Cold Start to Improve Market Thickness on Online Advertising Platforms

For your marketing

Possible founder application

Use this study as a bounded example of cold start to improve market thickness on online advertising platforms; assess whether its population, intervention and outcome match your own decision.

Reported result

What the study found

The algorithm increased cold-start success rate by 61.62%, with a 0.717% short-term-revenue compromise. It increased overall advertising-market thickness by 3.13% and long-term advertising revenue by at least 5.35%.

Research question

What the authors investigated

What does cold start to improve market thickness on online advertising platforms show about customer decisions or business outcomes?

Design

Data-driven optimization and bandit-algorithm study validated through a two-sided randomized field experiment with a large-scale video-sharing platform; the experiment evaluated the proposed shadow bidding with learning algorithms for new-ad cold start.

Sample and setting

Ads, advertisers, and users in the large-scale video-sharing-platform field experiment; the accessible publisher abstract does not state numeric sample counts.

Scope and transfer

Limitations to keep in view

The empirical validation is tied to one large-scale video-sharing platform and its online advertising system; the publisher page does not report the number of ads, advertisers, or users, so transferability and sample scale cannot be evaluated from the accessible article page alone. Full article methods and correction history were not independently reviewed.

Research sources

Publisher page directly retrieved; candidate metadata and reported result checked against that page. Full methods were not independently reviewed.