Nathaniel Forde

How much would the sales of Corn Flakes fall if a competitor cut prices by 10%? Answering this requires a demand model, but real markets are full of things nobody observes: how much each individual cares about price versus quality, the unmeasured "appeal" of a product that drives both its price...

Dynamic Path Analysis (DPA) extends survival analysis with a causal, time-varying perspective. This allows causal effects to be decomposed into direct and indirect pathways that evolve over time.

Along with the computational advancements that have enabled efficient Bayesian modelling in Python through packages like PyMC, PyStan and Numpyro, there has been an accompanying refinement of the Bayesian modelling workflow. In particular the methodological approach to model development has...

Consumer choice models are an important part of product innovation and market strategy. In this talk we'll see how they can be used to learn about substitution goods and market shares in competitive markets using PyMC marketing's new consumer choice module.

There is more to causal inference in industry than A/B testing. Often you will want to assess process change where a control group split is wasteful or unethical. To accommodate these questions we can use quasi-experimental causal inference techniques of the kind implemented in CausalPy....

A presentation on the complexities and subtleties of modelling discrete choice scenarios e.g. estimating the impact of pricing shifts on market share in a product choice offerings. We will discuss the history and uses of these types of models in marketing and upsell contexts. We will show how to...