Overview of Risk, Marketing, Collections analytics etc.

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

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Overview of Risk, Marketing, Collections analytics etc.

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)

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 Should Attend!

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

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Tags

  • Business Analytics
  • Business Idea Generation
  • Marketing Analytics
  • Fraud Analytics

Subscribers

4675

Lectures

36

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