Static & Dynamic Floor Design
Defining floor structures by placement, format, device, and geography; introducing dynamic floors driven by historical bid data and demand signals so you don’t leave money on the table or over-floor and lose fill.
Floor Pricing Strategy — Set Floors That Maximize Revenue
Ranjan Dasgupta has designed yield and floor strategies for programmatic and header bidding at scale. This page covers floor pricing — from static vs dynamic floors to placement and format rules that balance fill rate and CPM. For more, see Insights.
What I Do
Floor Testing & Analytics
Running A/B tests and holdback experiments to measure the impact of floor changes on fill rate, CPM, and overall revenue. Ranjan Dasgupta uses data to recommend floor levels and update frequency.
Integration with Ad Server & Prebid
Implementing floor rules in Google Ad Manager, Prebid, and exchange-side systems so floors are consistent across header bidding and open auction, with clear reporting.
Unified Auction & Floor Alignment
Aligning floor strategy with first-price unified auctions so floors act as a reserve price and don’t conflict with bid shading or buyer behavior. Ensuring transparency for demand partners.
Discuss Floor Pricing Strategy
FAQs
- What is floor pricing in programmatic advertising?
- Floor pricing is the minimum CPM (cost per mille) a publisher is willing to accept for an ad impression. Floors can be static (fixed by placement or format) or dynamic (adjusted by demand, time, or inventory quality) to maximize revenue without killing fill rate.
- How do dynamic floors work?
- Dynamic floor pricing uses historical bid data, time of day, geography, device, and inventory attributes to set minimum prices per impression. Floors are updated frequently so they respond to market demand while protecting against low-ball bids.
- Should you set one floor or many?
- Ranjan Dasgupta recommends segmenting floors by placement, ad size, device, and sometimes geography. A single global floor often leaves money on the table for premium inventory or depresses fill for long-tail. Granular rules with testing yield the best revenue outcome.
- How does Ranjan Dasgupta approach floor pricing strategy?
- Ranjan Dasgupta combines yield analytics with floor rules in the ad server and in Prebid: testing floor levels, measuring fill and CPM trade-offs, and aligning floors with unified auctions and header bidding so revenue and fill are optimized together.
Optimize Your Floor Strategy
Work with a yield and floor pricing expert to set and test floors that maximize revenue without sacrificing fill.
Related Projects
Explore More
Yield optimization · Prebid optimization · Header bidding · Exchange architecture