B1732
Title: Estimating the effectiveness of a digital commerce advertising campaigns using a Geo-experiment
Authors: Iman Al-Hasani - Durham University (United Kingdom) [presenting]
Abstract: A Geo-experiment is an approach used to measure the effectiveness of digital advertising campaigns where a region of interest is partitioned into geographical-targeting areas called Geos. The experiment is conducted in two distinct time periods where in the first time period there is no difference in advertising campaign between Geos, whereas during the second time period the campaign for some selected Geos is modified. The aim is to construct an efficient design for targeting the modified advertising campaign. The challenge is to design the campaign in a robust way which permits estimation of the effectiveness of the modified campaign. The issue is related to an absence of covariates related to socio-economic characteristics or other important unknown characteristics that are likely to affect the probability of making purchases. A stochastic simulation platform has been built for studying the effectiveness of advertising campaigns. However, due to the computational resource required, the use of simulation limits the complexity of study which can be carried out. A theoretical framework is developed to study the implications of unobserved covariates for inferences about estimated effects of the campaign. A proxy model is introduced to link the fitted model, without covariates, and the truth which includes unobserved covariates The proxy model makes possible the application of standard results in the literature on maximum likelihood estimation for mis-specified models.
Journal