A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution

38 Pages Posted: 14 Feb 2023

See all articles by Jun Tao

Jun Tao

Adobe Systems, Inc.

Qian Chen

Pennsylvania State University - Smeal College of Business

James W. Snyder Jr.

Adobe Systems, Inc.

Arava Sai Kumar

Adobe Systems, Inc.

Amirhossein Meisami

Adobe Systems, Inc.

Lingzhou Xue

Pennsylvania State University - Department of Statistics

Date Written: February 2023

Abstract

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 individual customer-level path-to-purchase data and the increasing number of online marketing channels and types of touchpoints bring new challenges to this fundamental problem. We aim to tackle the attribution problem with finer granularity by conducting attribution at the path level. To this end, we develop a novel graphical point process framework to study the direct conversion effects and the full relational structure among numerous types of touchpoints simultaneously. Utilizing the temporal point process of conversion and the graphical structure, we further propose graphical attribution methods to allocate proper path-level conversion credit, called the attribution score, to individual touchpoints or corresponding channels for each customer's path to purchase. Our proposed attribution methods consider the attribution score as the removal effect, and we use the rigorous probabilistic definition to derive two types of removal effects. We examine the performance of our proposed methods in extensive simulation studies and compare their performance with commonly used attribution models. We also demonstrate the performance of the proposed methods in a real-world attribution application.

Keywords: Granger Causality, Graphical Model, High Dimensional Statistics, Multi-Touch Attribution, Point Process.

Suggested Citation

Tao, Jun and Chen, Qian and Snyder Jr., James W. and Kumar, Arava Sai and Meisami, Amirhossein and Xue, Lingzhou, A Graphical Point Process Framework for Understanding Removal Effects in Multi-Touch Attribution (February 2023). Available at SSRN: https://ssrn.com/abstract=4356088 or http://dx.doi.org/10.2139/ssrn.4356088

Jun Tao

Adobe Systems, Inc. ( email )

Qian Chen

Pennsylvania State University - Smeal College of Business ( email )

University Park, PA 16802
United States

James W. Snyder Jr.

Adobe Systems, Inc. ( email )

Arava Sai Kumar

Adobe Systems, Inc. ( email )

Amirhossein Meisami

Adobe Systems, Inc. ( email )

Lingzhou Xue (Contact Author)

Pennsylvania State University - Department of Statistics ( email )

326 Thomas Building
University Park, PA 16802
United States

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