The combination of (longitudinal) household and retail scanner data and modern time series techniques offer the unique potential to separate cause and effect of marketing actions and phenomena in the marketplace. It allows us to separate short-run from long-run effects of marketing actions, and to quantify those effects on sales, market share and profitability. Current research aims at refining those models to incorporate different reactions, such as from competitors, to study marketing actions and reactions for several brands in relation to each other, to examine nonlinear response patterns, and to use individual-level data of consumers rather than store level or market-level data to study market change processes.
Our published and under construction work on Time Series Analysis.
AiMark 