We’re happy to announce that we will kickstart our first Marketing Analytics course on February 23 – March 10, 2018. In addition to this, we’re fortunate to have two esteemed instructors to lead the course; Nadav Rindler and Teng Chan Leong. Nadav Rindler is a data scientist at one of the largest non-profit organizations in the US, where he leverages statistics and machine learning to extract insights from data on more than 90 million donors. He specializes in marketing analytics with expertise in predictive modelling, data visualization, mapping, and R programming, and Teng Chan Leong is an experienced digital strategist with a demonstrated history of a multinational conglomerate and successful startups. He is also a technology enthusiast with a strong business process knowledge, digital strategy, digital marketing, social media strategy, analytical thinking, problem-solving, and data analytics.

Our pricing:

  • All day pass (this applies only to one day class from 9 am to 5 pm): RM500
  • Part I stand alone package: RM1,500
  • Part II stand alone package: RM1,500
  • Part I + II combo: RM2,500

Additional note: this course is not HRDF claimable

Registration for the course: https://goo.gl/forms/sJpApJ1yKfxHc3To2

Our course includes:

  • Course materials
  • Certificate of participation

The requirement of participation:

  • Open mind
  • Laptop

Course pace:

  • Beginner level

Venue: MITIN Conference Center, Taman Desa

Course time frame:

  • 9 am – 5 pm

Course dates:

  • Part I: Marketing analytics – February 23, 24, 25 & March 2
  • Part II: Digital marketing – March 3, 4, 9 & 10

Course outline:

  1. Part I: Marketing analytics
    • Introduction to business analytics
      • Overview of business analytics and course syllabus
      • Industry trends and case studies
      • How to build an analytics team
      • Hands-on exercise: TBD
    • Customer segmentation and profiling
      • Methodologies for segmentation (e.g. RFM), from business rules to clustering algorithms
      • Leveraging internal and external data sources to improve visibility into customer behavioural preferences, demographics, and psychographics
      • Hands-on exercise: Customer segmentation using clustering
    • Customer lifetime value
      • Overview of CLV. How and why companies use CLV – from customer segmentation to optimizing marketing investment for each customer
      • Investigate the variety of ways to calculate CLV, from simplistic heuristics to predictive analytics
      • Hands-on exercise: Design a methodology and use it to calculate customer CLV
    • Predictive analytics for acquisition, retention, cross-promotion, and upselling
      • Why, when and how to use predictive modelling for marketing
      • Overview of predictive modelling techniques and software programs used to predict customer behaviour.  Deep dive into regression and decision tree algorithms
      • Hands-on exercise: Build model to predict customer retention
  2. Part II: Digital marketing
    • Google Analytics
      • Introduction to Google Analytics and Google Tag Manager
      • Web analytics – how to measure web performance
      • UTM parameters
      • Dashboard and Reports
      • Hands-on: Channel and campaign performance analytics
    • Consumer purchase journey mapping (online to offline) and customer insights
      • Customer journey map
      • Touchpoints and attribution models
      • Customer 360 – matching offline visits to online visits
      • Analysing consumer research data and managing CRM data
      • Significance, outliers,
      • Hands-on: Modeling touchpoints attribution / analysing survey data
    • Performance driven email marketing
      • Email marketing performance metrics (send, open, clicks, uniques)
      • Audience segmentation and subscriber scoring
      • A/B testing
      • Hands-on: Analyzing audience profile
    • Digital advertising performance analytics (multi-channel ad campaign analytics)
      • Understanding CPC, CPV, CTR, CPA/CPL, ROAS
      • Attribution models
      • Setting the right campaign goals
      • Combining FB ads, Google ads, Email and survey data
      • Hands-on: Trend analysis for campaign performance


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