28 to 29 June 2018
22 to 23 November 2018
9.00 am to 5.00 pm
Data Analytics Consulting Centre
Department of Statistics and Applied Probability
Computer Laboratory 2 (S16-05-102)
Faculty of Science
6 Science Drive 2
This course uses data analytics to analyse customer lifetime value, identify high value customers, and customers to upsell and cross-sell to. This enables businesses to devise customer retention campaigns, customer profiling and segmentation strategies and product marketing strategies by deriving actionable insights through Association Rule Mining, descriptive statistics, Market Basket Analysis, RFM modelling etc.
• Cancellation before or on 15 March 2018: Full fee refund
• Cancellation between 16 to 31 March 2018: 50% fee refund
• Cancellation after 31 March 2018: No refund
• Introduction to data analytics
• Introduction to RFM modelling
• Customer profiling and segmentation
• Introduction to Customer Lifetime Value
• Introduction to Market Basket Analysis
• Introduction to Association Rule Mining
Prof Hargreaves is an analytics and business intelligence professional with over 28 years’ analytics experience. She has held leading roles in the pharmaceutical, healthcare, fast moving consumer goods and education industries.
Prof Hargreaves has worked with various leading companies to make businesses more intelligent. These include Pfizer, Novartis, MSD, Nestlè, MasterFoods, Goodman Fielder, Foxtel, Aztec (acquired by IRI), Cegedim Strategic Data (acquired by Quintiles IMS), the National Health and Medical Research Council and the National University of Singapore. Prof Hargreaves’ role includes analytics training, designing of analytics courses, and providing analytics advisory and consulting services. She is also a noted keynote conference speaker.
Prof Hargreaves has a passion for solving business problems using analytics and machine learning techniques to build data-driven solutions. Through faster and smarter business processes, her clients are empowered for organic revenue growth and to make effective decisions.