Abstract
Return on advertising spend (ROAS) refers to the ratio of revenue generated by advertising projects to its expense. It is used to assess the effectiveness of advertising marketing. Several simulation-based controlled experiments, such as geo experiments, have been proposed recently. This refers to calculating ROAS by dividing a geographic region into a control group and a treatment group and comparing the ROAS generated in each group. However, the data collected through these experiments can only be used to analyze previously constructed data, making it difficult to use in an inductive process that predicts future profits or costs. Furthermore, to obtain ROAS for each advertising group, data must be collected under a new experimental setting each time, suggesting that there is a limitation in using previously collected data. Considering these, we present a method for predicting ROAS that does not require controlled experiments in data acquisition and validates its effectiveness through comparative experiments. Specifically, we propose a task deposition method that divides the end-to-end prediction task into the two-stage process: occurrence prediction and occurred ROAS regression. Through comparative experiments, we reveal that these approaches can effectively deal with the advertising data, in which the label is mainly set to zero-label.
Funder
National Research Foundation of Kore
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)
Reference27 articles.
1. Social Media Networks as a Business Environment, During COVID-19 Crisis
2. Modelling of Digital Communication Surfaces for Products and Services Promotion;Krasnov,2019
3. Measuring Ad Effectiveness Using Geo Experiments;Vaver,2011
4. Estimating Ad Effectiveness Using Geo Experiments in a Time-Based Regression Framework;Kerman,2017
5. Consumer Heterogeneity and Paid Search Effectiveness: A Large-Scale Field Experiment
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