Mid-flight Forecasting for CPA Lines in Online Advertising

TL;DR

This paper presents a novel mid-flight forecasting methodology for CPA lines in online advertising that incorporates bidding mechanisms, providing actionable insights and accurate predictions to optimize campaign performance.

Contribution

It introduces a new forecasting approach that models relationships between key metrics and optimization signals, considering bidding effects and practical implementation issues.

Findings

Forecasting accuracy validated against actual campaign data.

Relationship between advertiser spend and eCPA characterized.

Method demonstrates promising accuracy in real-world scenarios.

Abstract

For Verizon MediaDemand Side Platform(DSP), forecasting of ad campaign performance not only feeds key information to the optimization server to allow the system to operate on a high-performance mode, but also produces actionable insights to the advertisers. In this paper, the forecasting problem for CPA lines in the middle of the flight is investigated by taking the bidding mechanism into account. The proposed methodology generates relationships between various key performance metrics and optimization signals. It can also be used to estimate the sensitivity of ad campaign performance metrics to the adjustments of optimization signal, which is important to the design of a campaign management system. The relationship between advertiser spends and effective Cost Per Action(eCPA) is also characterized, which serves as a guidance for mid-flight line adjustment to the advertisers. Several practical issues in implementation, such as downsampling of the dataset, are also discussed in the paper. At last, the forecasting results are validated against actual deliveries and demonstrates promising accuracy.