Seminar – Flexible demand estimation with search data

Stephan Seiler, Associate Professor, Imperial College London

Traditional methods for estimating demand are not always well-suited to online markets, where individual products are sold infrequently, unobserved factors such as webpage layout drive substitution, and often only a limited set of product characteristics is observed. We propose a demand model where browsing data – which is abundant in many online settings – is used to infer individual consumers’ consideration sets. In our model, the underlying variables which drive consideration can be correlated arbitrarily across products. We estimate the model through a constraint maximisation approach, based on the insight that these correlations should rationalise the product-pair co-search frequencies that are observed in the data. In turn, these correlations make it possible to estimate more flexible substitution patterns. We apply the model to data from an online retailer, recover the elasticity matrix, and solve for optimal prices.

There will be a light lunch served at the seminar.

Speaker bio

Stephan Seiler is an Associate Professor of Marketing at Imperial College. He is also an Associate Professor of Economics (by courtesy) at Imperial College and a Research Fellow at the Centre for Economic Policy Research (CEPR), the CESifo Research Network, and the Institute for Fiscal Studies (IFS). Professor Seiler received his PhD from the London School of Economics and was previously employed at Stanford and UCLA. He was named a Marketing Science Institute “Young Scholar” as well as subsequently an MSI “Scholar” and has won several best paper awards in marketing and economics. In 2020 he was awarded a Faculty Excellence Award for teaching in the Master of Science in Business Analytics program at UCLA. He is currently an Associate Editor at Marketing Science, Quantitative Marketing and Economics, and the Journal of Industrial Economics. He co-organises the European Quant Marketing Seminar series and he serves as a Public Editor at Quantitative Marketing and Economics.

His research focuses on consumer choice in various markets. He analyses issues ranging from the choice of hospital for a bypass operation to the reaction of consumers to promotions of laundry detergent. He is particularly interested in understanding consumer search behaviour, such as how informed consumers are about prices or other product characteristics when making a purchase decision. Another strand of his research analyses the production and impact of user-generated content on platforms such as Wikipedia and Twitter.

For more information, please get in touch with Luke Slater.