Shapley Value Methods for Attribution Modeling in Online Advertising

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   Beyond the Last Touch: Attribution in Online Advertising

   Ron Berman · 2018 · Marketing science (Providence, R.I.) · cité 143 fois · Pas encore résumé

   Résumé scientifique

   Online advertisers often utilize multiple publishers and bid in multiple auctions concurrently to deliver ads, a process which may result in externalities between publishers that impact advertising effectiveness. In conjunction with these externalities, uncertainty about consumer visit patterns may limit the advertiser's ability to optimize its campaigns.We define the attribution problem as the attempt to measure such uncertainties and correct for the externalities, and determine the characteristics of a good attribution process. Using an analytical model of an online campaign we show that publisher externalities will lead an advertiser to shift from truthful bidding in equilibrium, and that…

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   A Non-parametric Approach to the Multi-channel Attribution Problem

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   Counterfactual Shapley Additive Explanations

   Emanuele Albini, Jason Long, Danial Dervovic et al. · 2021 · Machine Learning · cité 80 fois · Résumé IA disponible

   Résumé scientifique

   Feature attributions are a common paradigm for model explanations due to their simplicity in assigning a single numeric score for each input feature to a model. In the actionable recourse setting, wherein the goal of the explanations is to improve outcomes for model consumers, it is often unclear how feature attributions should be correctly used. With this work, we aim to strengthen and clarify the link between actionable recourse and feature attributions. Concretely, we propose a variant of SHAP, Counterfactual SHAP (CF-SHAP), that incorporates counterfactual information to produce a background dataset for use within the marginal (a.k.a. interventional) Shapley value framework. We motivate …

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   Attributing Conversions in a Multichannel Online Marketing Environment: An Empirical Model and a Field Experiment

   Hong-Shuang Li, P. K. Kannan · 2014 · Journal of Marketing Research · cité 446 fois · Pas encore résumé
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   Causally motivated attribution for online advertising

   Brian Dalessandro, Claudia Perlich, Ori Stitelman et al. · 2012 · International Workshop on Data Mining for Online Advertising · cité 122 fois · Pas encore résumé
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   Attribution Theory and Advertising Effectiveness

   Richard M. Sparkman, William B. Locander · 1980 · Journal of Consumer Research · cité 108 fois · Pas encore résumé
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   Do display ads influence search? Attribution and dynamics in online advertising

   Pavel Kireyev, Koen H. Pauwels, Sunil Gupta · 2016 · International Journal of Research in Marketing · cité 167 fois · Pas encore résumé

   Résumé scientifique

   As firms increasingly rely on online media to acquire consumers, marketing managers rely on online metrics such as click-through rate (CTR) and cost per acquisition (CPA). However, these standard online advertising metrics are plagued with attribution problems and do not account for synergy or dynamics. These issues can easily lead firms to overspend on some actions and thus waste money and/or underspend in others, leaving money on the table.

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   Efficient Shapley Values Estimation by Amortization for Text Classification

   Chenghao Yang, Fan Yin, He He et al. · 2023 · Computation and Language · cité 7 fois · Résumé IA disponible

   Résumé scientifique

   Despite the popularity of Shapley Values in explaining neural text classification models, computing them is prohibitive for large pretrained models due to a large number of model evaluations. In practice, Shapley Values are often estimated with a small number of stochastic model evaluations. However, we show that the estimated Shapley Values are sensitive to random seed choices -- the top-ranked features often have little overlap across different seeds, especially on examples with longer input texts. This can only be mitigated by aggregating thousands of model evaluations, which on the other hand, induces substantial computational overheads. To mitigate the trade-off between stability and ef…

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