Artificial Intelligence 3 min read

Budget Pacing for Targeted Online Advertisements: Problem, Solution, and Pass‑Through Rate Mechanism

The article explains the drawbacks of the traditional generalized second‑price auction for online ads, proposes monitoring and probabilistically throttling fast‑spending campaigns using a time‑window based budget pacing model with a Pass‑Through Rate (PTR), and references the related research paper while also offering free resource links.

DataFunSummit
DataFunSummit
DataFunSummit
Budget Pacing for Targeted Online Advertisements: Problem, Solution, and Pass‑Through Rate Mechanism

Background : The generalized second‑price auction is the most widely used billing method for internet advertising, but it causes high‑quality ads to exhaust their budgets quickly, leading to poor advertiser experience, reduced market competition, and lower platform revenue. System latency can also cause overspend, further decreasing revenue.

Solution : Monitor each campaign's budget consumption and, for campaigns that spend too fast, allow participation in auctions with a certain probability to slow down consumption. Each campaign has a daily budget divided into T equal time windows; cumulative consumption up to window t is tracked, and the theoretical budget consumption at window t is calculated based on the estimated full‑day exposure. The probability of allowing participation in each auction is the Pass‑Through Rate (PTR), which is adjusted by a tuning factor.

Paper reference: Budget Pacing for Target Online Advertisements At LinkedIn .

Free Resources : Links are provided for downloading PPT versions of “Internet Core Application Algorithm Treasure Book” and a “Big Data Collection” ebook.

About Us : DataFun focuses on sharing and discussing big data and artificial intelligence technologies, having organized over 100 offline and online events since 2017, with a large community of experts and scholars.

AIonline advertisingbudget pacingad budgetingauction algorithmpass-through rate
DataFunSummit
Written by

DataFunSummit

Official account of the DataFun community, dedicated to sharing big data and AI industry summit news and speaker talks, with regular downloadable resource packs.

0 followers
Reader feedback

How this landed with the community

login Sign in to like

Rate this article

Was this worth your time?

Sign in to rate
Discussion

0 Comments

Thoughtful readers leave field notes, pushback, and hard-won operational detail here.