A Feedback Shift Correction in Predicting Conversion Rates under Delayed Feedback

02/06/2020
by   Shota Yasui, et al.
2

In display advertising, predicting the conversion rate, that is, the probability that a user takes a predefined action on an advertiser's website, such as purchasing goods is fundamental in estimating the value of displaying the advertisement. However, there is a relatively long time delay between a click and its resultant conversion. Because of the delayed feedback, some positive instances at the training period are labeled as negative because some conversions have not yet occurred when training data are gathered. As a result, the conditional label distributions differ between the training data and the production environment. This situation is referred to as a feedback shift. We address this problem by using an importance weight approach typically used for covariate shift correction. We prove its consistency for the feedback shift. Results in both offline and online experiments show that our proposed method outperforms the existing method.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
10/04/2019

Dual Learning Algorithm for Delayed Feedback in Display Advertising

In display advertising, predicting the conversion rate, that is, the pro...
research
02/01/2018

A Nonparametric Delayed Feedback Model for Conversion Rate Prediction

Predicting conversion rates (CVRs) in display advertising (e.g., predict...
research
04/29/2021

Real Negatives Matter: Continuous Training with Real Negatives for Delayed Feedback Modeling

One of the difficulties of conversion rate (CVR) prediction is that the ...
research
01/06/2021

Handling many conversions per click in modeling delayed feedback

Predicting the expected value or number of post-click conversions (purch...
research
08/13/2021

Follow the Prophet: Accurate Online Conversion Rate Prediction in the Face of Delayed Feedback

The delayed feedback problem is one of the imperative challenges in onli...
research
08/15/2023

Freshness or Accuracy, Why Not Both? Addressing Delayed Feedback via Dynamic Graph Neural Networks

The delayed feedback problem is one of the most pressing challenges in p...
research
10/24/2017

Display advertising: Estimating conversion probability efficiently

The goal of online display advertising is to entice users to "convert" (...

Please sign up or login with your details

Forgot password? Click here to reset