Understanding the effectiveness of various marketing channels is crucial to maximise the return on investment (ROI). However, the limitation of third-party cookies and an ever-growing focus on privacy make it difficult to rely on basic analytics. This talk discusses a pioneering project where a Bayesian model was employed to assess the marketing media mix effectiveness of WeRoad, an innovative Italian tour operator.

The Bayesian approach allows for the incorporation of prior knowledge, seamlessly updating it with new data to provide robust, actionable insights. This project leveraged a Bayesian model to unravel the complex interactions between marketing channels such as online ads, social media, and promotions. We'll dive deep into how the Bayesian model was designed, discussing how we provided the AI system with expert knowledge, and presenting how delays and saturation were modelled.

Attendees will walk away with:

- A simple understanding of the Bayesian approach and why it matters.
- Concrete examples of the transformative impact on WeRoad's marketing strategy.
- A blueprint to harness predictive models in their own business strategies.

First delivered at PyData Milan 2024, Italy
Also delivered at PyData Berlin 2024, PyData Paris 2024, WeMakeFuture Bologna 2024
Recorded session at https://youtu.be/k2LDWMLZQ8k?si=ViXHKVje9mOC0IL5