesses. Her solutions allow business processes to become smarter and faster while keeping customers engaged & delighted Dr. Hargreaves holds a PhD in Statistics and an MBA from the University of Wales (Cardiff). She was awarded the Foundation of Research and Development Scholarship in 1988. As an Analytics and Business Intelligence professional with over 27 years of work experience, she has held leading roles in the pharmaceutical, healthcare, fast moving consumer goods industry & the education Industry. An excellent Analytics Instructor for solving hands-on real world business problems. Dr. Hargreaves has worked with a variety of leading companies like Pfizer, Novartis, Merck Sharp & Dohme, Nestle, MasterFoods, Goodman Fielder, Foxtel, Aztec (IRI), Cegedim Strategic Data (Quintiles-IMS), National Health & Medical Research Council, University of Sydney and National University of Singapore.

Churn Analysis: How to Increase Your Sales by Managing Your Churn

Instructor: Dr. Carol Hargreaves

Learn how to use a data driven approach to prevent customers from leaving you

  • Gain in-depth knowledge of which customers are likely to churn based on implementing logistic regression models.
  • Instructor has worked with  Pfizer, Novartis, Merck Sharp & Dohme, Nestle, MasterFoods, Goodman Fielder, Foxtel, Aztec (IRI), Cegedim Strategic Data (Quintiles-IMS), National Health & Medical Research Council, University of Sydney, National University of Singapore.

Course Description

This course looks at what is churn and how to identify which customers are likely to leave you. It also looks at the factors that are likely related to churn and how to reduce churn. The course concludes with the benefits of churn and goes into detail on how to predict which customers are likely to churn using a Logistic Regression Model. We end the course with methods on evaluating churn models for their business effectiveness and accuracy.

What am I going to get from this course?
At the end of this course students will understand:
  • What is Churn
  • The overall benefits of Churn
  • Which factors are likely related to Churn
  • How to reduce Churn
  • How to prevent Customers from leaving them
  • How to calculate Churn
  • How to evaluate Churn Models for their business effectiveness and accuracy

Prerequisites and Target Audience

What will students need to know or do before starting this course?
There are no pre-requisites for this course. This course is an introductory course. It is for students of all levels.
Who should take this course? Who should not?
This course is an introductory course. It is for all students who work in the Retail, Financial or Telecommunications Industries who are interested in learning more on how to prevent customers from leaving their business. 

This course is also for data analysts, data scientists and data modellers who would like to understand what is churn, what are the benefits of churn for the business, how to run Logistic Regression Models and how to evaluate the business effectiveness and accuracy of churn models.

Curriculum

Module 1: Introduction
Lecture 1 Course Overview & Objectives
01:28

Highlights what the learner will be able to do by the end of the course.

Lecture 2 What is Churn?
02:13

Defines Churn. Provides a definition for the Churn Rate and discusses what is an acceptable Churn Rate. Concludes with how changes in the Churn Rate impact business.

Lecture 3 Why do Customers Churn?
03:52

Highlights some of the reasons why customers churn. For example, Bad On-boarding, Bad Customer Service, Lack of Ongoing Customer Success, Natural Causes, etc

Quiz 1 Module 1 Quiz

Module 2: Customer Churn
Lecture 4 Types of Customer Churn
02:07

Describes what is Negative Churn, Voluntary Churn and Involuntary Churn

Lecture 5 How to Calculate Customer Churn
02:21

Gives the method for calculating customer churn rate.

Lecture 6 Why Calculate Customer Churn?
02:14

Gives examples why business needs to calculate Customer Churn

Lecture 7 Tactics for Reducing
03:47

Churn Gives examples how business can reduce Customer Churn.

Quiz 2 Module 2 Quiz
Module 3: Customer Lifetime Value
Lecture 8 Customer Lifetime Value
04:33

Defines Customer Lifetime Value and describes the impact of Customer Lifetime Value on business. Provides the relationship between the Customer Lifetime Value and the Churn Rate.

Lecture 9 How to Calculate Customer Lifetime Value
02:17

Gives the formula for calculating Customer Lifetime Value

Quiz 3 Module 3 Quiz
Module 4: Latency
Lecture 10 What is Latency?
05:45

Defines what is Latency and gives an example on how to calculate Latency.

Lecture 11 What are the Benefits of Calculating Latency?
11:07

Describes the benefits of calculating Latency with a focus on how the Latency metric can help the business to make key decisions as to whom to market the Retention Campaign to.

Quiz 4 Module 4 Quiz
Module 5: Churn Analysis/Regression Techniques
Lecture 12 Churn Analysis in the Telecommunication Industry
01:39

Background information on Churn in the Telecommunication Industry

Lecture 13 Churn Analysis using the Logistic Regression Technique
03:48

An introduction to the Logistic Regression Technique.

Lecture 14 Preparing the Data for the Logistic Regression
08:36

A brief description on Data Preparation. This includes how to do data cleaning, data relevancy check, de-duplication, outlier check and handle missing values.

Lecture 15 Data Partitioning for the Logistic Regression Technique
01:51

This lecture describes how to divide the data set into a training data set and a test data set.

Lecture 16 Data Balancing of the Logistic Regression Technique
04:11

A brief description on how to balance your data output classes for optimal results

Quiz 5 Module 5 Quiz
Module 6: How to Build & Interpret the Logistic Regression Model
Lecture 17 Identifying the Significant Variables for Churn
03:12

Uses the Wald Test coefficient summary output table to explain how the significant values and the signs of the coefficients are important metrics to determine whether a variable contributes to the outcome of interest and whether the model is likely reliable and optimum.

Lecture 18 Interpreting the Odds Ratio
02:52

Describes how to interpret the odds ratio and relate it to the business for decision making.

Quiz 6 Module 6 Quiz
Module 7: Evaluating the Churn Model Accuracy
Lecture 19 Evaluating the Churn Model - Accuracy
06:16

This lecture looks at how we use the Confusion Matrix, the sensitivity and specificity of the model to measure model accuracy .

Lecture 20 Evaluating the Churn Model - Receiver Operating Curve (ROC)
01:48

The Receiver Operating Curve helps you to determine the threshold value for classification and helps you to better understand the trade-offs for the sensitivity and specificity measures.

Lecture 21 Evaluating the Churn Model - Area Under the Curve (AUC)
00:54

This lecture describes the Area Under the Curve method for assessing the accuracy of the Churn Model. The closer the value is to 1, the more accurate is the model.

Lecture 22 Evaluating the Churn Model - Lift Charts
02:40

This lecture helps us to see how we can use Lift Charts to determine effectiveness of the predictive model against a random model.

Quiz 7 Module 7 Quiz

Reviews

4 Reviews

Empty user
Kamal K

August, 2017

By understanding the way a data driven approach can prevent customers from leaving, I am now able to implement the in-depth knowledge I learned from this course. I definitely recommend this course if you are getting started with how to increase your sales by managing your churn, and want to kick-start your learning.

Empty user
Michael B

August, 2017

It is really an interesting course to learn methods of evaluating churn models for our business effectiveness and accuracy. The step-by-step method of learning churn, its benefits, churn related factors and calculating churn is excellent

Empty user
Andrew A

August, 2017

A very nice overview for someone new to sales. I loved the different levels of learning geared towards achieving proficiency in sales and related churn Models for business effectiveness and accuracy. I liked the trainer’sr approach to the subject matter and given examples were clear and concise.

Empty user
Jay J

August, 2017

I really enjoyed the course, it has a lot of useful tips and tricks and is informative for a Churn analysis newbie. The instructor definitely keeps you engaged throughout the course showing, and it is definitely a course that I will go through again to cement my understanding of how to create churn analysis

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