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:
1-The 3 main uses of data in marketing analytics:
- Model and describe behaviours / segment consumers
- Predict behaviours based on a set of variables
- Receive real-time information on consumer behaviours
2-The types of data used in quantitative marketing:
- Aggregate statistical/econometric data and time series
- Individual observations in data sets (survey data, databases, etc.)
- User generated content (text and images)
- Datafied objects
3-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.
4-The main statistical methods used in data analytics
5-The code languages used in advanced data analytics
6-Algorithms, machine learning, deep learning and artificial intelligence