Price floors are a simple but powerful tool for publishers looking to boost their ad revenue. In Google Ad Manager, you can set minimum CPMs. This prevents low bids from undervaluing your high-value inventory across different platforms.
By setting these floors, you protect your inventory’s value in real-time bidding and private deals. You also get to control how non-guaranteed demand competes. This gives you more control over your ad space.
Recently, Google introduced optimized floor prices (Beta). This uses machine learning to set minimums for each query. It aims to maximize your ad revenue over time.
This feature works alongside traditional pricing methods. Knowing when to use a hard floor, a target CPM, or an optimized floor is essential. It helps balance how often ads are shown and how much you earn from them.
Key Takeaways
- Unified pricing rules in Google Ad Manager centralize floor management for Google AdX and most non-guaranteed channels.
- Price floors stop low bids from undervaluing premium inventory in real-time bidding.
- Optimized floor prices (Beta) use per-query signals to improve long-term ad revenue optimization.
- Floor strategy affects fill rate, so test small changes and monitor win rates and CPMs.
- UPR does not apply to Programmatic Guaranteed or house line items, so plan rules according.
Understanding Floor Prices and Why They Matter for Ad Revenue Optimization
Price floors are the lowest CPM a publisher will accept in an auction. Target CPM is a flexible floor that changes based on past results and auction signals. Publishers use these tools to protect their best ad spots and keep the value of their inventory high.
Floors help manage ad inventory by stopping the sale of high-quality ad spots for too little. This keeps the value of these spots high for display ads. When buyers see consistent value, they bid more for the same spots over time.
Setting a target CPM uses machine learning to guide bids towards a publisher’s revenue goals. Google AdX supports target CPM, helping publishers balance minimum prices with market changes. The system learns from auction data to improve yield while keeping fill rates high.
There’s a trade-off between fill rate and long-term yield. A high floor can increase CPMs but might leave more spots unfilled. A low floor keeps spots filled but could lead buyers to bid less. Finding the right floor price is key to balancing these needs.
Effective ad inventory management needs testing and tracking. Use reports to see if floors are rejecting too many bids or if buyers are bidding less. Making small changes and watching for seasonal trends helps keep ad revenue healthy while keeping demand strong.
Key Price Floor Types: Dynamic, Tiered, and Smart Floors
Choosing the right floor strategy is key to making money in programmatic advertising. Publishers need to think about demand, inventory, and risk. Here are brief descriptions and tips to help pick the best model for Google AdX.
Dynamic adjustments and when to use them
Dynamic price floors change in real time based on market signals. They’re good for diverse, high-demand inventory. Be careful not to underprice or block bids during slow times.
Segmenting by ad unit, format, or partner
Tiered price floors divide inventory into different bands. Use them to price ad units, formats, or partners differently. This keeps high-value spots priced up and lower spots more competitive.
Predictive optimization and risks
AI-driven floors use machine learning to predict the best bids. They can improve yield over time without constant tweaking. But, test them well and validate results to avoid mispricing.
| Floor Type | Best Use | Key Benefit | Main Risk |
|---|---|---|---|
| Dynamic price floors | High-traffic, varied inventory | Real-time responsiveness to demand | Volatile pricing can cut fill if too aggressive |
| Tiered price floors | Segmented inventory by format or partner | Granular control over value capture | Complex rule sets increase management overhead |
| AI-driven floors | Large datasets with stable signal patterns | Scale optimization with minimal manual work | Model bias or poor training data may harm yield |
When using any floor type in Google AdX, make sure to align rules with reporting. This helps track important metrics. Use a mix of approaches: tiered for key spots and dynamic or AI for the rest. Test and review data to find and fix issues.
How Unified Pricing Rules Work in Google Ad Manager for AdX
Unified pricing rules help publishers set minimum prices for ads across many sources. This is done in Google Ad Manager. It lets you set a minimum CPM for Open Auction, First Look, and third-party buyers through Open Bidding. This makes managing prices easier and keeps them consistent.
Open Google Ad Manager and go to Inventory > Pricing rules. Here, you can see and create up to 200 unified pricing rules. Each rule shows its status, targets, and the price settings for eligible traffic.
Set pricing for everything versus set pricing for specific items
A rule can apply to all sizes, creative types, and buyers by default. Or, you can target specific advertisers, brands, sizes, or creative types. If a rule targets both broadly and narrowly, the platform uses the higher price to decide the floor.
| Scope | Typical Use | Applies To | Notes |
|---|---|---|---|
| Set pricing for everything | Network-wide baseline floors | All sizes, formats, buyers | Simple to maintain; can be overridden by higher specific rules |
| Set pricing for specific items | Targeted higher floors for premium inventory | Advertisers, brands, ad unit, creative types | Use to protect high-value placements without blocking general demand |
How pricing rules apply across demand channels
Unified pricing rules send floor values to Open Auction, Private Auctions, and First Look. They also apply to third-party exchanges in Open Bidding and to Ad Exchange and AdSense backfill. This ensures floors are consistent in bid requests and buyer logic.
Limitations and exclusions
Unified pricing rules don’t apply to Programmatic Direct or house line items. Remnant line items like Price Priority, Network, or Bulk are affected, but guaranteed deals keep their rates. For publishers moving from DoubleClick for Publishers, it’s important to map and review to avoid gaps.
Google AdX
Google Ad Exchange is key when unified pricing rules are on. Publishers set rules in Google Ad Manager. They map an Ad Exchange account to apply those rules to auctions.
This setup lets AdX follow floor logic. It also lets buyers compete within the publisher’s pricing rules.
How Google Ad Exchange interacts with unified pricing rules
Google Ad Exchange follows unified pricing rules. It reads the mapped settings and sets a floor for eligible inventory. This affects which bids enter the auction and how AdX reports bid rejections.
Publishers can control pricing for broad groups or specific items. AdX applies those floors across supported channels.
How floor prices are shared with buyers in bid requests (bidfloor / minimum_cpm_micros)
In real-time bidding, floor values are shared in bid requests. This tells buyers the minimum they must offer. OpenRTB uses the bidfloor field.
Google’s Ad Exchange proto exposes minimum_cpm_micros. This shows the publisher’s minimum CPM in micros. If a bid is below this, the RTB breakout will note it.
Ad Exchange-specific considerations for multi-size requests and buyers
Multi-size impressions send a single floor to buyers. The lowest floor among eligible sizes is sent. Size-specific floors may not appear in the external bid request if the buyer’s creative is unknown.
Yet, those specific floors affect the auction when a matching creative wins. For video, separate skippable or non-skippable floors exist for internal logic. But buyers may not see those distinctions in the request.
Step-by-Step: Creating a Unified Pricing Rule to Set a Floor
Before you start, gather all the inventory details. Decide which pricing options to use. Sign in to Google Ad Manager and have your ad unit names, placements, or packages ready. Taking small, clear steps helps avoid mistakes and speeds up the process.
Navigate to Inventory > Pricing rules
Open Google Ad Manager and go to Inventory, then Unified Pricing Rules. Click New Rule to start. Name the rule clearly, like “US Display – Minimum CPM”.
Choose targeting and pricing options
Select what inventory to target: ad units, placements, packages, or entire networks. Add filters for geography and devices if needed. Choose whether the rule applies to Open Auction, First Look, or both. Start with tight targeting to see how it works.
Select floor type: hard floor, target CPM, or optimized floor prices
For a hard floor, enter a fixed CPM value, like $5.00. Choose target CPM for a dynamic approach aiming for a target CPM. For Google to adjust, pick optimized floor prices and enable Set pricing for everything. Optimized floors mean you don’t have to manually enter a value.
Save, activate, and monitor affected line items
Save the rule and activate it. After activation, click the Affected line items link. Review remnant, network, and bulk line items below the floor. Use the Unified pricing rule dimension in Historical Reports and line item troubleshooting to track bid rejections and fill changes.
Enabling and Using Optimized Floor Prices (Beta)
Optimized floor prices (Beta) are an automated way to set floors for each query. They aim to boost long-term earnings. These rules use Google’s models to balance filling ads now with keeping value for later, making it easier for publishers.
What optimized floor prices do and how they differ from other pricing options
Optimized floor prices set a dynamic floor for each auction, unlike a single static value. This is different from optimized pricing, which keeps value but doesn’t change the target every auction. With optimized floors, publishers need to tweak less while keeping high-value spots safe.
How optimized floors use machine learning per query
Google uses machine learning to figure out a floor for each bid request. It looks at bidder behavior and future value. This model optimizes each query, balancing short-term gains with long-term bidder responses for better revenue over time.
Enable optimized floors and known limitations
To use optimized floor prices, choose “Set pricing for everything” in Unified Pricing Rules. They don’t work for targeting specific items. These floors override other pricing rules but keep advertiser-specific floors. When there are multiple optimized rules, the older rule is reported, even if the per-query price is different.
Running experiments to evaluate optimized floor performance
Create a New experiment in Unified Pricing Rules. Pick the rule, select “Everything,” and choose “Optimized” as the experiment price. Keep the experiment price at $0.00 for per-query optimization. Run experiments one at a time to avoid mixing results. Compare bid-rate, win-rate, and revenue against a control.
Configuring Pricing for Different Inventory Dimensions
Set pricing rules to match how buyers view inventory. Unified pricing rules let you target by ad unit, placement, packages, device type, and region. This way, pricing matches real demand and context. Clear slices reduce guesswork when adjusting floors across formats and geography.
Device targeting matters. Create separate rules for desktop, mobile, and tablet to reflect differing CPMs and user behavior. Setting floors by device type helps capture higher bids on desktop while protecting mobile yield with appropriate minimums.
Geography targeting should align with demand centers. Use country and DMA-level rules for markets such as the United States, United Kingdom, and Canada to lock in value where buyers pay more. Pair geography targeting with ad unit or placement slices when certain pages attract premium bids.
Different creative types require distinct treatment. You can apply rules to display advertising or to video. When Ad Manager cannot detect a creative type, Display pricing is applied by default, so set sensible display floors for header-bid situations.
Video pricing needs extra controls. Target video with minimum duration and skippability flags to separate skippable from non-skippable inventory. Avoid relying on creative size for video targeting; use ad unit or key-values to represent player dimensions and context instead.
Multi-size pricing works for responsive environments. When a multi-size request arrives, the lowest eligible size floor is sent to buyers. Enable the Pricing for everything option by default and test rule stacks so multi-size pricing does not undercut specific high-value sizes.
Use focused rules instead of broad overrides. Combine device targeting, geography targeting, and creative types in narrow slices to preserve inventory value. Monitor performance and iterate with small adjustments to avoid sudden fill loss or unintended suppression of demand.
Managing Overlapping Pricing Rules and Rule Priority
When multiple unified pricing rules target the same inventory, publishers need clear guidance. This is to prevent unexpected results in ad inventory management. Ad Manager evaluates competing rules and applies the price that benefits yield.
But, there are special cases for optimized floors and First Look rules. These can change outcomes.
How Ad Manager chooses the winning rule
Ad Manager compares competing rules and uses rule priority to decide which price governs an auction. If two unified pricing rules overlap, the higher price typically applies. When a First Look rule overlaps with a UPR and Ad Exchange demand exists, the higher price is used for Ad Exchange impressions.
Optimized floors and reporting behavior
Optimized floor prices take precedence over overlapping unified pricing rules, except when an advertiser-specific floor is present. If two optimized-floor rules share inventory, the per-query price is set independently. But, reporting attributes win to the older rule for consistency.
Using Explore overlap to inspect interactions
Open Inventory > Pricing rules and run Explore overlap to visualize how rules combine. The tool shows percentage of overlapping ad requests, merged settings, and lets you hover over targeting to inspect combinations. Overlap status relies on forecasting from sampled historical data, so use it as a planning aid.
Practical table: common overlap scenarios and outcomes
| Scenario | Key outcome | Action to take |
|---|---|---|
| Two UPRs target same ad unit | Higher price applies; auctions use that floor | Consolidate or remove redundant rules to simplify pricing rule overlap |
| First Look rule overlaps with UPR | Higher price used for Ad Exchange demand | Set clear rule priority and test with small traffic segments |
| Optimized floor overlaps UPR | Optimized floor overrides UPR; per-query pricing independent | Monitor reporting and limit overlapping optimized experiments |
| Two optimized-floor rules share inventory | Price set per query; older rule gets reporting attribution | Stagger optimized rule start dates and track attribution |
| Pricing for everything set and specific prices exist | Specific-item prices can outbid broad setting if higher | Keep Pricing for everything conservative or leave it off to avoid blocking higher specific prices |
Best practices to avoid conflicts
Avoid overly granular rules that create complex pricing rule overlap. Keep the number of overlapping experiments low. Use conservative values for Pricing for everything settings.
Run Explore overlap regularly to catch merged targeting that could limit demand.
Integrating Header Bidding and Prebid Floor Strategies
Publishers need to match floor prices in the ad server and header bidding wrapper to avoid losing money. It’s important to set priorities so that wrapper floors don’t block better prices from the ad server. Make sure Prebid is up to date and test it often to confirm that bidders get the right floor values.
Decide where to set floors carefully. Wrapper floors can block low bids before the auction reaches the ad server. Ad Manager floors protect the value of your inventory in Google AdX and unified pricing rules. A balanced approach helps avoid losing fill while keeping long-term yield.
Prebid offers a simple way to set floors with static configuration via pbjs.floors. You can use currency and schema fields to target specific ad types and sizes. For example, you might set a banner at 300×250 to 1.10 USD and a video at the same size to 2.00 USD to meet buyer expectations.
Dynamic floor solutions let vendors calculate floors per request. Prebid supports third-party floor providers with a setConfig call that includes auctionDelay and an endpoint. Use auctionDelay (like 100 ms) to give external services time to respond. If they don’t reply, Prebid falls back to default pbjs.floors data.
Here’s a comparison to help choose between static and dynamic floor approaches. It also shows how wrapper-level floors work with ad server rules.
| Aspect | Static pbjs.floors | Dynamic third-party floors | Ad Server (Ad Manager/AdX) |
|---|---|---|---|
| Setup | Defined in Prebid config with mediaType and size schema | Requires endpoint, data payload, and auctionDelay configuration | Configured through Unified Pricing Rules or specific line items |
| Latency | Minimal; no external call | Dependent on vendor response and auctionDelay window | No added auction latency from server-side rules |
| Flexibility | Low; manual updates needed for market changes | High; real-time adjustments based on signals and machine learning | Medium; can apply broad rules and optimized floors where available |
| Failover | Immediate; rules are always present | Fallback to pbjs.floors or default if vendor times out | Ad server enforces minimums at auction time |
| Best use | Stable inventory with predictable pricing | High-value, variable inventory benefiting from real-time signals | Publisher-wide protection and cross-channel consistency |
Test different combinations of wrapper-level floors and ad server rules in a controlled setup. Watch key metrics like bid rate, win rate, and timeouts to see if auctionDelay and floor logic boost your yield. Update your configs as needed based on bid feedback and reporting.
Using Bid Data and Reporting to Optimize Floor Prices
Start by pulling detailed bid logs and historical metrics to understand floor impacts on demand. Use the Bid Data Report to check rejected bids and patterns over time. In Google Ad Manager 360, the report shows why buyers lost auctions, helping set realistic floors without hurting fill rates.
Check BidRejectionReason in the Bid Data Report for “Floor” entries when buyer CPMs are below your minimum. This flag shows price rejections and helps distinguish between true demand gaps and bidder issues. If your account lacks Bid Data Report visibility, request access to the Beta and work with your Google Account Manager for enablement.
Use header bidding analytics to evaluate bidder behavior before adjusting floors. Watch bid rate to see who participates, win rate to see who clears your price, and timeout rate to spot slow bidders. For Prebid setups, raise floors on bidders that respond late or bid rarely, then observe page performance and bid share.
Combine historical reporting with the Unified pricing rule dimension to measure rule impact over weeks. Pull Requested ad sizes alongside bid metrics to verify multi-size pricing behavior and the lowest eligible size sent to buyers. Historical reporting allows you to compare pre- and post-change windows, ensuring adjustments are based on data, not guesses.
Monitor affected remnant line items in the UPR UI to catch Price Priority, Network, and Bulk items sitting below your floors. Use line item troubleshooting and the “Below pricing rule floor” non-delivery cause to find inventory that needs relabeling or price edits. Tracking these items prevents unexpected fill loss after a pricing rule rollout.
When testing, run small, time-bound experiments and track the same Bid Data Report metrics, header bidding analytics, and Unified pricing rule dimensions. Keep sample sizes large enough to be statistically useful. This approach minimizes revenue risk while revealing which floors improve yield and which block legitimate demand.
Troubleshooting Common Floor Price Issues and Fill Loss
When floor prices cause unexpected fill loss, start with a quick inventory check. Unified pricing rules include an Affected remnant line items section. This section lists Price Priority, Network, and Bulk line items below your set floor. The UI shows how many line items sit below the floor and links to a filtered table for review.
Use line item troubleshooting to identify non-delivery reasons. Look for “Below pricing rule floor” in the tool. Clicking that entry surfaces the specific pricing rule issues and the affected line items list. This helps you trace why bids were dropped.
Remnant line items often fall below the floor because their CPMs are set conservatively. Review those CPMs against current demand and adjust where needed to reduce fill loss. The Affected remnant line items view helps you prioritize which line items to edit.
Impressions go unfilled when no pricing rule matches a request or when bids fail to meet the floor. In those cases, house line items act as a fallback. House line items are treated as $0 value CPM and ignore floors, so they serve only when remnant, Ad Exchange, or Open Bidding demand is absent.
If house line items are appearing more than expected, check for gaps in targeting or unmatched pricing rules. Use the line item troubleshooting reports to filter for requests routed to house ads. Then, inspect the related pricing rule issues that allowed the fallback.
Create a simple table to map common causes to immediate actions. This gives teams a fast checklist to reduce fill loss and fix pricing rule issues before they affect revenue.
| Observed Issue | Diagnostic Tool | Immediate Action |
|---|---|---|
| High fill loss with low bid activity | Line item troubleshooting, Bid Data | Lower floor or broaden targeting for affected sizes |
| Many remnant line items listed below floor | Affected remnant line items section | Adjust remnant CPMs or set targeted pricing rules |
| Frequent house line items serving | Delivery reports, line item troubleshooting | Fill gaps by matching pricing rules or enabling additional demand |
| “Below pricing rule floor” non-delivery | Line item troubleshooting detail view | Click through to pricing rule, edit or exclude problematic rule |
Keep changes small and track impact over several days. Small, frequent checks of remnant line items and pricing rule issues reduce sudden fill loss. This keeps house line items reserved for true fallback scenarios.
Best Practices for Incremental Floor Optimization and Seasonality
Small, steady changes are key to improving ad revenue. Make tiny adjustments, track key metrics, and avoid big changes. This helps keep buyer behavior stable. Use experiments on small parts of your inventory to get clear results.
Plan for seasonality by matching demand cycles with floor rules. Raise floors during busy times to grab more value. Lower them in slow periods to keep revenue flowing.
When using Google AdX, pick your segments wisely. Avoid running tests that overlap and mess with each other. This way, you can see how changes affect bids and wins.
Set prices carefully to avoid blocking better offers. Keep prices low for everything unless you have specific prices for certain advertisers. This strategy helps you avoid losing out on better deals.
Keep an eye on results and make small improvements regularly. Use data on bids, win rates, and pricing to fine-tune your floors. This method helps you stay on top of ad revenue, even as the market changes.
Balancing Guaranteed and Non-Guaranteed Demand with Optimized Competition
Optimized Competition helps publishers meet their delivery goals. It lets non-guaranteed demand compete with guaranteed ads when needed. This way, channels like AdSense and Google AdX can win impressions even when standard ads are expensive.
How Optimized Competition works in Google Ad Manager is key for making more money. If a guaranteed ad doesn’t meet its goal, its price might go up. But Optimized Competition makes sure non-guaranteed ads can compete without lowering their value too much.
Turning on Optimized Competition is easy for admins. Just go to Admin > Global settings > Network settings > Ad serving settings and toggle it on. Then, check how it’s doing by running reports that show results by Ad Exchange.
Unified Pricing Rules can affect Optimized Competition, so make sure they match. If UPRs set strict floors for non-guaranteed demand, they might undo Optimized Competition’s changes. Check rule priority and overlap before making big changes. Test small changes to see how AdSense and Google AdX do.
Reporting is key to finding the right balance between guaranteed and non-guaranteed demand. Use Bid Data and line item reports to see when non-guaranteed bids succeed. Look at delivery percentage, win rate by exchange, and revenue per thousand impressions. Use these to fine-tune unified pricing and keep Optimized Competition on track.
Conclusion
Price floors are key for publishers aiming to keep inventory value high and boost ad revenue. They can be set in Google Ad Manager for AdX or at the wrapper level in Prebid. A clear floor price strategy prevents underselling and balances fill and long-term yield in programmatic ads.
Unified pricing rules give teams control over targeting by device, geography, creative type, and size. Use these rules with Bid Data Report and header bidding analytics to find floor rejections and fix fill loss. This helps make better decisions with data-driven experiments.
Optimized floor prices use Google’s machine learning to set per-query floors. But, they need “Set pricing for everything” and careful evaluation. Mix incremental adjustments, seasonally aware tactics, and rule-priority checks to boost performance in AdX and non-guaranteed demand.
In practice, a balanced approach works best. This includes clear unified pricing rules, measured floor changes, and ongoing reporting. This discipline helps publishers get the most revenue without losing long-term demand quality in Google AdX.
FAQ
How do I set floor prices in Google AdX to improve yield?
What is a price floor and how does a target CPM differ?
How do floors protect inventory value and prevent underselling?
What are the trade-offs between fill rate and long-term yield?
What are dynamic price floors and when should I use them?
How do tiered price floors work?
What are AI-driven or smart floors and what risks come with them?
Where do I find Unified Pricing Rules in Google Ad Manager?
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
How does Google Ad Exchange interact with unified pricing rules?
How are floor prices shared with buyers in bid requests?
What happens with multi-size requests and floors?
How do I create a Unified Pricing Rule step by step?
When should I select hard floor, target CPM, or optimized floor prices?
What do optimized floor prices do and how are they different from optimized pricing?
How do optimized floors use machine learning per query?
How do I enable optimized floors and what are their limits?
How do I run experiments to evaluate optimized floor performance?
FAQ
How do I set floor prices in Google AdX to improve yield?
Use Google Ad Manager’s Unified Pricing Rules. Go to Inventory > Pricing rules, create a new rule, target the inventory slice, and choose a price type: Hard floor (fixed CPM), Target CPM (dynamic), or Optimized floor prices (ML-driven beta). Save and monitor affected remnant line items and reporting to measure impact.
What is a price floor and how does a target CPM differ?
A price floor is a minimum CPM you set so buyers’ bids must meet that threshold to win. A target CPM (dynamic floor) uses historical auction data to adjust the effective floor over time to balance fill rate and long-term yield while maintaining an average minimum price.
How do floors protect inventory value and prevent underselling?
Floors prevent buyers from winning premium placements at very low CPMs, preserving perceived market value. They signal to buyers what inventory is worth and discourage downward price pressure that can erode long-term demand.
What are the trade-offs between fill rate and long-term yield?
Higher floors raise CPM but can reduce fill or win rates, lowering immediate impressions. Lower floors increase fill but can teach buyers to bid lower, hurting long-term yield. Incremental testing and ML-driven optimized floors help balance short-term revenue with inventory preservation.
What are dynamic price floors and when should I use them?
Dynamic floors adjust in real time to market conditions, ideal for diverse, high-demand inventory where price sensitivity changes frequently. Use them when you need responsive pricing, but monitor sensitivity to avoid under- or overpricing.
How do tiered price floors work?
Tiered floors segment inventory by ad unit, format, partner, geography, or device, allowing different minimum CPMs for different slices. This granular approach aligns price with actual market value for each inventory type.
What are AI-driven or smart floors and what risks come with them?
AI-driven floors (e.g., Optimized floor prices) use machine learning to set per-query floors that aim to maximize long-term revenue. Risks include misconfiguration, overlap with other rules, and the need for experiments to validate outcomes—so test carefully and avoid overlapping experiments.
Where do I find Unified Pricing Rules in Google Ad Manager?
Sign in to Google Ad Manager and navigate to Inventory > Pricing rules. From there you can create, edit, explore overlap, run experiments, and view affected remnant line items.
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
“Set pricing for everything” applies the rule broadly to all inventory and is required to enable Optimized floor prices. “Set pricing for specific items” targets advertisers, sizes, or creative types. When both exist, the higher price applies.
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
Unified Pricing Rules apply to non-guaranteed demand channels: Open Auction via Authorized Buyers (AdX), Private Auctions, First Look, and third-party exchanges participating in Open Bidding. They also affect AdSense backfill and remnant line items.
How does Google Ad Exchange interact with unified pricing rules?
AdX respects UPRs set in the linked Ad Exchange account. UPRs influence AdX demand in Open Auction, Private Auctions, and First Look, and AdX receives the floor values when it evaluates bids.
How are floor prices shared with buyers in bid requests?
In OpenRTB the floor is in the bidfloor field. For the Ad Exchange protocol, the minimum is sent in minimum_cpm_micros. Bidders whose bids fall below these values see rejections labeled as “Bid was below the minimum threshold.”
What happens with multi-size requests and floors?
For multi-size requests the floor sent to buyers is the lowest floor for any eligible size. Size-specific floors are applied in auction when a buyer’s creative is matched, but the initial bid request may use the lowest eligible size floor.
How do I create a Unified Pricing Rule step by step?
Navigate to Inventory > Pricing rules > New Rule. Name the rule, choose Price Floor as the type, target inventory (ad units, placements, packages), geography, and device type. Choose pricing: Hard Floor, Target CPM, or Optimized floor prices. Save, then review Affected remnant line items and historical reports.
When should I select hard floor, target CPM, or optimized floor prices?
Use a hard floor when you need a fixed minimum CPM. Choose target CPM for dynamic floors that adapt via Google’s target CPM logic. Select Optimized floor prices (beta) to let Google’s ML set per-query floors—only available when you choose “Set pricing for everything.”
What do optimized floor prices do and how are they different from optimized pricing?
Optimized floor prices use machine learning to set per-query minimums that maximize long-term revenue while protecting inventory value. They differ from the older “optimized pricing” by actively setting floors per query, making optimized pricing unnecessary when enabled.
How do optimized floors use machine learning per query?
The ML model evaluates query-level signals and bidder behavior to predict the optimal floor for each auction, balancing fill and future bidder responses. It adapts over time to bidder patterns and market signals.
How do I enable optimized floors and what are their limits?
In a Unified Pricing Rule choose “Set pricing for everything” and select “Let Google optimize floor prices.” Optimized floors are not supported under “Set pricing for specific items” and they override overlapping pricing rules (but not advertiser-specific floors).
How do I run experiments to evaluate optimized floor performance?
In Unified Pricing Rules create a New experiment, select the rule, choose “Everything” as the pricing option and “Optimized” as the experiment price, leave the price at
FAQ
How do I set floor prices in Google AdX to improve yield?
Use Google Ad Manager’s Unified Pricing Rules. Go to Inventory > Pricing rules, create a new rule, target the inventory slice, and choose a price type: Hard floor (fixed CPM), Target CPM (dynamic), or Optimized floor prices (ML-driven beta). Save and monitor affected remnant line items and reporting to measure impact.
What is a price floor and how does a target CPM differ?
A price floor is a minimum CPM you set so buyers’ bids must meet that threshold to win. A target CPM (dynamic floor) uses historical auction data to adjust the effective floor over time to balance fill rate and long-term yield while maintaining an average minimum price.
How do floors protect inventory value and prevent underselling?
Floors prevent buyers from winning premium placements at very low CPMs, preserving perceived market value. They signal to buyers what inventory is worth and discourage downward price pressure that can erode long-term demand.
What are the trade-offs between fill rate and long-term yield?
Higher floors raise CPM but can reduce fill or win rates, lowering immediate impressions. Lower floors increase fill but can teach buyers to bid lower, hurting long-term yield. Incremental testing and ML-driven optimized floors help balance short-term revenue with inventory preservation.
What are dynamic price floors and when should I use them?
Dynamic floors adjust in real time to market conditions, ideal for diverse, high-demand inventory where price sensitivity changes frequently. Use them when you need responsive pricing, but monitor sensitivity to avoid under- or overpricing.
How do tiered price floors work?
Tiered floors segment inventory by ad unit, format, partner, geography, or device, allowing different minimum CPMs for different slices. This granular approach aligns price with actual market value for each inventory type.
What are AI-driven or smart floors and what risks come with them?
AI-driven floors (e.g., Optimized floor prices) use machine learning to set per-query floors that aim to maximize long-term revenue. Risks include misconfiguration, overlap with other rules, and the need for experiments to validate outcomes—so test carefully and avoid overlapping experiments.
Where do I find Unified Pricing Rules in Google Ad Manager?
Sign in to Google Ad Manager and navigate to Inventory > Pricing rules. From there you can create, edit, explore overlap, run experiments, and view affected remnant line items.
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
“Set pricing for everything” applies the rule broadly to all inventory and is required to enable Optimized floor prices. “Set pricing for specific items” targets advertisers, sizes, or creative types. When both exist, the higher price applies.
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
Unified Pricing Rules apply to non-guaranteed demand channels: Open Auction via Authorized Buyers (AdX), Private Auctions, First Look, and third-party exchanges participating in Open Bidding. They also affect AdSense backfill and remnant line items.
How does Google Ad Exchange interact with unified pricing rules?
AdX respects UPRs set in the linked Ad Exchange account. UPRs influence AdX demand in Open Auction, Private Auctions, and First Look, and AdX receives the floor values when it evaluates bids.
How are floor prices shared with buyers in bid requests?
In OpenRTB the floor is in the bidfloor field. For the Ad Exchange protocol, the minimum is sent in minimum_cpm_micros. Bidders whose bids fall below these values see rejections labeled as “Bid was below the minimum threshold.”
What happens with multi-size requests and floors?
For multi-size requests the floor sent to buyers is the lowest floor for any eligible size. Size-specific floors are applied in auction when a buyer’s creative is matched, but the initial bid request may use the lowest eligible size floor.
How do I create a Unified Pricing Rule step by step?
Navigate to Inventory > Pricing rules > New Rule. Name the rule, choose Price Floor as the type, target inventory (ad units, placements, packages), geography, and device type. Choose pricing: Hard Floor, Target CPM, or Optimized floor prices. Save, then review Affected remnant line items and historical reports.
When should I select hard floor, target CPM, or optimized floor prices?
Use a hard floor when you need a fixed minimum CPM. Choose target CPM for dynamic floors that adapt via Google’s target CPM logic. Select Optimized floor prices (beta) to let Google’s ML set per-query floors—only available when you choose “Set pricing for everything.”
What do optimized floor prices do and how are they different from optimized pricing?
Optimized floor prices use machine learning to set per-query minimums that maximize long-term revenue while protecting inventory value. They differ from the older “optimized pricing” by actively setting floors per query, making optimized pricing unnecessary when enabled.
How do optimized floors use machine learning per query?
The ML model evaluates query-level signals and bidder behavior to predict the optimal floor for each auction, balancing fill and future bidder responses. It adapts over time to bidder patterns and market signals.
How do I enable optimized floors and what are their limits?
In a Unified Pricing Rule choose “Set pricing for everything” and select “Let Google optimize floor prices.” Optimized floors are not supported under “Set pricing for specific items” and they override overlapping pricing rules (but not advertiser-specific floors).
How do I run experiments to evaluate optimized floor performance?
In Unified Pricing Rules create a New experiment, select the rule, choose “Everything” as the pricing option and “Optimized” as the experiment price, leave the price at $0.00, and run the test. Avoid overlapping experiments to prevent spillover and confusing attribution.
How can I target pricing by device, geography, or ad unit?
In the pricing rule targeting options pick device type (desktop, mobile, tablet), geography, and specific ad units, placements, or packages. UPR supports granular slicing so floors match the market value of each inventory segment.
How do creative types like display and video affect pricing rules?
You can target rules to display or video. If Ad Manager can’t determine creative type (for example with some header bidding), it defaults to Display pricing. For video you can target skippable vs. non-skippable and minimum duration.
How does multi-size pricing work and what floor gets sent to buyers?
You can set size-specific floors, but for multi-size bid requests Ad Manager sends the lowest eligible size floor to buyers. Size-specific floors are applied when the buyer’s creative matches the size during auction.
What happens when pricing rules overlap—how does Ad Manager pick one?
When rules overlap, the rule with the higher price applies. For optimized-floor rules that overlap, the older rule is attributed in reporting though per-query pricing is independent. The higher effective floor wins between UPRs and First Look for Ad Exchange demand.
How do I use the Explore overlap tool to visualize rule interactions?
Go to Inventory > Pricing rules > Explore overlap. The tool shows the percentage of overlapping ad requests, merged settings, and lets you hover to inspect combined targeting. It uses sampled historical data to forecast overlap.
What best practices prevent conflicting or limiting pricing rules?
Avoid overly granular or conflicting rules. Keep “Pricing for everything” conservative or off to prevent unintentionally blocking higher specific prices. Limit overlapping experiments and use Explore overlap before publishing rules.
Should I set floors at the wrapper (Prebid) level, ad server level, or both?
Manage floors at both levels. Set server-side floors in Ad Manager/AdX for centralized control and set wrapper-level floors in Prebid to guide header bidding. Coordinate both to avoid blocking demand or double-enforcing floors.
What is a sample static Prebid floors configuration?
A simple pbjs.floors example sets currency, schema fields, and values by mediaType and size. For example: banner 300×250 floor $1.10, video 300×250 floor $2.00. Use pbjs.floors with clear schema to align wrapper floors with server rules.
How do dynamic Prebid floors and third-party floor providers work?
Configure pbjs.setConfig with floors that call an external endpoint. Use auctionDelay (for example 100 ms) to let the vendor respond; if the vendor fails to return, Prebid falls back to default data floors. This allows near-real-time floor signals from specialized providers.
How can I use Bid Data reports to find floor rejections?
The Bid Data Report and BidRejectionReason reveal when bids are rejected due to “Floor.” The Bid Data Report is in Beta and requires GAM 360 access. Use it to understand which buyers are tripping floors and adjust them.
What header bidding metrics should I monitor to optimize floors?
Track bid rate, win rate, and timeout rate. Low bid or win rates may indicate floors are too high or bidders are poorly configured. High timeout rates suggest auctionDelay or integration issues that can reduce effective competition.
How do I evaluate Unified Pricing Rule impact in historical reporting?
Use the Unified pricing rule dimension in Historical reports and pair it with ad size, requested ad sizes, and bid metrics. Compare CPM, fill, and revenue before and after rule changes to measure effectiveness.
How do I find remnant line items below my floor price?
In the UPR UI, review the Affected remnant line items section after saving a rule. It lists Price Priority, Network, and Bulk line items with CPMs below the floor and links to filtered tables for troubleshooting.
Why do impressions go unfilled and when do house line items serve?
Impressions go unfilled if no unified pricing rule matches the request or bids don’t meet the floor. House line items (treated as $0 Value CPM) serve only when no remnant, Ad Exchange, or Open Bidding demand is available and act as a fallback.
How do I use line item troubleshooting for "Below pricing rule floor" issues?
Use line item troubleshooting to view non-delivery causes labeled “Below pricing rule floor.” Click through to see which pricing rules affect those line items and adjust floors or remnant CPMs as needed.
What’s the recommended approach for adjusting floors incrementally?
Make small cent-level changes and monitor fill rate, CPM, and long-term yield. Incremental adjustments reduce the risk of sudden fill loss and let you measure buyer response over time.
How should I adapt floors for seasonal demand or events?
Increase floors during high-demand events and lower them during lulls to maintain fill. Plan seasonality into rules ahead of time and run short experiments during peak periods to validate the impact.
How should "Pricing for everything" be set relative to item-specific prices?
Set “Pricing for everything” conservatively—lower than item-specific prices—or disable it to avoid accidentally overriding higher per-advertiser or size-specific floors. This prevents broadly applied prices from blocking more valuable specific pricing.
What is Optimized Competition and how does it balance demand?
Optimized Competition lowers effective floors for non-guaranteed demand when guaranteed line items spike in CPM to ensure non-guaranteed channels can compete and meet delivery goals, preventing them from being blocked by temporarily high guaranteed prices.
How does Optimized Competition affect AdX, AdSense, and Prebid?
It temporarily reduces the effective price for non-guaranteed channels like AdX, AdSense, and Prebid so they can win impressions when guaranteed line items raise their CPMs to meet delivery. This balances revenue and delivery across channels.
How do I enable Optimized Competition and evaluate its performance?
Enable it at Admin > Global settings > Network settings > Ad serving settings. To evaluate, run reports breaking down metrics by Optimization type or Ad Exchange and monitor delivery, CPM, and fill shifts after activation.
Are there any final workflow tips for managing floors across Ad Manager and Prebid?
Coordinate server-side UPRs with wrapper-level floors, keep Prebid and other header bidding wrappers up to date, use Bid Data reports and unified pricing rule historical reporting to analyze impacts, and run controlled experiments before rolling out broad changes.
FAQ
How do I set floor prices in Google AdX to improve yield?
Use Google Ad Manager’s Unified Pricing Rules. Go to Inventory > Pricing rules, create a new rule, target the inventory slice, and choose a price type: Hard floor (fixed CPM), Target CPM (dynamic), or Optimized floor prices (ML-driven beta). Save and monitor affected remnant line items and reporting to measure impact.
What is a price floor and how does a target CPM differ?
A price floor is a minimum CPM you set so buyers’ bids must meet that threshold to win. A target CPM (dynamic floor) uses historical auction data to adjust the effective floor over time to balance fill rate and long-term yield while maintaining an average minimum price.
How do floors protect inventory value and prevent underselling?
Floors prevent buyers from winning premium placements at very low CPMs, preserving perceived market value. They signal to buyers what inventory is worth and discourage downward price pressure that can erode long-term demand.
What are the trade-offs between fill rate and long-term yield?
Higher floors raise CPM but can reduce fill or win rates, lowering immediate impressions. Lower floors increase fill but can teach buyers to bid lower, hurting long-term yield. Incremental testing and ML-driven optimized floors help balance short-term revenue with inventory preservation.
What are dynamic price floors and when should I use them?
Dynamic floors adjust in real time to market conditions, ideal for diverse, high-demand inventory where price sensitivity changes frequently. Use them when you need responsive pricing, but monitor sensitivity to avoid under- or overpricing.
How do tiered price floors work?
Tiered floors segment inventory by ad unit, format, partner, geography, or device, allowing different minimum CPMs for different slices. This granular approach aligns price with actual market value for each inventory type.
What are AI-driven or smart floors and what risks come with them?
AI-driven floors (e.g., Optimized floor prices) use machine learning to set per-query floors that aim to maximize long-term revenue. Risks include misconfiguration, overlap with other rules, and the need for experiments to validate outcomes—so test carefully and avoid overlapping experiments.
Where do I find Unified Pricing Rules in Google Ad Manager?
Sign in to Google Ad Manager and navigate to Inventory > Pricing rules. From there you can create, edit, explore overlap, run experiments, and view affected remnant line items.
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
“Set pricing for everything” applies the rule broadly to all inventory and is required to enable Optimized floor prices. “Set pricing for specific items” targets advertisers, sizes, or creative types. When both exist, the higher price applies.
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
Unified Pricing Rules apply to non-guaranteed demand channels: Open Auction via Authorized Buyers (AdX), Private Auctions, First Look, and third-party exchanges participating in Open Bidding. They also affect AdSense backfill and remnant line items.
How does Google Ad Exchange interact with unified pricing rules?
AdX respects UPRs set in the linked Ad Exchange account. UPRs influence AdX demand in Open Auction, Private Auctions, and First Look, and AdX receives the floor values when it evaluates bids.
How are floor prices shared with buyers in bid requests?
In OpenRTB the floor is in the bidfloor field. For the Ad Exchange protocol, the minimum is sent in minimum_cpm_micros. Bidders whose bids fall below these values see rejections labeled as “Bid was below the minimum threshold.”
What happens with multi-size requests and floors?
For multi-size requests the floor sent to buyers is the lowest floor for any eligible size. Size-specific floors are applied in auction when a buyer’s creative is matched, but the initial bid request may use the lowest eligible size floor.
How do I create a Unified Pricing Rule step by step?
Navigate to Inventory > Pricing rules > New Rule. Name the rule, choose Price Floor as the type, target inventory (ad units, placements, packages), geography, and device type. Choose pricing: Hard Floor, Target CPM, or Optimized floor prices. Save, then review Affected remnant line items and historical reports.
When should I select hard floor, target CPM, or optimized floor prices?
Use a hard floor when you need a fixed minimum CPM. Choose target CPM for dynamic floors that adapt via Google’s target CPM logic. Select Optimized floor prices (beta) to let Google’s ML set per-query floors—only available when you choose “Set pricing for everything.”
What do optimized floor prices do and how are they different from optimized pricing?
Optimized floor prices use machine learning to set per-query minimums that maximize long-term revenue while protecting inventory value. They differ from the older “optimized pricing” by actively setting floors per query, making optimized pricing unnecessary when enabled.
How do optimized floors use machine learning per query?
The ML model evaluates query-level signals and bidder behavior to predict the optimal floor for each auction, balancing fill and future bidder responses. It adapts over time to bidder patterns and market signals.
How do I enable optimized floors and what are their limits?
In a Unified Pricing Rule choose “Set pricing for everything” and select “Let Google optimize floor prices.” Optimized floors are not supported under “Set pricing for specific items” and they override overlapping pricing rules (but not advertiser-specific floors).
How do I run experiments to evaluate optimized floor performance?
In Unified Pricing Rules create a New experiment, select the rule, choose “Everything” as the pricing option and “Optimized” as the experiment price, leave the price at
FAQ
How do I set floor prices in Google AdX to improve yield?
Use Google Ad Manager’s Unified Pricing Rules. Go to Inventory > Pricing rules, create a new rule, target the inventory slice, and choose a price type: Hard floor (fixed CPM), Target CPM (dynamic), or Optimized floor prices (ML-driven beta). Save and monitor affected remnant line items and reporting to measure impact.
What is a price floor and how does a target CPM differ?
A price floor is a minimum CPM you set so buyers’ bids must meet that threshold to win. A target CPM (dynamic floor) uses historical auction data to adjust the effective floor over time to balance fill rate and long-term yield while maintaining an average minimum price.
How do floors protect inventory value and prevent underselling?
Floors prevent buyers from winning premium placements at very low CPMs, preserving perceived market value. They signal to buyers what inventory is worth and discourage downward price pressure that can erode long-term demand.
What are the trade-offs between fill rate and long-term yield?
Higher floors raise CPM but can reduce fill or win rates, lowering immediate impressions. Lower floors increase fill but can teach buyers to bid lower, hurting long-term yield. Incremental testing and ML-driven optimized floors help balance short-term revenue with inventory preservation.
What are dynamic price floors and when should I use them?
Dynamic floors adjust in real time to market conditions, ideal for diverse, high-demand inventory where price sensitivity changes frequently. Use them when you need responsive pricing, but monitor sensitivity to avoid under- or overpricing.
How do tiered price floors work?
Tiered floors segment inventory by ad unit, format, partner, geography, or device, allowing different minimum CPMs for different slices. This granular approach aligns price with actual market value for each inventory type.
What are AI-driven or smart floors and what risks come with them?
AI-driven floors (e.g., Optimized floor prices) use machine learning to set per-query floors that aim to maximize long-term revenue. Risks include misconfiguration, overlap with other rules, and the need for experiments to validate outcomes—so test carefully and avoid overlapping experiments.
Where do I find Unified Pricing Rules in Google Ad Manager?
Sign in to Google Ad Manager and navigate to Inventory > Pricing rules. From there you can create, edit, explore overlap, run experiments, and view affected remnant line items.
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
“Set pricing for everything” applies the rule broadly to all inventory and is required to enable Optimized floor prices. “Set pricing for specific items” targets advertisers, sizes, or creative types. When both exist, the higher price applies.
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
Unified Pricing Rules apply to non-guaranteed demand channels: Open Auction via Authorized Buyers (AdX), Private Auctions, First Look, and third-party exchanges participating in Open Bidding. They also affect AdSense backfill and remnant line items.
How does Google Ad Exchange interact with unified pricing rules?
AdX respects UPRs set in the linked Ad Exchange account. UPRs influence AdX demand in Open Auction, Private Auctions, and First Look, and AdX receives the floor values when it evaluates bids.
How are floor prices shared with buyers in bid requests?
In OpenRTB the floor is in the bidfloor field. For the Ad Exchange protocol, the minimum is sent in minimum_cpm_micros. Bidders whose bids fall below these values see rejections labeled as “Bid was below the minimum threshold.”
What happens with multi-size requests and floors?
For multi-size requests the floor sent to buyers is the lowest floor for any eligible size. Size-specific floors are applied in auction when a buyer’s creative is matched, but the initial bid request may use the lowest eligible size floor.
How do I create a Unified Pricing Rule step by step?
Navigate to Inventory > Pricing rules > New Rule. Name the rule, choose Price Floor as the type, target inventory (ad units, placements, packages), geography, and device type. Choose pricing: Hard Floor, Target CPM, or Optimized floor prices. Save, then review Affected remnant line items and historical reports.
When should I select hard floor, target CPM, or optimized floor prices?
Use a hard floor when you need a fixed minimum CPM. Choose target CPM for dynamic floors that adapt via Google’s target CPM logic. Select Optimized floor prices (beta) to let Google’s ML set per-query floors—only available when you choose “Set pricing for everything.”
What do optimized floor prices do and how are they different from optimized pricing?
Optimized floor prices use machine learning to set per-query minimums that maximize long-term revenue while protecting inventory value. They differ from the older “optimized pricing” by actively setting floors per query, making optimized pricing unnecessary when enabled.
How do optimized floors use machine learning per query?
The ML model evaluates query-level signals and bidder behavior to predict the optimal floor for each auction, balancing fill and future bidder responses. It adapts over time to bidder patterns and market signals.
How do I enable optimized floors and what are their limits?
In a Unified Pricing Rule choose “Set pricing for everything” and select “Let Google optimize floor prices.” Optimized floors are not supported under “Set pricing for specific items” and they override overlapping pricing rules (but not advertiser-specific floors).
How do I run experiments to evaluate optimized floor performance?
In Unified Pricing Rules create a New experiment, select the rule, choose “Everything” as the pricing option and “Optimized” as the experiment price, leave the price at $0.00, and run the test. Avoid overlapping experiments to prevent spillover and confusing attribution.
How can I target pricing by device, geography, or ad unit?
In the pricing rule targeting options pick device type (desktop, mobile, tablet), geography, and specific ad units, placements, or packages. UPR supports granular slicing so floors match the market value of each inventory segment.
How do creative types like display and video affect pricing rules?
You can target rules to display or video. If Ad Manager can’t determine creative type (for example with some header bidding), it defaults to Display pricing. For video you can target skippable vs. non-skippable and minimum duration.
How does multi-size pricing work and what floor gets sent to buyers?
You can set size-specific floors, but for multi-size bid requests Ad Manager sends the lowest eligible size floor to buyers. Size-specific floors are applied when the buyer’s creative matches the size during auction.
What happens when pricing rules overlap—how does Ad Manager pick one?
When rules overlap, the rule with the higher price applies. For optimized-floor rules that overlap, the older rule is attributed in reporting though per-query pricing is independent. The higher effective floor wins between UPRs and First Look for Ad Exchange demand.
How do I use the Explore overlap tool to visualize rule interactions?
Go to Inventory > Pricing rules > Explore overlap. The tool shows the percentage of overlapping ad requests, merged settings, and lets you hover to inspect combined targeting. It uses sampled historical data to forecast overlap.
What best practices prevent conflicting or limiting pricing rules?
Avoid overly granular or conflicting rules. Keep “Pricing for everything” conservative or off to prevent unintentionally blocking higher specific prices. Limit overlapping experiments and use Explore overlap before publishing rules.
Should I set floors at the wrapper (Prebid) level, ad server level, or both?
Manage floors at both levels. Set server-side floors in Ad Manager/AdX for centralized control and set wrapper-level floors in Prebid to guide header bidding. Coordinate both to avoid blocking demand or double-enforcing floors.
What is a sample static Prebid floors configuration?
A simple pbjs.floors example sets currency, schema fields, and values by mediaType and size. For example: banner 300×250 floor $1.10, video 300×250 floor $2.00. Use pbjs.floors with clear schema to align wrapper floors with server rules.
How do dynamic Prebid floors and third-party floor providers work?
Configure pbjs.setConfig with floors that call an external endpoint. Use auctionDelay (for example 100 ms) to let the vendor respond; if the vendor fails to return, Prebid falls back to default data floors. This allows near-real-time floor signals from specialized providers.
How can I use Bid Data reports to find floor rejections?
The Bid Data Report and BidRejectionReason reveal when bids are rejected due to “Floor.” The Bid Data Report is in Beta and requires GAM 360 access. Use it to understand which buyers are tripping floors and adjust them.
What header bidding metrics should I monitor to optimize floors?
Track bid rate, win rate, and timeout rate. Low bid or win rates may indicate floors are too high or bidders are poorly configured. High timeout rates suggest auctionDelay or integration issues that can reduce effective competition.
How do I evaluate Unified Pricing Rule impact in historical reporting?
Use the Unified pricing rule dimension in Historical reports and pair it with ad size, requested ad sizes, and bid metrics. Compare CPM, fill, and revenue before and after rule changes to measure effectiveness.
How do I find remnant line items below my floor price?
In the UPR UI, review the Affected remnant line items section after saving a rule. It lists Price Priority, Network, and Bulk line items with CPMs below the floor and links to filtered tables for troubleshooting.
Why do impressions go unfilled and when do house line items serve?
Impressions go unfilled if no unified pricing rule matches the request or bids don’t meet the floor. House line items (treated as $0 Value CPM) serve only when no remnant, Ad Exchange, or Open Bidding demand is available and act as a fallback.
How do I use line item troubleshooting for "Below pricing rule floor" issues?
Use line item troubleshooting to view non-delivery causes labeled “Below pricing rule floor.” Click through to see which pricing rules affect those line items and adjust floors or remnant CPMs as needed.
What’s the recommended approach for adjusting floors incrementally?
Make small cent-level changes and monitor fill rate, CPM, and long-term yield. Incremental adjustments reduce the risk of sudden fill loss and let you measure buyer response over time.
How should I adapt floors for seasonal demand or events?
Increase floors during high-demand events and lower them during lulls to maintain fill. Plan seasonality into rules ahead of time and run short experiments during peak periods to validate the impact.
How should "Pricing for everything" be set relative to item-specific prices?
Set “Pricing for everything” conservatively—lower than item-specific prices—or disable it to avoid accidentally overriding higher per-advertiser or size-specific floors. This prevents broadly applied prices from blocking more valuable specific pricing.
What is Optimized Competition and how does it balance demand?
Optimized Competition lowers effective floors for non-guaranteed demand when guaranteed line items spike in CPM to ensure non-guaranteed channels can compete and meet delivery goals, preventing them from being blocked by temporarily high guaranteed prices.
How does Optimized Competition affect AdX, AdSense, and Prebid?
It temporarily reduces the effective price for non-guaranteed channels like AdX, AdSense, and Prebid so they can win impressions when guaranteed line items raise their CPMs to meet delivery. This balances revenue and delivery across channels.
How do I enable Optimized Competition and evaluate its performance?
Enable it at Admin > Global settings > Network settings > Ad serving settings. To evaluate, run reports breaking down metrics by Optimization type or Ad Exchange and monitor delivery, CPM, and fill shifts after activation.
Are there any final workflow tips for managing floors across Ad Manager and Prebid?
Coordinate server-side UPRs with wrapper-level floors, keep Prebid and other header bidding wrappers up to date, use Bid Data reports and unified pricing rule historical reporting to analyze impacts, and run controlled experiments before rolling out broad changes.
FAQ
How do I set floor prices in Google AdX to improve yield?
Use Google Ad Manager’s Unified Pricing Rules. Go to Inventory > Pricing rules, create a new rule, target the inventory slice, and choose a price type: Hard floor (fixed CPM), Target CPM (dynamic), or Optimized floor prices (ML-driven beta). Save and monitor affected remnant line items and reporting to measure impact.
What is a price floor and how does a target CPM differ?
A price floor is a minimum CPM you set so buyers’ bids must meet that threshold to win. A target CPM (dynamic floor) uses historical auction data to adjust the effective floor over time to balance fill rate and long-term yield while maintaining an average minimum price.
How do floors protect inventory value and prevent underselling?
Floors prevent buyers from winning premium placements at very low CPMs, preserving perceived market value. They signal to buyers what inventory is worth and discourage downward price pressure that can erode long-term demand.
What are the trade-offs between fill rate and long-term yield?
Higher floors raise CPM but can reduce fill or win rates, lowering immediate impressions. Lower floors increase fill but can teach buyers to bid lower, hurting long-term yield. Incremental testing and ML-driven optimized floors help balance short-term revenue with inventory preservation.
What are dynamic price floors and when should I use them?
Dynamic floors adjust in real time to market conditions, ideal for diverse, high-demand inventory where price sensitivity changes frequently. Use them when you need responsive pricing, but monitor sensitivity to avoid under- or overpricing.
How do tiered price floors work?
Tiered floors segment inventory by ad unit, format, partner, geography, or device, allowing different minimum CPMs for different slices. This granular approach aligns price with actual market value for each inventory type.
What are AI-driven or smart floors and what risks come with them?
AI-driven floors (e.g., Optimized floor prices) use machine learning to set per-query floors that aim to maximize long-term revenue. Risks include misconfiguration, overlap with other rules, and the need for experiments to validate outcomes—so test carefully and avoid overlapping experiments.
Where do I find Unified Pricing Rules in Google Ad Manager?
Sign in to Google Ad Manager and navigate to Inventory > Pricing rules. From there you can create, edit, explore overlap, run experiments, and view affected remnant line items.
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
“Set pricing for everything” applies the rule broadly to all inventory and is required to enable Optimized floor prices. “Set pricing for specific items” targets advertisers, sizes, or creative types. When both exist, the higher price applies.
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
Unified Pricing Rules apply to non-guaranteed demand channels: Open Auction via Authorized Buyers (AdX), Private Auctions, First Look, and third-party exchanges participating in Open Bidding. They also affect AdSense backfill and remnant line items.
How does Google Ad Exchange interact with unified pricing rules?
AdX respects UPRs set in the linked Ad Exchange account. UPRs influence AdX demand in Open Auction, Private Auctions, and First Look, and AdX receives the floor values when it evaluates bids.
How are floor prices shared with buyers in bid requests?
In OpenRTB the floor is in the bidfloor field. For the Ad Exchange protocol, the minimum is sent in minimum_cpm_micros. Bidders whose bids fall below these values see rejections labeled as “Bid was below the minimum threshold.”
What happens with multi-size requests and floors?
For multi-size requests the floor sent to buyers is the lowest floor for any eligible size. Size-specific floors are applied in auction when a buyer’s creative is matched, but the initial bid request may use the lowest eligible size floor.
How do I create a Unified Pricing Rule step by step?
Navigate to Inventory > Pricing rules > New Rule. Name the rule, choose Price Floor as the type, target inventory (ad units, placements, packages), geography, and device type. Choose pricing: Hard Floor, Target CPM, or Optimized floor prices. Save, then review Affected remnant line items and historical reports.
When should I select hard floor, target CPM, or optimized floor prices?
Use a hard floor when you need a fixed minimum CPM. Choose target CPM for dynamic floors that adapt via Google’s target CPM logic. Select Optimized floor prices (beta) to let Google’s ML set per-query floors—only available when you choose “Set pricing for everything.”
What do optimized floor prices do and how are they different from optimized pricing?
Optimized floor prices use machine learning to set per-query minimums that maximize long-term revenue while protecting inventory value. They differ from the older “optimized pricing” by actively setting floors per query, making optimized pricing unnecessary when enabled.
How do optimized floors use machine learning per query?
The ML model evaluates query-level signals and bidder behavior to predict the optimal floor for each auction, balancing fill and future bidder responses. It adapts over time to bidder patterns and market signals.
How do I enable optimized floors and what are their limits?
In a Unified Pricing Rule choose “Set pricing for everything” and select “Let Google optimize floor prices.” Optimized floors are not supported under “Set pricing for specific items” and they override overlapping pricing rules (but not advertiser-specific floors).
How do I run experiments to evaluate optimized floor performance?
In Unified Pricing Rules create a New experiment, select the rule, choose “Everything” as the pricing option and “Optimized” as the experiment price, leave the price at
FAQ
How do I set floor prices in Google AdX to improve yield?
Use Google Ad Manager’s Unified Pricing Rules. Go to Inventory > Pricing rules, create a new rule, target the inventory slice, and choose a price type: Hard floor (fixed CPM), Target CPM (dynamic), or Optimized floor prices (ML-driven beta). Save and monitor affected remnant line items and reporting to measure impact.
What is a price floor and how does a target CPM differ?
A price floor is a minimum CPM you set so buyers’ bids must meet that threshold to win. A target CPM (dynamic floor) uses historical auction data to adjust the effective floor over time to balance fill rate and long-term yield while maintaining an average minimum price.
How do floors protect inventory value and prevent underselling?
Floors prevent buyers from winning premium placements at very low CPMs, preserving perceived market value. They signal to buyers what inventory is worth and discourage downward price pressure that can erode long-term demand.
What are the trade-offs between fill rate and long-term yield?
Higher floors raise CPM but can reduce fill or win rates, lowering immediate impressions. Lower floors increase fill but can teach buyers to bid lower, hurting long-term yield. Incremental testing and ML-driven optimized floors help balance short-term revenue with inventory preservation.
What are dynamic price floors and when should I use them?
Dynamic floors adjust in real time to market conditions, ideal for diverse, high-demand inventory where price sensitivity changes frequently. Use them when you need responsive pricing, but monitor sensitivity to avoid under- or overpricing.
How do tiered price floors work?
Tiered floors segment inventory by ad unit, format, partner, geography, or device, allowing different minimum CPMs for different slices. This granular approach aligns price with actual market value for each inventory type.
What are AI-driven or smart floors and what risks come with them?
AI-driven floors (e.g., Optimized floor prices) use machine learning to set per-query floors that aim to maximize long-term revenue. Risks include misconfiguration, overlap with other rules, and the need for experiments to validate outcomes—so test carefully and avoid overlapping experiments.
Where do I find Unified Pricing Rules in Google Ad Manager?
Sign in to Google Ad Manager and navigate to Inventory > Pricing rules. From there you can create, edit, explore overlap, run experiments, and view affected remnant line items.
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
“Set pricing for everything” applies the rule broadly to all inventory and is required to enable Optimized floor prices. “Set pricing for specific items” targets advertisers, sizes, or creative types. When both exist, the higher price applies.
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
Unified Pricing Rules apply to non-guaranteed demand channels: Open Auction via Authorized Buyers (AdX), Private Auctions, First Look, and third-party exchanges participating in Open Bidding. They also affect AdSense backfill and remnant line items.
How does Google Ad Exchange interact with unified pricing rules?
AdX respects UPRs set in the linked Ad Exchange account. UPRs influence AdX demand in Open Auction, Private Auctions, and First Look, and AdX receives the floor values when it evaluates bids.
How are floor prices shared with buyers in bid requests?
In OpenRTB the floor is in the bidfloor field. For the Ad Exchange protocol, the minimum is sent in minimum_cpm_micros. Bidders whose bids fall below these values see rejections labeled as “Bid was below the minimum threshold.”
What happens with multi-size requests and floors?
For multi-size requests the floor sent to buyers is the lowest floor for any eligible size. Size-specific floors are applied in auction when a buyer’s creative is matched, but the initial bid request may use the lowest eligible size floor.
How do I create a Unified Pricing Rule step by step?
Navigate to Inventory > Pricing rules > New Rule. Name the rule, choose Price Floor as the type, target inventory (ad units, placements, packages), geography, and device type. Choose pricing: Hard Floor, Target CPM, or Optimized floor prices. Save, then review Affected remnant line items and historical reports.
When should I select hard floor, target CPM, or optimized floor prices?
Use a hard floor when you need a fixed minimum CPM. Choose target CPM for dynamic floors that adapt via Google’s target CPM logic. Select Optimized floor prices (beta) to let Google’s ML set per-query floors—only available when you choose “Set pricing for everything.”
What do optimized floor prices do and how are they different from optimized pricing?
Optimized floor prices use machine learning to set per-query minimums that maximize long-term revenue while protecting inventory value. They differ from the older “optimized pricing” by actively setting floors per query, making optimized pricing unnecessary when enabled.
How do optimized floors use machine learning per query?
The ML model evaluates query-level signals and bidder behavior to predict the optimal floor for each auction, balancing fill and future bidder responses. It adapts over time to bidder patterns and market signals.
How do I enable optimized floors and what are their limits?
In a Unified Pricing Rule choose “Set pricing for everything” and select “Let Google optimize floor prices.” Optimized floors are not supported under “Set pricing for specific items” and they override overlapping pricing rules (but not advertiser-specific floors).
How do I run experiments to evaluate optimized floor performance?
In Unified Pricing Rules create a New experiment, select the rule, choose “Everything” as the pricing option and “Optimized” as the experiment price, leave the price at $0.00, and run the test. Avoid overlapping experiments to prevent spillover and confusing attribution.
How can I target pricing by device, geography, or ad unit?
In the pricing rule targeting options pick device type (desktop, mobile, tablet), geography, and specific ad units, placements, or packages. UPR supports granular slicing so floors match the market value of each inventory segment.
How do creative types like display and video affect pricing rules?
You can target rules to display or video. If Ad Manager can’t determine creative type (for example with some header bidding), it defaults to Display pricing. For video you can target skippable vs. non-skippable and minimum duration.
How does multi-size pricing work and what floor gets sent to buyers?
You can set size-specific floors, but for multi-size bid requests Ad Manager sends the lowest eligible size floor to buyers. Size-specific floors are applied when the buyer’s creative matches the size during auction.
What happens when pricing rules overlap—how does Ad Manager pick one?
When rules overlap, the rule with the higher price applies. For optimized-floor rules that overlap, the older rule is attributed in reporting though per-query pricing is independent. The higher effective floor wins between UPRs and First Look for Ad Exchange demand.
How do I use the Explore overlap tool to visualize rule interactions?
Go to Inventory > Pricing rules > Explore overlap. The tool shows the percentage of overlapping ad requests, merged settings, and lets you hover to inspect combined targeting. It uses sampled historical data to forecast overlap.
What best practices prevent conflicting or limiting pricing rules?
Avoid overly granular or conflicting rules. Keep “Pricing for everything” conservative or off to prevent unintentionally blocking higher specific prices. Limit overlapping experiments and use Explore overlap before publishing rules.
Should I set floors at the wrapper (Prebid) level, ad server level, or both?
Manage floors at both levels. Set server-side floors in Ad Manager/AdX for centralized control and set wrapper-level floors in Prebid to guide header bidding. Coordinate both to avoid blocking demand or double-enforcing floors.
What is a sample static Prebid floors configuration?
A simple pbjs.floors example sets currency, schema fields, and values by mediaType and size. For example: banner 300×250 floor $1.10, video 300×250 floor $2.00. Use pbjs.floors with clear schema to align wrapper floors with server rules.
How do dynamic Prebid floors and third-party floor providers work?
Configure pbjs.setConfig with floors that call an external endpoint. Use auctionDelay (for example 100 ms) to let the vendor respond; if the vendor fails to return, Prebid falls back to default data floors. This allows near-real-time floor signals from specialized providers.
How can I use Bid Data reports to find floor rejections?
The Bid Data Report and BidRejectionReason reveal when bids are rejected due to “Floor.” The Bid Data Report is in Beta and requires GAM 360 access. Use it to understand which buyers are tripping floors and adjust them.
What header bidding metrics should I monitor to optimize floors?
Track bid rate, win rate, and timeout rate. Low bid or win rates may indicate floors are too high or bidders are poorly configured. High timeout rates suggest auctionDelay or integration issues that can reduce effective competition.
How do I evaluate Unified Pricing Rule impact in historical reporting?
Use the Unified pricing rule dimension in Historical reports and pair it with ad size, requested ad sizes, and bid metrics. Compare CPM, fill, and revenue before and after rule changes to measure effectiveness.
How do I find remnant line items below my floor price?
In the UPR UI, review the Affected remnant line items section after saving a rule. It lists Price Priority, Network, and Bulk line items with CPMs below the floor and links to filtered tables for troubleshooting.
Why do impressions go unfilled and when do house line items serve?
Impressions go unfilled if no unified pricing rule matches the request or bids don’t meet the floor. House line items (treated as $0 Value CPM) serve only when no remnant, Ad Exchange, or Open Bidding demand is available and act as a fallback.
How do I use line item troubleshooting for "Below pricing rule floor" issues?
Use line item troubleshooting to view non-delivery causes labeled “Below pricing rule floor.” Click through to see which pricing rules affect those line items and adjust floors or remnant CPMs as needed.
What’s the recommended approach for adjusting floors incrementally?
Make small cent-level changes and monitor fill rate, CPM, and long-term yield. Incremental adjustments reduce the risk of sudden fill loss and let you measure buyer response over time.
How should I adapt floors for seasonal demand or events?
Increase floors during high-demand events and lower them during lulls to maintain fill. Plan seasonality into rules ahead of time and run short experiments during peak periods to validate the impact.
How should "Pricing for everything" be set relative to item-specific prices?
Set “Pricing for everything” conservatively—lower than item-specific prices—or disable it to avoid accidentally overriding higher per-advertiser or size-specific floors. This prevents broadly applied prices from blocking more valuable specific pricing.
What is Optimized Competition and how does it balance demand?
Optimized Competition lowers effective floors for non-guaranteed demand when guaranteed line items spike in CPM to ensure non-guaranteed channels can compete and meet delivery goals, preventing them from being blocked by temporarily high guaranteed prices.
How does Optimized Competition affect AdX, AdSense, and Prebid?
It temporarily reduces the effective price for non-guaranteed channels like AdX, AdSense, and Prebid so they can win impressions when guaranteed line items raise their CPMs to meet delivery. This balances revenue and delivery across channels.
How do I enable Optimized Competition and evaluate its performance?
Enable it at Admin > Global settings > Network settings > Ad serving settings. To evaluate, run reports breaking down metrics by Optimization type or Ad Exchange and monitor delivery, CPM, and fill shifts after activation.
Are there any final workflow tips for managing floors across Ad Manager and Prebid?
Coordinate server-side UPRs with wrapper-level floors, keep Prebid and other header bidding wrappers up to date, use Bid Data reports and unified pricing rule historical reporting to analyze impacts, and run controlled experiments before rolling out broad changes.
.00, and run the test. Avoid overlapping experiments to prevent spillover and confusing attribution.
How can I target pricing by device, geography, or ad unit?
In the pricing rule targeting options pick device type (desktop, mobile, tablet), geography, and specific ad units, placements, or packages. UPR supports granular slicing so floors match the market value of each inventory segment.
How do creative types like display and video affect pricing rules?
You can target rules to display or video. If Ad Manager can’t determine creative type (for example with some header bidding), it defaults to Display pricing. For video you can target skippable vs. non-skippable and minimum duration.
How does multi-size pricing work and what floor gets sent to buyers?
You can set size-specific floors, but for multi-size bid requests Ad Manager sends the lowest eligible size floor to buyers. Size-specific floors are applied when the buyer’s creative matches the size during auction.
What happens when pricing rules overlap—how does Ad Manager pick one?
When rules overlap, the rule with the higher price applies. For optimized-floor rules that overlap, the older rule is attributed in reporting though per-query pricing is independent. The higher effective floor wins between UPRs and First Look for Ad Exchange demand.
How do I use the Explore overlap tool to visualize rule interactions?
Go to Inventory > Pricing rules > Explore overlap. The tool shows the percentage of overlapping ad requests, merged settings, and lets you hover to inspect combined targeting. It uses sampled historical data to forecast overlap.
What best practices prevent conflicting or limiting pricing rules?
Avoid overly granular or conflicting rules. Keep “Pricing for everything” conservative or off to prevent unintentionally blocking higher specific prices. Limit overlapping experiments and use Explore overlap before publishing rules.
Should I set floors at the wrapper (Prebid) level, ad server level, or both?
Manage floors at both levels. Set server-side floors in Ad Manager/AdX for centralized control and set wrapper-level floors in Prebid to guide header bidding. Coordinate both to avoid blocking demand or double-enforcing floors.
What is a sample static Prebid floors configuration?
A simple pbjs.floors example sets currency, schema fields, and values by mediaType and size. For example: banner 300×250 floor
FAQ
How do I set floor prices in Google AdX to improve yield?
Use Google Ad Manager’s Unified Pricing Rules. Go to Inventory > Pricing rules, create a new rule, target the inventory slice, and choose a price type: Hard floor (fixed CPM), Target CPM (dynamic), or Optimized floor prices (ML-driven beta). Save and monitor affected remnant line items and reporting to measure impact.
What is a price floor and how does a target CPM differ?
A price floor is a minimum CPM you set so buyers’ bids must meet that threshold to win. A target CPM (dynamic floor) uses historical auction data to adjust the effective floor over time to balance fill rate and long-term yield while maintaining an average minimum price.
How do floors protect inventory value and prevent underselling?
Floors prevent buyers from winning premium placements at very low CPMs, preserving perceived market value. They signal to buyers what inventory is worth and discourage downward price pressure that can erode long-term demand.
What are the trade-offs between fill rate and long-term yield?
Higher floors raise CPM but can reduce fill or win rates, lowering immediate impressions. Lower floors increase fill but can teach buyers to bid lower, hurting long-term yield. Incremental testing and ML-driven optimized floors help balance short-term revenue with inventory preservation.
What are dynamic price floors and when should I use them?
Dynamic floors adjust in real time to market conditions, ideal for diverse, high-demand inventory where price sensitivity changes frequently. Use them when you need responsive pricing, but monitor sensitivity to avoid under- or overpricing.
How do tiered price floors work?
Tiered floors segment inventory by ad unit, format, partner, geography, or device, allowing different minimum CPMs for different slices. This granular approach aligns price with actual market value for each inventory type.
What are AI-driven or smart floors and what risks come with them?
AI-driven floors (e.g., Optimized floor prices) use machine learning to set per-query floors that aim to maximize long-term revenue. Risks include misconfiguration, overlap with other rules, and the need for experiments to validate outcomes—so test carefully and avoid overlapping experiments.
Where do I find Unified Pricing Rules in Google Ad Manager?
Sign in to Google Ad Manager and navigate to Inventory > Pricing rules. From there you can create, edit, explore overlap, run experiments, and view affected remnant line items.
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
“Set pricing for everything” applies the rule broadly to all inventory and is required to enable Optimized floor prices. “Set pricing for specific items” targets advertisers, sizes, or creative types. When both exist, the higher price applies.
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
Unified Pricing Rules apply to non-guaranteed demand channels: Open Auction via Authorized Buyers (AdX), Private Auctions, First Look, and third-party exchanges participating in Open Bidding. They also affect AdSense backfill and remnant line items.
How does Google Ad Exchange interact with unified pricing rules?
AdX respects UPRs set in the linked Ad Exchange account. UPRs influence AdX demand in Open Auction, Private Auctions, and First Look, and AdX receives the floor values when it evaluates bids.
How are floor prices shared with buyers in bid requests?
In OpenRTB the floor is in the bidfloor field. For the Ad Exchange protocol, the minimum is sent in minimum_cpm_micros. Bidders whose bids fall below these values see rejections labeled as “Bid was below the minimum threshold.”
What happens with multi-size requests and floors?
For multi-size requests the floor sent to buyers is the lowest floor for any eligible size. Size-specific floors are applied in auction when a buyer’s creative is matched, but the initial bid request may use the lowest eligible size floor.
How do I create a Unified Pricing Rule step by step?
Navigate to Inventory > Pricing rules > New Rule. Name the rule, choose Price Floor as the type, target inventory (ad units, placements, packages), geography, and device type. Choose pricing: Hard Floor, Target CPM, or Optimized floor prices. Save, then review Affected remnant line items and historical reports.
When should I select hard floor, target CPM, or optimized floor prices?
Use a hard floor when you need a fixed minimum CPM. Choose target CPM for dynamic floors that adapt via Google’s target CPM logic. Select Optimized floor prices (beta) to let Google’s ML set per-query floors—only available when you choose “Set pricing for everything.”
What do optimized floor prices do and how are they different from optimized pricing?
Optimized floor prices use machine learning to set per-query minimums that maximize long-term revenue while protecting inventory value. They differ from the older “optimized pricing” by actively setting floors per query, making optimized pricing unnecessary when enabled.
How do optimized floors use machine learning per query?
The ML model evaluates query-level signals and bidder behavior to predict the optimal floor for each auction, balancing fill and future bidder responses. It adapts over time to bidder patterns and market signals.
How do I enable optimized floors and what are their limits?
In a Unified Pricing Rule choose “Set pricing for everything” and select “Let Google optimize floor prices.” Optimized floors are not supported under “Set pricing for specific items” and they override overlapping pricing rules (but not advertiser-specific floors).
How do I run experiments to evaluate optimized floor performance?
In Unified Pricing Rules create a New experiment, select the rule, choose “Everything” as the pricing option and “Optimized” as the experiment price, leave the price at $0.00, and run the test. Avoid overlapping experiments to prevent spillover and confusing attribution.
How can I target pricing by device, geography, or ad unit?
In the pricing rule targeting options pick device type (desktop, mobile, tablet), geography, and specific ad units, placements, or packages. UPR supports granular slicing so floors match the market value of each inventory segment.
How do creative types like display and video affect pricing rules?
You can target rules to display or video. If Ad Manager can’t determine creative type (for example with some header bidding), it defaults to Display pricing. For video you can target skippable vs. non-skippable and minimum duration.
How does multi-size pricing work and what floor gets sent to buyers?
You can set size-specific floors, but for multi-size bid requests Ad Manager sends the lowest eligible size floor to buyers. Size-specific floors are applied when the buyer’s creative matches the size during auction.
What happens when pricing rules overlap—how does Ad Manager pick one?
When rules overlap, the rule with the higher price applies. For optimized-floor rules that overlap, the older rule is attributed in reporting though per-query pricing is independent. The higher effective floor wins between UPRs and First Look for Ad Exchange demand.
How do I use the Explore overlap tool to visualize rule interactions?
Go to Inventory > Pricing rules > Explore overlap. The tool shows the percentage of overlapping ad requests, merged settings, and lets you hover to inspect combined targeting. It uses sampled historical data to forecast overlap.
What best practices prevent conflicting or limiting pricing rules?
Avoid overly granular or conflicting rules. Keep “Pricing for everything” conservative or off to prevent unintentionally blocking higher specific prices. Limit overlapping experiments and use Explore overlap before publishing rules.
Should I set floors at the wrapper (Prebid) level, ad server level, or both?
Manage floors at both levels. Set server-side floors in Ad Manager/AdX for centralized control and set wrapper-level floors in Prebid to guide header bidding. Coordinate both to avoid blocking demand or double-enforcing floors.
What is a sample static Prebid floors configuration?
A simple pbjs.floors example sets currency, schema fields, and values by mediaType and size. For example: banner 300×250 floor $1.10, video 300×250 floor $2.00. Use pbjs.floors with clear schema to align wrapper floors with server rules.
How do dynamic Prebid floors and third-party floor providers work?
Configure pbjs.setConfig with floors that call an external endpoint. Use auctionDelay (for example 100 ms) to let the vendor respond; if the vendor fails to return, Prebid falls back to default data floors. This allows near-real-time floor signals from specialized providers.
How can I use Bid Data reports to find floor rejections?
The Bid Data Report and BidRejectionReason reveal when bids are rejected due to “Floor.” The Bid Data Report is in Beta and requires GAM 360 access. Use it to understand which buyers are tripping floors and adjust them.
What header bidding metrics should I monitor to optimize floors?
Track bid rate, win rate, and timeout rate. Low bid or win rates may indicate floors are too high or bidders are poorly configured. High timeout rates suggest auctionDelay or integration issues that can reduce effective competition.
How do I evaluate Unified Pricing Rule impact in historical reporting?
Use the Unified pricing rule dimension in Historical reports and pair it with ad size, requested ad sizes, and bid metrics. Compare CPM, fill, and revenue before and after rule changes to measure effectiveness.
How do I find remnant line items below my floor price?
In the UPR UI, review the Affected remnant line items section after saving a rule. It lists Price Priority, Network, and Bulk line items with CPMs below the floor and links to filtered tables for troubleshooting.
Why do impressions go unfilled and when do house line items serve?
Impressions go unfilled if no unified pricing rule matches the request or bids don’t meet the floor. House line items (treated as $0 Value CPM) serve only when no remnant, Ad Exchange, or Open Bidding demand is available and act as a fallback.
How do I use line item troubleshooting for "Below pricing rule floor" issues?
Use line item troubleshooting to view non-delivery causes labeled “Below pricing rule floor.” Click through to see which pricing rules affect those line items and adjust floors or remnant CPMs as needed.
What’s the recommended approach for adjusting floors incrementally?
Make small cent-level changes and monitor fill rate, CPM, and long-term yield. Incremental adjustments reduce the risk of sudden fill loss and let you measure buyer response over time.
How should I adapt floors for seasonal demand or events?
Increase floors during high-demand events and lower them during lulls to maintain fill. Plan seasonality into rules ahead of time and run short experiments during peak periods to validate the impact.
How should "Pricing for everything" be set relative to item-specific prices?
Set “Pricing for everything” conservatively—lower than item-specific prices—or disable it to avoid accidentally overriding higher per-advertiser or size-specific floors. This prevents broadly applied prices from blocking more valuable specific pricing.
What is Optimized Competition and how does it balance demand?
Optimized Competition lowers effective floors for non-guaranteed demand when guaranteed line items spike in CPM to ensure non-guaranteed channels can compete and meet delivery goals, preventing them from being blocked by temporarily high guaranteed prices.
How does Optimized Competition affect AdX, AdSense, and Prebid?
It temporarily reduces the effective price for non-guaranteed channels like AdX, AdSense, and Prebid so they can win impressions when guaranteed line items raise their CPMs to meet delivery. This balances revenue and delivery across channels.
How do I enable Optimized Competition and evaluate its performance?
Enable it at Admin > Global settings > Network settings > Ad serving settings. To evaluate, run reports breaking down metrics by Optimization type or Ad Exchange and monitor delivery, CPM, and fill shifts after activation.
Are there any final workflow tips for managing floors across Ad Manager and Prebid?
Coordinate server-side UPRs with wrapper-level floors, keep Prebid and other header bidding wrappers up to date, use Bid Data reports and unified pricing rule historical reporting to analyze impacts, and run controlled experiments before rolling out broad changes.
.10, video 300×250 floor .00. Use pbjs.floors with clear schema to align wrapper floors with server rules.
How do dynamic Prebid floors and third-party floor providers work?
Configure pbjs.setConfig with floors that call an external endpoint. Use auctionDelay (for example 100 ms) to let the vendor respond; if the vendor fails to return, Prebid falls back to default data floors. This allows near-real-time floor signals from specialized providers.
How can I use Bid Data reports to find floor rejections?
The Bid Data Report and BidRejectionReason reveal when bids are rejected due to “Floor.” The Bid Data Report is in Beta and requires GAM 360 access. Use it to understand which buyers are tripping floors and adjust them.
What header bidding metrics should I monitor to optimize floors?
Track bid rate, win rate, and timeout rate. Low bid or win rates may indicate floors are too high or bidders are poorly configured. High timeout rates suggest auctionDelay or integration issues that can reduce effective competition.
How do I evaluate Unified Pricing Rule impact in historical reporting?
Use the Unified pricing rule dimension in Historical reports and pair it with ad size, requested ad sizes, and bid metrics. Compare CPM, fill, and revenue before and after rule changes to measure effectiveness.
How do I find remnant line items below my floor price?
In the UPR UI, review the Affected remnant line items section after saving a rule. It lists Price Priority, Network, and Bulk line items with CPMs below the floor and links to filtered tables for troubleshooting.
Why do impressions go unfilled and when do house line items serve?
Impressions go unfilled if no unified pricing rule matches the request or bids don’t meet the floor. House line items (treated as
FAQ
How do I set floor prices in Google AdX to improve yield?
Use Google Ad Manager’s Unified Pricing Rules. Go to Inventory > Pricing rules, create a new rule, target the inventory slice, and choose a price type: Hard floor (fixed CPM), Target CPM (dynamic), or Optimized floor prices (ML-driven beta). Save and monitor affected remnant line items and reporting to measure impact.
What is a price floor and how does a target CPM differ?
A price floor is a minimum CPM you set so buyers’ bids must meet that threshold to win. A target CPM (dynamic floor) uses historical auction data to adjust the effective floor over time to balance fill rate and long-term yield while maintaining an average minimum price.
How do floors protect inventory value and prevent underselling?
Floors prevent buyers from winning premium placements at very low CPMs, preserving perceived market value. They signal to buyers what inventory is worth and discourage downward price pressure that can erode long-term demand.
What are the trade-offs between fill rate and long-term yield?
Higher floors raise CPM but can reduce fill or win rates, lowering immediate impressions. Lower floors increase fill but can teach buyers to bid lower, hurting long-term yield. Incremental testing and ML-driven optimized floors help balance short-term revenue with inventory preservation.
What are dynamic price floors and when should I use them?
Dynamic floors adjust in real time to market conditions, ideal for diverse, high-demand inventory where price sensitivity changes frequently. Use them when you need responsive pricing, but monitor sensitivity to avoid under- or overpricing.
How do tiered price floors work?
Tiered floors segment inventory by ad unit, format, partner, geography, or device, allowing different minimum CPMs for different slices. This granular approach aligns price with actual market value for each inventory type.
What are AI-driven or smart floors and what risks come with them?
AI-driven floors (e.g., Optimized floor prices) use machine learning to set per-query floors that aim to maximize long-term revenue. Risks include misconfiguration, overlap with other rules, and the need for experiments to validate outcomes—so test carefully and avoid overlapping experiments.
Where do I find Unified Pricing Rules in Google Ad Manager?
Sign in to Google Ad Manager and navigate to Inventory > Pricing rules. From there you can create, edit, explore overlap, run experiments, and view affected remnant line items.
What’s the difference between "Set pricing for everything" and "Set pricing for specific items"?
“Set pricing for everything” applies the rule broadly to all inventory and is required to enable Optimized floor prices. “Set pricing for specific items” targets advertisers, sizes, or creative types. When both exist, the higher price applies.
How do pricing rules apply across Open Auction, First Look, and Open Bidding?
Unified Pricing Rules apply to non-guaranteed demand channels: Open Auction via Authorized Buyers (AdX), Private Auctions, First Look, and third-party exchanges participating in Open Bidding. They also affect AdSense backfill and remnant line items.
How does Google Ad Exchange interact with unified pricing rules?
AdX respects UPRs set in the linked Ad Exchange account. UPRs influence AdX demand in Open Auction, Private Auctions, and First Look, and AdX receives the floor values when it evaluates bids.
How are floor prices shared with buyers in bid requests?
In OpenRTB the floor is in the bidfloor field. For the Ad Exchange protocol, the minimum is sent in minimum_cpm_micros. Bidders whose bids fall below these values see rejections labeled as “Bid was below the minimum threshold.”
What happens with multi-size requests and floors?
For multi-size requests the floor sent to buyers is the lowest floor for any eligible size. Size-specific floors are applied in auction when a buyer’s creative is matched, but the initial bid request may use the lowest eligible size floor.
How do I create a Unified Pricing Rule step by step?
Navigate to Inventory > Pricing rules > New Rule. Name the rule, choose Price Floor as the type, target inventory (ad units, placements, packages), geography, and device type. Choose pricing: Hard Floor, Target CPM, or Optimized floor prices. Save, then review Affected remnant line items and historical reports.
When should I select hard floor, target CPM, or optimized floor prices?
Use a hard floor when you need a fixed minimum CPM. Choose target CPM for dynamic floors that adapt via Google’s target CPM logic. Select Optimized floor prices (beta) to let Google’s ML set per-query floors—only available when you choose “Set pricing for everything.”
What do optimized floor prices do and how are they different from optimized pricing?
Optimized floor prices use machine learning to set per-query minimums that maximize long-term revenue while protecting inventory value. They differ from the older “optimized pricing” by actively setting floors per query, making optimized pricing unnecessary when enabled.
How do optimized floors use machine learning per query?
The ML model evaluates query-level signals and bidder behavior to predict the optimal floor for each auction, balancing fill and future bidder responses. It adapts over time to bidder patterns and market signals.
How do I enable optimized floors and what are their limits?
In a Unified Pricing Rule choose “Set pricing for everything” and select “Let Google optimize floor prices.” Optimized floors are not supported under “Set pricing for specific items” and they override overlapping pricing rules (but not advertiser-specific floors).
How do I run experiments to evaluate optimized floor performance?
In Unified Pricing Rules create a New experiment, select the rule, choose “Everything” as the pricing option and “Optimized” as the experiment price, leave the price at $0.00, and run the test. Avoid overlapping experiments to prevent spillover and confusing attribution.
How can I target pricing by device, geography, or ad unit?
In the pricing rule targeting options pick device type (desktop, mobile, tablet), geography, and specific ad units, placements, or packages. UPR supports granular slicing so floors match the market value of each inventory segment.
How do creative types like display and video affect pricing rules?
You can target rules to display or video. If Ad Manager can’t determine creative type (for example with some header bidding), it defaults to Display pricing. For video you can target skippable vs. non-skippable and minimum duration.
How does multi-size pricing work and what floor gets sent to buyers?
You can set size-specific floors, but for multi-size bid requests Ad Manager sends the lowest eligible size floor to buyers. Size-specific floors are applied when the buyer’s creative matches the size during auction.
What happens when pricing rules overlap—how does Ad Manager pick one?
When rules overlap, the rule with the higher price applies. For optimized-floor rules that overlap, the older rule is attributed in reporting though per-query pricing is independent. The higher effective floor wins between UPRs and First Look for Ad Exchange demand.
How do I use the Explore overlap tool to visualize rule interactions?
Go to Inventory > Pricing rules > Explore overlap. The tool shows the percentage of overlapping ad requests, merged settings, and lets you hover to inspect combined targeting. It uses sampled historical data to forecast overlap.
What best practices prevent conflicting or limiting pricing rules?
Avoid overly granular or conflicting rules. Keep “Pricing for everything” conservative or off to prevent unintentionally blocking higher specific prices. Limit overlapping experiments and use Explore overlap before publishing rules.
Should I set floors at the wrapper (Prebid) level, ad server level, or both?
Manage floors at both levels. Set server-side floors in Ad Manager/AdX for centralized control and set wrapper-level floors in Prebid to guide header bidding. Coordinate both to avoid blocking demand or double-enforcing floors.
What is a sample static Prebid floors configuration?
A simple pbjs.floors example sets currency, schema fields, and values by mediaType and size. For example: banner 300×250 floor $1.10, video 300×250 floor $2.00. Use pbjs.floors with clear schema to align wrapper floors with server rules.
How do dynamic Prebid floors and third-party floor providers work?
Configure pbjs.setConfig with floors that call an external endpoint. Use auctionDelay (for example 100 ms) to let the vendor respond; if the vendor fails to return, Prebid falls back to default data floors. This allows near-real-time floor signals from specialized providers.
How can I use Bid Data reports to find floor rejections?
The Bid Data Report and BidRejectionReason reveal when bids are rejected due to “Floor.” The Bid Data Report is in Beta and requires GAM 360 access. Use it to understand which buyers are tripping floors and adjust them.
What header bidding metrics should I monitor to optimize floors?
Track bid rate, win rate, and timeout rate. Low bid or win rates may indicate floors are too high or bidders are poorly configured. High timeout rates suggest auctionDelay or integration issues that can reduce effective competition.
How do I evaluate Unified Pricing Rule impact in historical reporting?
Use the Unified pricing rule dimension in Historical reports and pair it with ad size, requested ad sizes, and bid metrics. Compare CPM, fill, and revenue before and after rule changes to measure effectiveness.
How do I find remnant line items below my floor price?
In the UPR UI, review the Affected remnant line items section after saving a rule. It lists Price Priority, Network, and Bulk line items with CPMs below the floor and links to filtered tables for troubleshooting.
Why do impressions go unfilled and when do house line items serve?
Impressions go unfilled if no unified pricing rule matches the request or bids don’t meet the floor. House line items (treated as $0 Value CPM) serve only when no remnant, Ad Exchange, or Open Bidding demand is available and act as a fallback.
How do I use line item troubleshooting for "Below pricing rule floor" issues?
Use line item troubleshooting to view non-delivery causes labeled “Below pricing rule floor.” Click through to see which pricing rules affect those line items and adjust floors or remnant CPMs as needed.
What’s the recommended approach for adjusting floors incrementally?
Make small cent-level changes and monitor fill rate, CPM, and long-term yield. Incremental adjustments reduce the risk of sudden fill loss and let you measure buyer response over time.
How should I adapt floors for seasonal demand or events?
Increase floors during high-demand events and lower them during lulls to maintain fill. Plan seasonality into rules ahead of time and run short experiments during peak periods to validate the impact.
How should "Pricing for everything" be set relative to item-specific prices?
Set “Pricing for everything” conservatively—lower than item-specific prices—or disable it to avoid accidentally overriding higher per-advertiser or size-specific floors. This prevents broadly applied prices from blocking more valuable specific pricing.
What is Optimized Competition and how does it balance demand?
Optimized Competition lowers effective floors for non-guaranteed demand when guaranteed line items spike in CPM to ensure non-guaranteed channels can compete and meet delivery goals, preventing them from being blocked by temporarily high guaranteed prices.
How does Optimized Competition affect AdX, AdSense, and Prebid?
It temporarily reduces the effective price for non-guaranteed channels like AdX, AdSense, and Prebid so they can win impressions when guaranteed line items raise their CPMs to meet delivery. This balances revenue and delivery across channels.
How do I enable Optimized Competition and evaluate its performance?
Enable it at Admin > Global settings > Network settings > Ad serving settings. To evaluate, run reports breaking down metrics by Optimization type or Ad Exchange and monitor delivery, CPM, and fill shifts after activation.
Are there any final workflow tips for managing floors across Ad Manager and Prebid?
Coordinate server-side UPRs with wrapper-level floors, keep Prebid and other header bidding wrappers up to date, use Bid Data reports and unified pricing rule historical reporting to analyze impacts, and run controlled experiments before rolling out broad changes.
Value CPM) serve only when no remnant, Ad Exchange, or Open Bidding demand is available and act as a fallback.
How do I use line item troubleshooting for "Below pricing rule floor" issues?
Use line item troubleshooting to view non-delivery causes labeled “Below pricing rule floor.” Click through to see which pricing rules affect those line items and adjust floors or remnant CPMs as needed.
What’s the recommended approach for adjusting floors incrementally?
Make small cent-level changes and monitor fill rate, CPM, and long-term yield. Incremental adjustments reduce the risk of sudden fill loss and let you measure buyer response over time.
How should I adapt floors for seasonal demand or events?
Increase floors during high-demand events and lower them during lulls to maintain fill. Plan seasonality into rules ahead of time and run short experiments during peak periods to validate the impact.
How should "Pricing for everything" be set relative to item-specific prices?
Set “Pricing for everything” conservatively—lower than item-specific prices—or disable it to avoid accidentally overriding higher per-advertiser or size-specific floors. This prevents broadly applied prices from blocking more valuable specific pricing.
What is Optimized Competition and how does it balance demand?
Optimized Competition lowers effective floors for non-guaranteed demand when guaranteed line items spike in CPM to ensure non-guaranteed channels can compete and meet delivery goals, preventing them from being blocked by temporarily high guaranteed prices.
How does Optimized Competition affect AdX, AdSense, and Prebid?
It temporarily reduces the effective price for non-guaranteed channels like AdX, AdSense, and Prebid so they can win impressions when guaranteed line items raise their CPMs to meet delivery. This balances revenue and delivery across channels.
How do I enable Optimized Competition and evaluate its performance?
Enable it at Admin > Global settings > Network settings > Ad serving settings. To evaluate, run reports breaking down metrics by Optimization type or Ad Exchange and monitor delivery, CPM, and fill shifts after activation.
Are there any final workflow tips for managing floors across Ad Manager and Prebid?
Coordinate server-side UPRs with wrapper-level floors, keep Prebid and other header bidding wrappers up to date, use Bid Data reports and unified pricing rule historical reporting to analyze impacts, and run controlled experiments before rolling out broad changes.