What Is Ad Fill Rate? Formula, Examples & How to Improve It

Publishers can generate substantial website traffic and send thousands of ad requests but still leave some advertising opportunities unfilled. When this happens, potential impressions and revenue may be lost.

Ad fill rate is a useful metric for understanding this situation. It helps publishers and ad operations specialists evaluate how much of their requested inventory is being filled with ads.

However, fill rate alone does not tell the entire story. A high fill rate does not necessarily mean high revenue, and a low fill rate does not automatically indicate a technical problem. To understand performance, you need to examine fill rate alongside impressions, revenue, eCPM, demand sources, and the specific metrics available in your ad server.

1. What Is Ad Fill Rate?

Ad fill rate is the percentage of ad requests or advertising opportunities that result in a filled ad, according to the metric’s specific definition.

When a website or app requests an ad, the ad-serving system evaluates the eligible campaigns and available demand. If an ad is selected and returned, the opportunity may count as filled under the relevant metric. If no eligible ad is returned, the request may be recorded as unfilled.

Fill rate is especially useful for:

• Publishers: Understanding how much inventory is being monetized.
• Ad operations specialists: Investigating unfilled requests, targeting issues, and delivery problems.
• Yield managers: Evaluating demand coverage and the impact of optimization changes.
• App developers: Monitoring how effectively ad requests are filled across supported ad formats and networks.

Fill rate should be evaluated for specific inventory segments as well as across the entire network. A healthy network-level figure can hide poor fill on a particular device, geography, ad unit, or format.

2. Ad Fill Rate Formula

A commonly used formula for ad fill rate is:

Here is what each term means:

• Filled ad requests: Requests counted as filled under the selected platform’s metric definition.
• Total ad requests: The total number of requests included in the same calculation.
• 100: Converts the ratio into a percentage.

Important: This is a general formula. Some ad platforms define fill rate using impressions rather than filled requests. For example, Google Ad Manager documents a Total fill rate metric calculated as total impressions divided by total ad requests. Ad Exchange delivery rate and Ad Exchange match rate use their own definitions and denominators.

Always use the numerator and denominator specified for the report you are analyzing. Do not compare percentages from different platforms or reports until you confirm their definitions.

3. Ad Fill Rate Calculation Example

Suppose a publisher’s ad server records the following figures for a day:

Using the general filled-request formula:

The fill rate is 80%. In this example, 20% of the requests were not filled, assuming filled and unfilled requests use the same request-level definition and reporting scope.

The next step is to determine why those requests were not filled. They might be associated with unavailable demand, targeting restrictions, line-item eligibility, or another issue in the delivery process.

4. What Is a Good Ad Fill Rate?

There is no universal fill rate that is ideal for every publisher. The appropriate benchmark depends on the ad format, geography, demand sources, traffic quality, targeting, consent requirements, and the platform’s counting methodology.

A 95% fill rate is not automatically better for business than an 85% fill rate. If the higher fill rate comes from low-value demand, it might not produce better revenue. Similarly, a lower fill rate can be acceptable for inventory that is deliberately restricted to premium campaigns.

Instead of pursuing a single benchmark, focus on these questions:

• Is the fill rate stable compared with the publisher’s historical baseline?
• Which ad units, formats, devices, or geographies have the lowest fill?
• Is low fill associated with lower revenue or eCPM?
• Are unfilled requests caused by missing demand, eligibility restrictions, or technical issues?
• Did the fill rate change after a tag, targeting, floor-price, consent, or demand configuration update?

Tracking changes over time is usually more actionable than comparing your fill rate with an unrelated publisher’s percentage.

5. Fill Rate vs. Match Rate vs. Impression Rate

These metrics are related, but they should not be treated as interchangeable. Their exact definitions depend on the ad server, demand source, and report.

For Google Ad Manager, consult the official Ad Manager report metrics reference and the Interactive report metrics reference before interpreting a particular metric.

6. Why Is Your Ad Fill Rate Low?

A low fill rate can have several causes. The most effective troubleshooting approach is to identify where the requests stop progressing through the ad-serving process.

1. Insufficient eligible demand

There may not be enough campaigns, buyers, or demand sources eligible to serve the requested inventory. This can be particularly noticeable for niche audiences, less common ad sizes, or lower-demand geographies.

What to check: Review demand coverage, eligible line items, and the affected inventory segments. Determine whether additional suitable demand is available before changing other settings.

2. Incorrect targeting or line-item configuration

Line items may be active but unable to serve because their targeting, dates, ad sizes, device rules, or other delivery settings do not match the incoming request.

What to check: Verify ad-unit targeting, requested sizes, start and end dates, exclusions, creative association, and delivery troubleshooting details.

3. Price floors or pricing restrictions

Pricing rules and floors can affect which bids are eligible to compete. A floor set too high for the available demand may reduce the number of bids that qualify and leave more inventory unfilled.

What to check: Review recent pricing changes and compare fill rate, bid behavior, and revenue by inventory segment. Test changes carefully rather than lowering every floor across the network.

4. Weak or inconsistent demand coverage

A publisher may depend heavily on one demand source or have limited demand coverage for particular formats and markets. When that source does not return suitable demand, fill can decline.

What to check: Compare available demand-source reporting, response rates, and delivery outcomes. Confirm that each additional source is compatible with the inventory and configured correctly.

5. Ad tags or implementation problems

Incorrect ad-unit paths, unsupported sizes, JavaScript errors, consent-related restrictions, or implementation changes can prevent requests from behaving as expected.

What to check: Test the affected page or app, inspect browser console errors where applicable, verify the tag configuration, and compare request behavior before and after the change.

6. Video ad and player errors

Video inventory has additional requirements involving player behavior, VAST responses, creative compatibility, and playback. A request may not result in a playable ad or a recorded impression.

What to check: Review video-specific request and response metrics, VAST errors, timeouts, and playback diagnostics. For optimized video pods, use the appropriate unmatched-request metric rather than assuming ordinary impression counts fully represent unfilled pod duration.

7. Consent, privacy, and eligibility restrictions

Consent signals, regional requirements, demand-partner eligibility, and other restrictions can affect which demand sources are allowed to participate in a request.

What to check: Confirm that consent messages, consent signals, privacy settings, and demand-partner configurations are functioning as intended. Do not bypass user choices or applicable privacy requirements to increase fill.

7. How to Improve Ad Fill Rate

Improving fill rate starts with identifying the cause of unfilled requests. These steps can help publishers improve inventory coverage while protecting revenue and user experience.

1. Find the inventory with the largest gap

Break down performance by ad unit, requested size, device, geography, and format where available. Start with segments showing the largest decline or the highest volume of unfilled requests.

2. Investigate unfilled impressions

In Google Ad Manager, use a compatible report with the Ad unit and Requested ad sizes dimensions alongside the Unfilled impressions metric. Then use delivery tools to investigate why eligible line items are not returning ads.

Official guide: Troubleshoot unfilled impressions in Ad Manager.

3. Correct line-item and tag configuration

Verify that inventory paths, sizes, targeting, schedules, and creative associations are correct. Fix configuration problems before adding more demand or changing pricing rules.

4. Review demand coverage

Evaluate whether suitable demand sources cover your inventory. Where appropriate, consider additional compatible demand partners or eligible remnant demand. Review their impact on revenue, latency, and operational complexity.

5. Test pricing changes carefully

If floors are contributing to low fill, run controlled tests on comparable inventory segments. Measure the combined effect on fill rate, eCPM, and total revenue. A higher fill rate is not a success if the extra impressions generate insufficient revenue to justify the change.

6. Improve creative and player reliability

Investigate creative loading problems, timeouts, and player errors. For video inventory, review VAST and playback diagnostics. For web inventory, check tag behavior and page performance.

7. Monitor the effect of every change

Record the baseline before changing settings. Compare like-for-like dates and traffic segments after implementation, allowing for reporting delays. Keep changes that improve the intended business outcome rather than optimizing one metric in isolation.

8. How to Investigate Low Fill Rate in Google Ad Manager

Use the following workflow to investigate a decline in GAM fill rate.

1. Choose a consistent reporting period. Compare equivalent time windows and use the same time zone.
2. Confirm the metric definition. Check whether the report uses Total fill rate, Ad Exchange match rate, Ad Exchange delivery rate, or another metric.
3. Segment the results. Review the ad units, requested sizes, geographies, devices, and formats available in the selected report.
4. Review unfilled inventory. Identify where unfilled impressions are concentrated.
5. Investigate delivery eligibility. Use the line item’s Troubleshoot tab and GAM delivery tools to identify non-delivery causes.
6. Check demand and pricing. Look for changes in eligible demand, response behavior, and pricing restrictions.
7. Check implementation issues. Review recent tag, creative, player, and consent configuration changes.
8. Measure revenue impact. Compare impressions, revenue, and eCPM before and after changes to determine whether the outcome improved.

9. Does a Higher Fill Rate Always Mean Higher Revenue?

No. Fill rate measures how much inventory is filled under the chosen metric definition. Revenue depends on the value of the ads served as well as the number of monetized impressions.

Consider two hypothetical outcomes for 10,000 ad requests:

In this simplified example, Scenario B fills more opportunities but generates less revenue because the average revenue per filled opportunity is lower. Real ad systems can have different counting and revenue rules, so this example is illustrative rather than a universal GAM calculation.

For a more complete assessment, monitor fill rate alongside revenue, eCPM, impression volume, and relevant demand-source metrics. You can use the CPMinSider eCPM guide to understand revenue per thousand impressions and how it differs from fill rate.

10. Frequently Asked Questions

Official Google Ad Manager Resources

• Troubleshoot unfilled impressions in Ad Manager — find unfilled inventory and investigate delivery eligibility.
• Ad Manager report metrics — definitions for fill rate, match rate, delivery rate, and other metrics.
• Interactive report metrics reference — current metric definitions and reporting availability.