OverviewCurriculum

Marketing, Customer and Social Media Analytics

Overview

In this fast growing industry of analytics (expected to grow to USD 200 B by 2020 from $130 B today), Marketing, Customer and Digital/Social media analytics is currently among top 3 niche areas of opportunity. As they say, Innovation and Effective sophistication command a premium, the holistic understanding of analytics in “Customer acquisition, retention, growth and support through online and offline medium” is that sophisticated but premium approach which every big organization is looking to deploy but very few could do it successfully.

This program aims to put you in that elite niche category who is able to understand & view holistic application of analytics across all stages of product and customer lifecycle and command a premium for oneself in the industry. As the tag line of this program says “Rock Solid and Scary Smart” , integrated strategy is indeed solid & smart.

Course Objectives

  • Practical usage of Decision Science in respective domain.
  • Learn data sources and its implications.
  • Learn about domain relevant tools and techniques.
  • Get hands on exposure to analytical tool R.

Key Features

  • Holistic approach encapsulating aspects of Marketing, Customer and Social Media Analytics.
  • Eminent academicians and practitioners as course advisors and faculties.
  • Program accredited and certified by Analytics Society of India.
  • Case study based approach.
  • Course pedagogy comprises of assignment()s and hands on project.
  • Non-disruptive weekend program.
  • Spans across 60 hours of 100% in classroom knowledge sharing.
  • V Connect – Acts as a platform to connect with industry experts and get mentored.
  • Route α – Your club to connect and progress.

Curriculum

Overview

  • Overview of Analytics.
  • Overview of Marketing, Customer and Social Media domains.

Fundamentals of Statistical analysis

  • Types of data, Central Tendencies, Central limit theorem, Probability distribution, Histogram, Hypothesis Testing, Sampling, Confidence Interval, Correlation.
  • Processes of data quality check, Missing data treatment/data imputation, Data transformation.
  • Data Exploration and Visualization.

Marketing and Customer acquisition analytics

  • Market Segmentation, Market Sizing & Forecasting.
  • Campaign optimization, Opportunity Identification & Conversion analytics.
  • Product/bundle Analytics, Behavioral Analytics, Campaign effectiveness, Store Design & Location, Sales Incentives.
  • Digital/ecommerce analytics supporting customer acquisition.

Customer retention analytics

  • Reward & Loyalty analytics, Customer lifetime value.
  • Customer Churn model, Recency,Frequency and Monetary Analysis.
  • Customer Retention Strategy.

Customer Value creation / Growth

  • Cross Sell / Up Sell Models – Market Basket analysis, Recommender system, Real time product targeting & pricing incentives.
  • Store display analytics, Revenue maximization.
  • Digital/ecommerce analytics supporting customer growth.

Customer Engagement and Support

  • Customer Relationship & Support analytics.
  • Customer Journey Mapping, Customer Experience/Perception analytics, Customer Experience vs Operational & Financial Goals.
  • Web scrapping, Social media and sentiment analytics.

Analytical techniques & Strategy for practical usage

  • Practical application of following analytical techniques using case studies for above topics using R :
    – Decision Tree
    – Machine Learning – Random Forest, Logistic regression
    – Classification & Clustering
    – Optimization