Case studies/Causal AI Case-Study
Understanding the drivers of demand.
Building materials · 2023
Challenge
Sales volumes fluctuated strongly over time. The client wanted to understand why, and how demand could be stabilised and increased.
Solution
Existing data on sales volumes, prices, and marketing activity were cleaned and enriched with external data such as competitor prices, macroeconomic indicators, and Google Trends. Based on expert knowledge and algorithms, a directed acyclic graph (DAG) was built that maps the causal relationships of demand.
Impact
The key demand drivers were identified and explained, a robust forecast model was created, and optimal pricing for profit maximisation was determined.