Monetizing your Enterprise Datasets

27 Apr 2019 | kuala lumpur
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Course Objectives

  • Direct marketing via customer segmentation
  • Customer loyalty prediction
  • Product upsell/cross-sell recommendation engine
  • Sales and marketing forecasting engine


This one-day course prepares business professional ways to harness the advantages with ready available data from applications like CRM, ERP, POS, MRP and HRM. Relevant datasets for each application will be presented, along with the layman illustration of the step-by-step process in creating and deploying the predictive models.

Target Audience

This course is suggested for C-level executives, sales manager, marketing manager, and other senior management personnel.

Training Outline

Introduction to data analytics
  • The variety of data
  • The types of analytics
  • The importance of data to enterprises
  • Identifying data opportunities
  • The best practices to initiate data analytics initiatives

Case Study 1: Data Analytics for Retail/Wholesale Businesses

Market Basket Analysis
  • Market Basket Analysis – identify upsell/cross-sell potential with historical purchase transaction data to generate extra revenue
  • Data sources: CRM, POS
Customer Segmentation
  • Customer Segmentation – identify groups of customers with similar behaviors to align respective marketing strategies and ultimately improve rates of successful sales
  • Data sources: CRM, MRM
Sales Forecasting
  • Sales Forecasting – accurately predict sales performance and profit margins based on seasonal trends and stages of sales funnels
  • Data sources: CRM, ERP, Accounting Systems

Case Study 2: Data Analytics for the Services Industry (e-Commerce, Telco, Banking)

Customer Profiling
  • Customer Profiling – identify the key-drivers in customers’ decision-making process to improve customer experience and revenue
  • Data sources: CRM, POS, ERP, Machine Logs
Churn Prediction
  • Churn Prediction – predict customer lifetime and implement preventive strategies to ensure high customer retention
  • Data sources: CRM, POS, ERP, Machine Logs
Social Media Analytics
  • Social Media Analytics – grasp the real-time trends in your business/industry and align your corporate strategy on the move
  • Data sources: Web, Media, Social Media


With the business objective to growth sales and reduce cost.