arXiv:2603.13059v2 Announce Type: replace Abstract: Cost-per-click (CPC) in paid search is an auction-generated outcome shaped by a competitive landscape that is only partially observable from any single advertiser's history. From 1.66 billion Google Ads log records for a concentrated car-rental market (2021-2023), we construct a weekly panel of 1,811 keyword series over 127 weeks (218,924 keyword-week observations) and build competition-aware proxies from keyword text, CPC trajectories, and geographic market structure. The design combines (i) semantic neighborhoods and a semantic keyword grap
The increasing sophistication of AI models and the availability of large, granular datasets enable more accurate and competition-aware forecasting for digital advertising at this moment.
Accurate CPC forecasting allows advertisers to optimize spending, improve ROI, and gain a competitive edge in digital marketplaces, impacting overall digital economy efficiency.
Advertisers can now leverage AI to predict ad costs more effectively by accounting for competitive dynamics, shifting from reactive bidding to proactive, data-driven strategies.
- · Savvy advertisers
- · Digital marketing platforms
- · Data scientists
- · AI/ML providers
- · Advertisers without advanced AI tools
- · Traditional marketing agencies
- · Platforms with less sophisticated auction mechanics
Individual advertisers can achieve higher return on ad spend by precisely identifying optimal bid strategies.
Increased efficiency in ad markets may lead to more competitive bidding overall, potentially raising baseline CPCs for certain highly contested keywords.
The development of 'competition-aware' AI agents could lead to an escalating arms race in advertising, requiring continuous innovation in forecasting and bidding to maintain an edge.
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Read at arXiv cs.LG