Prebid.js & Header Bidding
Waterfall setups leave 20-50% of programmatic revenue behind. Most publishers running Prebid.js still don't know why bids are being lost.
We implement Prebid.js from scratch or audit your existing setup. Demand partner configuration, floor strategy from real bid data, latency optimization, and a yield analytics layer that shows exactly which bidders are winning — and which are not.
The problem
Waterfall legacy and misconfigured Prebid.js
Waterfall setups pass each impression to one demand source at a time, in priority order. If the first source doesn't buy, it goes to the second, then the third. By the time the impression reaches a buyer who wants it, there is no competition. The CPM reflects that.
Header bidding runs all demand sources simultaneously and takes the highest bid. That is where the 20-50% revenue lift comes from. But only when it is set up correctly. Publishers who install Prebid.js with default configurations, without floor strategy, and without bid-level analytics are running header bidding — and still leaving revenue behind.
The deeper problem is visibility. Without a proper analytics layer on top of Prebid.js, your team cannot see why bids are being lost. Is it the floor? Latency timeout? A demand partner that is misconfigured? Without that data, the only tool available is guessing.
What we build
Prebid.js implementation built for yield, not just setup
Implementation scoped to your inventory, your demand partners, and your latency targets. Or an audit of your existing Prebid.js setup to recover the yield that configuration drift has been quietly costing you.
Demand partner setup and integration
Each SSP connected and configured for your inventory — ad units, sizes, formats, floor prices. Not a generic integration. Configured for your placements, your audience segments, and the deal structures your demand partners actually use.
Floor strategy from actual bid density data
Floor prices set based on real bid data from your auctions — not guesses. Which placements are clearing above floor. Where floors are suppressing fill. Which bidders respond to floor changes. The full picture before you set a price.
Latency optimization
Slow header bidding kills user experience and reduces ad revenue. We tune timeout configurations, bidder priority, and lazy loading logic to recover yield from placements that are losing bids to latency — not lack of demand.
Yield analytics layer
Dashboard showing exactly which bidders are winning, which are losing, and why. Win rate by bidder, average CPM by placement, floor breach rate, timeout rate. The data your team needs to make real decisions about your demand stack.
Already running Prebid.js?
We audit existing setups and recover yield
Prebid.js configurations drift over time. Demand partners get added without tuning. Floor prices get set and never revisited. Timeout configurations that worked a year ago are now costing fill rate. New bidder behavior changes the optimal floor — nobody updates it.
We audit the full configuration: bidder setup, floor logic, timeout settings, lazy load behavior, and analytics coverage. Then we identify where configuration drift is costing revenue and fix it.
Configuration drift in Prebid.js is quiet. It does not break anything. It just costs revenue slowly.
Most publishers running Prebid.js for 12+ months have recoverable yield sitting in their setup. The audit finds it.
Business outcomes
What publishers see after proper implementation
20-50%
Programmatic revenue recovery vs waterfall
Waterfall setups pass each impression to demand sources one at a time. Header bidding runs all sources simultaneously and takes the highest bid. Publishers moving from waterfall to properly implemented Prebid.js typically see 20-50% more programmatic revenue.
35%+
Yield lift from proper Prebid.js implementation
Publishers who install Prebid.js without proper configuration leave significant revenue behind. Correct demand partner setup, floor strategy, and latency tuning typically recovers 35% or more above a baseline install.
Real
Bid-level data on why bids are lost
Most publishers running Prebid.js have no visibility into losing bids. The yield analytics layer shows exactly where demand is dropping — floor too high, latency timeout, bidder misconfiguration — so the team can fix it.
Lower
Latency without sacrificing fill rate
Aggressive timeout settings kill fill. Loose settings hurt page performance. We tune timeout and lazy load logic to the actual latency profile of your demand partners — protecting both fill rate and user experience.
Who this is for
Publishers starting with programmatic or underperforming on it
New implementation
Small Publishers — $500K-$5M ad revenue
Moving from a basic waterfall setup to Prebid.js header bidding. Getting this right from the start — demand partner selection, floor strategy, latency tuning — is the difference between 10% lift and 40% lift.
Audit and optimization
Medium Publishers — $5M-$25M ad revenue
Already running Prebid.js but programmatic yield is flat or declining. The setup works technically but the revenue performance suggests configuration drift or a floor strategy that needs revisiting with current bid data.
Start here
Stop leaving programmatic revenue behind.
New implementation or audit of an existing setup — we scope to your demand partners, inventory, and latency targets. You own the configuration. No SaaS dependency, no ongoing fees.