What is Fill Rate?
Fill rate is the percentage of ad requests that result in a served impression. If a publisher sends 1,000 ad requests to an ad network and 850 come back with a live ad, the fill rate is 85%. It is one of the most direct indicators of how efficiently a publisher is monetizing available inventory.
Fill Rate Formula
The calculation is straightforward:
Fill Rate (%) = (Ads Served ÷ Ad Requests) × 100
For example, a mid-size news site sending 500,000 daily ad requests with 410,000 filled impressions produces a fill rate of 82%. The remaining 18% represents unfilled inventory, which generates zero revenue regardless of the traffic behind it.
Why Fill Rate Matters
A low fill rate is essentially leaving money on the table. Publishers depend on every page view generating ad revenue, and an unfilled slot means a visitor saw blank space instead of a paid creative. For high-traffic properties, even a 5% improvement in fill rate can translate to tens of thousands of dollars in additional monthly revenue.
Fill rate also serves as a diagnostic signal. A sudden drop often points to a technical issue or a shift in buyer demand. It can also indicate a floor price set too high or a mismatch between the publisher’s audience and available advertiser targeting criteria.
Typical Fill Rate Benchmarks
| Inventory Type | Typical Fill Rate Range |
|---|---|
| Premium direct-sold display | 95–100% |
| Programmatic open exchange | 60–85% |
| Mobile in-app | 70–90% |
| Video (pre-roll) | 50–75% |
| Native ad units | 55–80% |
These ranges vary by vertical, geography, and season. Q4 holiday periods tend to push fill rates higher as advertiser budgets peak, while Q1 typically sees a pullback that depresses both fill rate and CPM.
Fill Rate vs. eCPM: The Trade-Off
Publishers often face a tension between fill rate and effective CPM. Setting a high floor price filters out low-value bids, which raises average revenue per impression but reduces fill rate. Setting the floor too low fills nearly every request, but at rates that undervalue the inventory.
Consider two scenarios for a site receiving 1,000,000 monthly ad requests:
- Scenario A: $3.00 floor, 65% fill rate = 650,000 impressions × $3.00 CPM = $1,950 revenue
- Scenario B: $1.50 floor, 88% fill rate = 880,000 impressions × $1.80 blended CPM = $1,584 revenue
In this case, the higher floor generates more total revenue despite the lower fill rate. The optimal balance depends on the publisher’s audience quality, advertiser demand in that vertical, and header bidding stack configuration.
What Causes Low Fill Rates
Demand-Side Gaps
If a publisher’s audience does not match the targeting parameters of available advertisers, buyers pass on the impression. A niche B2B publication covering supply chain logistics may see low fill on general display networks simply because relevant advertisers are not buying programmatically at scale in that space.
Floor Price Misalignment
Aggressive price floors block bids that fall below the threshold. A publisher on Google Ad Manager, for example, might set a $4.00 CPM floor that excludes 40% of incoming bids, even if those bids would otherwise fill the slot.
Ad Format Mismatches
Requesting a 300×600 half-page unit in a market where most buyers are trafficking 300×250 medium rectangles will produce lower fill. Format demand varies by region and device type, with mobile web and desktop often showing different fill rate patterns for the same ad sizes.
Technical Latency
Timeout settings on the ad server can cause legitimate bids to arrive after the slot has already been declared unfilled. Publishers running header bidding through Prebid.js commonly adjust bid timeouts between 800ms and 2,000ms to balance fill rate against page load speed.
Strategies to Improve Fill Rate
Header Bidding
Running a header bidding wrapper increases competitive pressure on each impression by allowing multiple demand sources to bid simultaneously rather than in a waterfall sequence. Publishers using Prebid.js with five or more demand partners routinely report fill rate improvements of 10 to 20 percentage points compared to a single-network waterfall.
Open Bidding and Mediation
Google’s Open Bidding and equivalent mobile mediation platforms, such as ironSource or MAX by AppLovin, allow additional demand sources to compete in real time through the ad server. The result: filled requests that a primary network would otherwise leave empty.
House Ads and Backfill
Using house ads or low-CPM backfill networks as a last resort prevents completely empty slots. While the revenue per impression is minimal, it keeps fill rate close to 100% and avoids the user experience problem of blank ad containers on the page.
Audience Extension
Publishers with strong first-party data can work with demand-side platforms to make their audience segments available to buyers who want precise targeting. This increases the relevance of the inventory to more advertisers and raises the probability of a filled impression.
Fill Rate in Programmatic Advertising
In programmatic advertising, supply-side platforms (SSPs) such as Magnite and PubMatic track fill rate at the placement, device, and geographic level in real time. Publishers can see how each ad unit performs alongside win rate and average CPM, giving a complete picture of demand health across their inventory.
A media buying team at a large brand might exclude placements with chronic low fill rates from their private marketplace deals. Low fill signals either thin demand or inventory quality issues, and neither is welcome in a curated buying list.
Frequently Asked Questions
What is a good fill rate for programmatic advertising?
A fill rate above 80% is generally considered healthy for programmatic open exchange inventory. Premium direct-sold campaigns typically reach 95–100%. Anything below 70% on programmatic inventory warrants investigation into floor prices, demand partner configuration, or technical latency settings.
How is fill rate calculated?
Fill rate equals the number of ads served divided by the number of ad requests, multiplied by 100. If 850 ads are served from 1,000 requests, the fill rate is 85%.
What is the difference between fill rate and win rate?
Fill rate measures how many of a publisher’s ad requests receive a served impression. Win rate measures how often a buyer’s bid wins an auction. A publisher can show a low fill rate even with active bidders if overall auction participation is thin.
How does floor price affect fill rate?
A higher floor price filters out low bids, raising average CPM but reducing fill rate. Setting the floor too low fills more requests but at rates that undervalue the inventory. The goal is the floor price that maximizes total revenue, not fill rate in isolation.
Why does fill rate typically drop in Q1?
Advertiser budgets reset at the start of the year, pulling back overall demand. This causes both fill rates and CPMs to dip across most verticals. Publishers who saw strong Q4 numbers should expect the pullback and may need to adjust floor prices to maintain yield.
Key Takeaways
- Fill rate measures how many ad requests actually receive a served impression, expressed as a percentage.
- A fill rate below 70% on programmatic inventory typically warrants investigation into floor prices, demand diversity, or technical configuration.
- Optimizing fill rate requires balancing volume against CPM rather than chasing 100% fill at any price.
- Header bidding, mediation platforms, and diversified demand partnerships are the primary tools publishers use to push fill rates higher without sacrificing yield.