- Data Science
- Consumer Behaviour
Consumer survey information is a critical resource in understanding not only what your consumers are doing, but also why they are going it. The responses collected through these surveys can help compare consumer perception of product quality, pricing, and other key attributes among competing brands.
Given the dynamic requirements of surveys, designing robust data models to generate insights can prove to be challenging. Join us on the 20th of May, as we explore different analytical modelling approaches to study aspects of consumer behaviour, such as brand switching, movement across segments, and key drivers’ analysis.
What we will cover
Drawing from our experience, we will explore:
- Architecture design patterns featuring data engineering, data science, and data visualization components.
- Key business drivers and how we can ensure alignment to business operations when delivering decision-making systems.
- How you can leverage the power of Analytical Modelling to productionize key analyses.
Is it for you?
- Are you looking to get more value out of your consumer survey data?
- Have you been exploring modelling techniques and technologies to revamp your understanding of consumer behaviour?
- Would you like to learn about the business value of Machine Learning at-scale and how it can support decision making?