Experimental Designs and Estimation for Online Display Advertising Attribution in Marketplaces

Abstract

O nline Display Advertising's importance as a marketing channel is partially due to its ability to attribute conversions to campaigns. Current industry practice to measure ad effectiveness is to run randomized experiments using placebo ads, assuming external validity for future exposures. We identify two different effects, i.e., a strategic effect of the campaign presence in marketplaces, and a selection effect due to user targeting; these are confounded in current practices. We propose two novel randomized designs to: (1) estimate the overall campaign attribution without placebo ads, (2) disaggregate the campaign presence and ad effects. Using the Potential Outcomes Causal Model, we address the selection effect by estimating the probability of selecting influenceable users. We show the ex-ante value of continuing evaluation to enhance the user selection for ad exposure mid-flight. We analyze two performance-based (CPA) and one Cost-Per-Impression (CPM) campaigns with 20 million users each. We estimate a negative CPM campaign presence effect due to cross product spillovers. Experimental evidence suggests that CPA campaigns incentivize selection of converting users regardless of the ad, up to 96% more than CPM campaigns, thus challenging the standard practice of targeting most likely converting users.

Editorial—Marketing Science and Big Data

“…Indeed, they demonstrate that their approach is superior to existing methods. Barajas et al (2016) develop new methods that separate the target selection component and the campaign effect of online display ads for millions of users. Braun and Damien (2016) demonstrate how to scale rejection sampling for large hierarchical Bayes models.…”

Differences in Buyer Journey between High- and Low-Value Customers of E-Commerce Business

“…In this case, more credit is assigned to these channels when it comes to low-value customers. As we work with the assumption that during the first purchase the customer only purchases a few goods to try the seller [4], it is natural that more searches are performed by users in the initial research and evaluation of the suitability of the potential seller. In both cases, other channels are not significant drivers of conversions for acquiring low-value and high-value clients.…”

“…Barajas et al [4], Anderl et al [1], Sterne [27] Abhishek et al (Site 1) and Bryl (Site 3) reported that the use of heuristic attribution models is not proper for attribution purposes. Barajas et al [4] claim that heuristic models assign a value to each displayed and converting channel. However, they ignore hypothetical reaction without a user being in touch with the advertisement.…”

Inefficiencies in Digital Advertising Markets

“…based on expectations of future demand, e.g., a car dealer advertising a temporary price reduction before a holiday weekend. Ad treatment often correlates with ad response--and possibly other marketing actions, such as temporary price reductions--creating a confounding correlation between ad levels and outcomes (Barajas et al 2016 (Becker and Murphy 1993;Tuchman, Nair and Gardete 2018). As a result, it may be difficult for advertisers to distinguish incremental effects of ads from consumers' baseline propensities to attend to the brand's ads.…”