Fill rate is one of the most critical metrics for publishers. Even small improvements can translate to significant revenue gains. This guide provides actionable strategies for maximizing your fill rates.

Understanding Fill Rate

Fill rate is the percentage of ad requests that are successfully filled with an ad. The formula is simple:

Fill Rate = (Filled Ad Requests / Total Ad Requests) × 100

However, optimizing fill rate is far from simple. It requires understanding your inventory, demand sources, and audience.

Step 1: Diagnose Your Fill Rate Issues

Segment Your Analysis

Break down fill rates by:

Geography: Some regions may have lower demand
Device Type: CTV, mobile, and desktop often have different fill rates
Time of Day: Demand fluctuates throughout the day
Content Category: Different content types attract different advertisers
Ad Position: Pre-roll typically fills better than mid-roll

Identify Patterns

Look for systematic gaps. Are you seeing consistent unfilled inventory at specific times or for specific audiences? These patterns point to opportunities.

Step 2: Diversify Your Demand Sources

Build a Waterfall

Implement a demand waterfall with multiple tiers:

Tier 1: Premium direct campaigns and programmatic guaranteed
Tier 2: Preferred deals and private marketplace (PMP)
Tier 3: Open exchange and header bidding
Tier 4: Backfill and house ads

Implement Header Bidding

Header bidding allows multiple demand sources to compete simultaneously, increasing competition and fill rates. For video, consider server-side header bidding to reduce latency.

Step 3: Optimize Your Floor Prices

Dynamic Floor Pricing

Static floor prices leave money on the table. Implement dynamic floors that adjust based on:

Time of day and day of week
Audience segments
Historical performance
Real-time demand signals

Test and Learn

Run A/B tests on floor prices. Sometimes lowering floors slightly can dramatically increase fill while maintaining revenue.

Step 4: Enhance Your Inventory Quality

Improve Metadata

Rich, accurate metadata helps advertisers find your inventory. Ensure you're providing:

Content genre and rating
IAB categories
Episode-level descriptions
Contextual signals

Address Brand Safety

Advertisers avoid inventory they perceive as risky. Implement:

Content classification systems
Third-party verification
Transparent reporting on content adjacency

Step 5: Leverage Data for Targeting

First-Party Data Activation

Your first-party data is valuable. Create audience segments based on:

Viewing behavior
Content preferences
Engagement patterns
Device and platform usage

Contextual Targeting

In a privacy-first world, contextual targeting is resurgent. Provide detailed contextual signals to attract more demand.

Step 6: Optimize Ad Placement

Pre-Roll Optimization

Pre-roll typically achieves highest fill rates. Consider:

Limiting pre-roll duration (15-30 seconds performs best)
A/B testing single ads vs. pods
Dynamic pre-roll based on content length

Mid-Roll Strategy

Mid-roll can be challenging but lucrative. Best practices:

Place breaks at natural content transitions
Avoid too-frequent breaks (8-12 minutes minimum)
Offer longer mid-roll pods to increase demand

Step 7: Monitor and Iterate

Key Metrics to Track

Beyond fill rate, monitor:

eCPM by source: Ensure fill improvements aren't degrading price
Revenue per session: The ultimate measure of success
Win rate in auctions: Are you competitive in the market?
Discrepancy rates: High discrepancies signal measurement issues

Set Up Alerts

Automated alerts for fill rate drops help you respond quickly to issues.

Advanced Tactics: Programmatic Guaranteed Deals & ML Optimization

Programmatic Guaranteed

For publishers with consistent audiences, programmatic guaranteed deals provide fill rate certainty while maintaining programmatic efficiency.

Demand Path Optimization (DPO)

Reduce the supply chain to improve margins and potentially attract more demand.

Machine Learning

Use ML to predict fill likelihood and optimize decisioning in real-time.

Common Pitfalls to Avoid

Chasing fill over revenue: 100% fill at $0 CPM helps no one
Ignoring user experience: Too many ads reduce engagement and long-term value
Set-and-forget mentality: Markets change; your strategy should too
Over-segmentation: Too many tiny segments can fragment demand

Conclusion

Maximizing fill rates is an ongoing process of analysis, optimization, and iteration. By following a data-driven approach and continuously testing new strategies, publishers can achieve both high fill rates and strong eCPMs.

Remember: the goal isn't 100% fill rate—it's maximizing revenue while delivering a quality viewer experience.