Applied Analytics (business application - non mathematical) (Udemy.com)

Basics of Risk, Marketing, Collections, Operations & Fraud Analytics. Know the objective, techniques & Success stories

( 38 Reviews )

Created by: Gopal Prasad Malakar

Produced in 2021

What you will learn

Learn about wide applicability of analytics across various industries
Learn that analytics results in win-win scenario (good for customer and firm)

Quality Score

Content Quality

Video Quality

Qualified Instructor

Course Pace

Course Depth & Coverage

Overall Score : 74 / 100

Course Description

What is this course about?
Part 1 of this course is all about applied analytics (by business analytics verticals)

Course Overview : Basics of Risk, Marketing, Collections, Operations & Fraud Analytics. Know the objective, tools & techniques used.
Birds Eye View of Analytics Verticals, their goals and inter linkage - Which are the analytics vertical. What are their primary goals.
Common Industry Terms - Understand terms like Loan types, billing cycle, due date, delinquency etc.
Marketing Analytics Overview - Objective and levers - what is the objective of marketing analytics. What are there main levers.
MA 01 Increase / Maintain Base (more new customer, stop customer churn / attrition) : Marketing Analytics 01 - How can you maintain & increase customer base. What metrics you should look. What are the applicable techniques.
MA 02 Increase Revenue per customer (cross sell ) - Marketing Analytics 02 A - How to increase revenue per customer through xsell
MA 03 Marketing Campaigns and it's effectiveness measurement - Marketing Analytics 02 B -what is campaign? How do you measure campaign effectiveness
Risk Analytics Overview - Objective and levers - What is primary goal of risk analytics?
RA 01 Application Approval n Application Fraud prevention - Understand about 1. application approval process and 2. application fraud prevention
RA 02 Authorization & Transaction Fraud prevention - Prevent bad usage of the card and prevent transaction fraud
RA 03 Credit Limit Management - CLI (Credit Limit Increase) and CLD (Credit Limit Decrease)
Collections Analytics Overview -
CA 01 Best Practices of Collections Strategy for Early / Middle Late stage accounts-Understand two different school of thoughts for collection
CA 02 Collections Operations - how to contact & understand training needs of agents
Customer Services (find what customer wants) or Operations Analytics (detect internal fraud)

Part 2 of this course is a collection of case study on analytics from various industries. It will help users to know about how analytics has helped to meet customer demand with efficiency. It has

Case Study from Health Care Industry
Case Study from Telecom Industry
Case Study from Automobile Industry
Case Study from Transport Industry
Case Study from Electroni Case Study Industry
Case Study from Entertainment Industry
Case Study from Retail Chain Industry
Case Study from Sport Industry
Case Study from Cement Supply Business
Case Study from On Line Business
Case Study from Google Apps
Case Study from Contact Center

Terminology To be used by Target Audience to find this course

Analytics Case Study
Analytics Case Studies
Case Study on Analytics
Case Studies on Analytics
Analytics success stories
Using Analytics for customer success
Analytics applications
Application of Analytics

Course Contents
Course contains HD videos and PDF file.
Course Duration
Ideally it should take just 4 hours to complete it.
What is in it for the reader
Reader will get to know, how analytics has resulted into many success stories. It has created a win-win situation where customer is happy and firm is gaining.

Why Take this course?
This ensures that you get to know wide applicability of analytics across various industries. It is a collections of many popular analytics success stories.Who this course is for:

Those who wishes to know about analytics usage
Those who wishes to learn about sucess stories of analytics application

Time: 2.5h

Instructor Details

Gopal Prasad Malakar

3.7 Rating
38 Reviews

I am a seasoned Analytics professional with 18+ years of professional experience. I have industry experience of impactful and actionable analytics, data science, decision strategy and enterprise wise data strategy.
I am a keen trainer, who believes that training is all about making users understand the concepts. If students remain confused after the training, the training is useless. I ensure that after my training, students (or partcipants) are crystal clear on how to use the learning in their business scenarios.
My expertise is in Credit Card Business, Scoring (econometrics based model development), score management, loss forecasting, business intelligence systems like tableau /SAS Visual Analytics, MS access based database application development, Enterprise wide big data framework and streaming analysis.
Please refer to my course for
- SAS / R program details (syntax and options)
- SAS / R output deep dive
- Practical usage in Industrial situation