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Related papers: Bayesian Modeling of Marketing Attribution

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The flexibility of choosing the ad action as a function of the consumer state is critical for modern-day marketing campaigns. We study the problem of identifying the optimal sequential personalized interventions that maximize the adoption…

Machine Learning · Computer Science 2024-01-15 Garud Iyengar , Raghav Singal

Predicting click and conversion probabilities when bidding on ad exchanges is at the core of the programmatic advertising industry. Two separated lines of previous works respectively address i) the prediction of user conversion probability…

Machine Learning · Statistics 2017-07-24 Eustache Diemert , Julien Meynet , Pierre Galland , Damien Lefortier

Marketers employ various online advertising channels to reach customers, and they are particularly interested in attribution for measuring the degree to which individual touchpoints contribute to an eventual conversion. The availability of…

Methodology · Statistics 2023-02-14 Jun Tao , Qian Chen , James W. Snyder , Arava Sai Kumar , Amirhossein Meisami , Lingzhou Xue

Consumer behavior under social influence is a well-known phenomenon and computer scientists and economists are prevalently trying to analyze the dynamics behind decision making during the consumption process through agent-based modeling…

Social and Information Networks · Computer Science 2022-10-18 Eren Arkangil

Social marketing is becoming increasingly important in contemporary business. Central to social marketing is quantifying how consumers choose between alternatives and how they influence each other. This work considers a new but simple…

Social and Information Networks · Computer Science 2014-05-05 Jeremy Chen

The causal effect of showing an ad to a potential customer versus not, commonly referred to as "incrementality", is the fundamental question of advertising effectiveness. In digital advertising three major puzzle pieces are central to…

Machine Learning · Computer Science 2022-08-30 Randall Lewis , Jeffrey Wong

In online advertising, users may be exposed to a range of different advertising campaigns, such as natural search or referral or organic search, before leading to a final transaction. Estimating the contribution of advertising campaigns on…

Information Retrieval · Computer Science 2020-04-02 Dongdong Yang , Kevin Dyer , Senzhang Wang

Modern collaborative filtering algorithms seek to provide personalized product recommendations by uncovering patterns in consumer-product interactions. However, these interactions can be biased by how the product is marketed, for example…

Information Retrieval · Computer Science 2019-12-05 Mengting Wan , Jianmo Ni , Rishabh Misra , Julian McAuley

Multi-touch attribution (MTA) estimates the relative contributions of the multiple ads a user may see prior to any observed conversions. Increasingly, advertisers also want to base budget and bidding decisions on these attributions,…

Applications · Statistics 2023-06-26 Dinah Shender , Ali Nasiri Amini , Xinlong Bao , Mert Dikmen , Amy Richardson , Jing Wang

E-commerce businesses employ recommender models to assist in identifying a personalized set of products for each visitor. To accurately assess the recommendations' influence on customer clicks and buys, three target areas -- customer…

Computers and Society · Computer Science 2019-11-05 Namrata Chaudhary , Drimik Roy Chowdhury

The Bayesian persuasion model studies communication between an informed sender and a receiver with a payoff-relevant action, emphasizing the ability of a sender to extract maximal surplus from his informational advantage. In this paper we…

Computer Science and Game Theory · Computer Science 2020-06-04 Ronen Gradwohl , Niklas Hahn , Martin Hoefer , Rann Smorodinsky

We study computational questions in a game-theoretic model that, in particular, aims to capture advertising/persuasion applications such as viral marketing. Specifically, we consider a multi-agent Bayesian persuasion model where an informed…

Computer Science and Game Theory · Computer Science 2016-03-07 Yakov Babichenko , Siddharth Barman

Marketing mix modeling (MMM) is a widely used method to assess the effectiveness of marketing campaigns and optimize marketing strategies. Bayesian MMM is an advanced approach that allows for the incorporation of prior information,…

Applications · Statistics 2025-01-03 Roy Ravid

Budget allocation in online advertising deals with distributing the campaign (insertion order) level budgets to different sub-campaigns which employ different targeting criteria and may perform differently in terms of return-on-investment…

Artificial Intelligence · Computer Science 2015-02-25 Sahin Cem Geyik , Abhishek Saxena , Ali Dasdan

Many marketing applications, including credit card incentive programs, offer rewards to customers who exceed specific spending thresholds to encourage increased consumption. Quantifying the causal effect of these thresholds on customers is…

Methodology · Statistics 2026-01-19 Kohsuke Kubota , Shonosuke Sugasawa

Online advertising has been the major monetization approach for Internet companies. Advertisers invest budgets to bid for real-time impressions to gain direct and indirect returns. Existing works have been concentrating on optimizing direct…

Computer Science and Game Theory · Computer Science 2019-03-12 Hao Liu , Yunze Li , Qinyu Cao , Guang Qiu , Jiming Chen

The celebrated Bayesian persuasion model considers strategic communication between an informed agent (the sender) and uninformed decision makers (the receivers). The current rapidly-growing literature mostly assumes a dichotomy: either the…

Computer Science and Game Theory · Computer Science 2022-03-16 Yakov Babichenko , Inbal Talgam-Cohen , Haifeng Xu , Konstantin Zabarnyi

Persuasion studies how an informed principal may influence the behavior of agents by the strategic provision of payoff-relevant information. We focus on the fundamental multi-receiver model by Arieli and Babichenko (2019), in which there…

Computer Science and Game Theory · Computer Science 2020-04-01 Matteo Castiglioni , Andrea Celli , Nicola Gatti

Social media are extensively used in today's world, and facilitate quick and easy sharing of information, which makes them a good way to advertise products. Influencers of a social media network, owing to their massive popularity, provide a…

Artificial Intelligence · Computer Science 2024-05-21 Ronak Doshi , Ajay Ramesh Ranganathan , Shrisha Rao

We consider a brand with a given budget that wants to promote a product over multiple rounds of influencer marketing. In each round, it commissions an influencer to promote the product over a social network, and then observes the subsequent…

Machine Learning · Computer Science 2019-11-11 Shatian Wang , Zhen Xu , Van-Anh Truong
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