Understand how data analytics, machine and deep learning methods on large volumes of structured or unstructured data allow to better model, predict or describe consumer behaviour. Understand how data analytics based modelling impacts marketing decisions and how recent advances are changing market research and marketing science.
Course outline:
- The 3 main uses of data in marketing analytics:
o Model and describe behaviours / segment consumers
o Predict behaviours based on a set of variables
o Receive real-time information on consumer behaviours
- The types of data used in quantitative marketing:
o Aggregate statistical/econometric data and time series
o Individual observations in data sets (survey data, databases, etc.)
o User generated content (text and images)
o Datafied objects
- How data is changing and why: from solicited to unsolicited, from structured to unstructured, from manual datafication to algorithm-led datafication, from text to data, etc.
- The main statistical methods used in data analytics
- The code languages used in advanced data analytics
- Algorithms, machine learning, deep learning and artificial intelligence