This article will examine how traffic shaping can serve as a strategic remedy for the prevalent issue of bidstream bloat in programmatic advertising. It will delve into methods for reducing extraneous bidstream noise to boost operational efficiency while simultaneously enhancing demand to drive increased revenue for publishers. The piece should balance a technical exploration of traffic shaping with actionable insights for publishers, advertisers, and ad ops professionals.
Introduction
The exponential rise of programmatic advertising has brought both opportunities and challenges. Bidstream bloat is one such critical challenge that reduces operational efficiency and limits revenue potential. Digital publishers, supply-side platforms (SSPs), and demand-side platforms (DSPs) handle massive bid request volumes, many of which are redundant or low-value.
According to eMarketer, bid request volumes increased 2.3 times between 2020 and 2023, while programmatic ad spending grew by only 18% in the same period. Such a mismatch creates inefficiencies, unnecessary costs, and data congestion.There is an urgent need for solutions that streamline data flows and optimise inventory value. Traffic shaping has emerged as a powerful solution that helps filter out unnecessary data, ensuring high-quality impressions.
Bidstream bloat refers to the phenomenon where the volume of bid requests far exceeds the actual value of impressions, leading to inefficiencies and increased costs. Industry experts have highlighted that while the volume of auction requests has surged, often reaching up to 30 million per second, DSPs can process only a fraction (approximately 3 million per second). This imbalance leads to significant filtering, where valuable inventory is "crowded out" by duplicate and redundant requests.
As a way to selectively control the flow of ad requests, traffic shaping has emerged as a key remedy. By prioritising high-quality traffic and filtering out low-value or duplicate requests, traffic shaping improves both operational efficiency and revenue outcomes. In the following sections, we look into the causes of bidstream bloat, explain how traffic shaping works, and outline strategies for its successful implementation.
Understanding Bidstream Bloat
Bidstream bloat is characterised by an excess volume of bid requests that saturate the programmatic ecosystem. Key contributors include:
- Excessive Data Transmission: Publishers and SSPs often send multiple, overlapping bid requests, while the average DSP is capable of processing only a limited number of such requests. This creates a massive disconnect between the available supply and the demand processing capacity.
- Duplicate and Crowded Requests: The practice of integrating multiple SSPs and sending duplicate requests leads to "crowding out" where valuable inventory is obscured by identical requests. This duplication not only dilutes the quality of available impressions but also hampers the ability of DSPs to evaluate diverse inventory.
- Conflicting Incentives: SSPs are incentivised to maximise revenue by winning bids, even if that means sending numerous identical requests to ensure that they are included in the auction. In contrast, publishers need a balanced approach to monetise both high- and mid-value inventory effectively.
- Increased Supply Without Proportional Demand: While new formats such as connected TV (CTV) and shifting user habits have expanded supply, corresponding ad budgets have not grown at the same pace.
Impacts on Operational Efficiency and Ad Performance
The effects of bidstream bloat are significant.
- Processing Overload: With DSPs processing only a small fraction of incoming requests, the excess volume leads to increased cloud and operational costs.
- Latency and Delayed Bidding: The excessive number of bid requests can introduce delays, slowing down the decision-making process and potentially impacting user experience.
- Wasted Impressions: Valuable inventory may be overlooked due to the sheer volume of duplicate requests, resulting in lost revenue opportunities and inefficient auctions.
- Revenue Disparity: There is a growing gap between top-performing inventory and the bottom half, where the over-monetised high-value inventory coexists with under-monetised, low-value impressions.
These challenges highlight the need for a solution that not only reduces irrelevant bid traffic but also ensures that DSPs receive the most relevant and high-quality signals.
Traffic Shaping Explained
Traffic shaping is the strategic process of controlling and optimising which ad requests are forwarded to SSPs, DSPs, and other ad tech partners. It involves filtering out low-value or redundant bid requests and ensuring that only high-quality, relevant impressions reach the auction. This focused approach enables better decision-making and higher-quality bids.
- Filtering Irrelevant Traffic: Advanced algorithms analyse bid requests to identify and block low-quality, duplicate, or redundant signals. This process is crucial in addressing the “crowding out” effect and ensuring that DSPs are not overwhelmed by excessive requests.
- Prioritising High-Value Impressions: By setting floor prices and using criteria such as domain, placement ID, and integration method, traffic shaping ensures that only the most promising impressions are prioritised. This selective process is critical in environments where DSPs impose queries per second (QPS) caps to manage their processing capacity.
- Dynamic Optimisation: The approach can be enhanced by machine learning techniques that automatically adjust filtering parameters based on real-time data. Automated traffic shaping enables publishers to adapt to market fluctuations and optimise inventory dynamically.
For example, publishers using platforms such as Google Ad Manager or DoubleClick for Publisher can integrate traffic shaping strategies to control the flow of bid requests effectively. Advanced solutions, such as Google Ad Manager 360, provide enhanced data insights that help fine-tune the parameters of traffic shaping. Moreover, techniques like key-value targeting play an important role in segmenting audiences and ensuring that the right signals reach the right buyers.
Balancing Efficiency and Demand: The Dual Benefits of Traffic Shaping
An effective traffic shaping strategy delivers dual benefits: it reduces bidstream noise while boosting demand. Achieving the right balance is critical, as over-filtering might lead to underexposure of valuable inventory, whereas under-filtering may not mitigate the issues associated with bidstream bloat.
Reducing Bidstream Noise
Traffic shaping minimises the clutter in the bidstream by doing the following:
- Eliminating Duplicates: By filtering out repetitive and low-value bid requests, the system prevents "crowding out” ensuring that each request carries unique, high-quality data.
- Enhancing Signal Accuracy: With a cleaner bidstream, DSPs receive more accurate signals, which helps them make better-informed bidding decisions. This results in more efficient processing and reduced operational costs.
- Lowering Latency: Reduced noise leads to faster processing times, thereby decreasing latency and improving the overall speed of the ad auction process.
Increasing Demand and Revenue
A refined bidstream offers several revenue advantages.
- Improved Auction Quality: With fewer low-quality requests, high-value impressions attract stronger bids. This drives better fill rates and enables publishers to command higher cost per mille (CPM) rates.
- Focused Demand Generation: Traffic shaping ensures that DSPs see the most relevant and premium inventory. This focused exposure enhances targeting precision and increases the likelihood of securing competitive bids.
- Revenue Optimisation Across Inventory: A balanced approach allows publishers to monetise both high-performing and mid-level inventory effectively. Rather than simply maximising revenue per SSP, publishers can optimise the entire SSP portfolio.
Industry experts emphasise that while reducing extraneous bid traffic is essential, maintaining a sufficient volume of quality impressions is equally important to attract diverse and competitive demand.
Strategies for Implementing Traffic Shaping
Implementing traffic shaping requires a systematic approach that combines data analysis, technology selection, and ongoing optimisation. Here are six actionable strategies based on industry insights.
1. Evaluate Your Ad Inventory
- Comprehensive Data Analysis: Begin by reviewing detailed performance metrics to identify which placements generate the highest revenue and which ones lag. Use platforms such as Google Ad Manager to gather data.
- Segmenting and Prioritisation: Leverage techniques such as key-value targeting to segment your inventory based on performance indicators. Prioritise high-yield placements while considering strategies to enhance mid-level inventory, which often suffers from crowding out.
- Identifying Duplication Patterns: Analyse how many duplicate requests are being sent and identify patterns that contribute to bidstream bloat. Understanding these trends is key to designing effective filtering rules.
2. Choose the Right Traffic Shaping Tools and Partners
- Integration and Compatibility: Select tools that integrate seamlessly with your existing ad tech stack. For publishers using Google Ad Manager, ensuring compatibility with current systems is essential.
- Real-Time Analytics: Opt for solutions that offer real-time insights, enabling you to adjust filters and thresholds dynamically based on market conditions.
- Customisability: The ideal traffic shaping solution should allow for granular control over filtering parameters, enabling you to set specific thresholds for different types of inventory.
3. Set Clear Performance Metrics
Establish measurable goals to assess the effectiveness of your traffic shaping strategy.
- Bid Response Accuracy: Track the ratio of bid requests that result in successful bids. Improved accuracy indicates better-quality traffic reaching the DSPs.
- Cost Reduction: Monitor reductions in processing costs and overall operational expenses.
- Revenue Impact: Evaluate changes in fill rates, CPMs, and overall revenue performance before and after implementing traffic shaping.
4. Experiment with Filters and Thresholds
Traffic shaping is an iterative process that requires continuous testing.
- A/B Testing: Run experiments to compare the performance of different filtering strategies. Test various parameters such as floor prices, domain filters, and integration methods.
- Dynamic Adjustments: Use machine learning to automate adjustments in real time. Automated traffic shaping can respond to market fluctuations and optimise inventory without constant manual intervention.
- Feedback Integration: Collect feedback from ad ops teams, DSPs, and SSPs to refine your strategies continually. Collaboration with partners is crucial for identifying what works best in a dynamic environment.
5. Collaborate with Industry Partners
Effective traffic shaping requires alignment across the ecosystem.
- Clear Communication: Establish clear expectations with SSPs and DSPs regarding traffic shaping guidelines. Ensure that partners understand the importance of sending high-quality, non-duplicative traffic.
- Joint Monitoring: Set up regular review sessions with your partners to analyse performance data and discuss potential adjustments. A collaborative approach helps address challenges such as QPS caps and duplication effectively.
- Unified Strategies: Consider industry initiatives that encourage unified traffic shaping across multiple SSP connections. This not only streamlines processes but also enhances overall auction performance.
6. Leverage Automation and Advanced Analytics
The future of traffic shaping lies in automation.
- Machine Learning Integration: Employ automated systems that use machine learning to analyse data in real time. This approach helps dynamically adjust traffic shaping parameters, ensuring optimal performance despite fluctuating market conditions.
- Real-Time Data Processing: Tools that offer real-time insights enable you to see immediate effects of any adjustments, allowing for rapid fine-tuning and improved decision-making.
- Advanced Signal Processing: Use techniques such as key-value targeting, along with identity management tools, such as Google MCM and Google PPID, to deliver more precise audience segmentation and improved ad targeting.
Challenges and Considerations
While traffic shaping offers substantial benefits, there are challenges that must be managed carefully.
Over-Filtering and Under-Filtering
Finding the right balance is crucial.
- Over-Filtering: Setting overly strict criteria can inadvertently block valuable traffic, reducing the overall volume and potentially cutting off premium demand.
- Under-Filtering: Insufficient filtering fails to address the bidstream bloat, leaving DSPs overwhelmed and impairing auction efficiency.
Technical Integration
Integrating traffic shaping solutions with existing ad tech stacks presents its own set of challenges.
- Compatibility Issues: Ensuring that new tools work seamlessly with platforms such as Google Ad Manager 360 is essential to avoid disruptions.
- Maintaining Low Latency: The additional layers of traffic shaping should not introduce significant delays. Real-time data analytics and automation are key to minimising latency.
Continuous Monitoring and Adaptation
Given the rapidly changing world of digital advertising, traffic shaping is not a set-it-and-forget-it strategy.
- Regular Reviews: Implement periodic reviews of performance metrics, and adjust filtering parameters as needed.
- Industry Collaboration: Ongoing dialogue with SSPs, DSPs, and technology partners is necessary to stay ahead of market trends and address new challenges such as evolving QPS caps and duplication practices.
- Data-Driven Decisions: Maintain a robust system for tracking and analysing bid responses, ensuring that every change is supported by solid data.
Future Trends
The field of traffic shaping is evolving rapidly, with several key trends set to shape its future.
- AI-Driven Optimisation: Advances in machine learning are enabling more sophisticated, automated traffic shaping that adapts in real time, reducing the need for manual intervention.
- Enhanced Real-Time Analytics: As real-time data processing improves, traffic shaping tools will be able to respond more swiftly to market changes, ensuring that DSPs receive only the most relevant impressions.
- Unified Ecosystem Collaboration: There is growing momentum towards unified traffic shaping solutions that span multiple SSPs, reducing duplication and maximising overall yield.
- Targeted Inventory Optimisation: Publishers are expected to further refine their strategies by focusing not just on high-value inventory but also on optimising mid-level inventory that often suffers from crowding out.
Conclusion
Traffic shaping is a strategic solution designed to address the persistent challenges of bidstream bloat. By filtering out redundant and low-value bid requests, traffic shaping enhances operational efficiency and improves revenue outcomes. It not only benefits DSPs and SSPs by reducing processing overhead and latency but also helps publishers to achieve a more balanced and effective monetisation strategy. The key to successful traffic shaping lies in a combination of careful data analysis, the right technological tools, and a willingness to adapt to changing market dynamics.
For publishers, the message is clear: addressing bidstream bloat requires a proactive, data-driven approach that adopts traffic shaping as a core component of your ad operations. By evaluating your inventory, choosing the right tools, setting clear performance metrics, and collaborating closely with SSPs and DSPs, you can optimise your bidstream, improve auction outcomes, and, ultimately, drive higher revenue.
The future of programmatic advertising depends on our ability to refine and streamline the flow of bid requests. With the integration of automated, AI-driven traffic shaping solutions and real-time analytics, the industry is poised to overcome the challenges of bidstream bloat and unlock new levels of efficiency and performance. Now is the time for publishers, advertisers, and ad ops professionals to invest in this transformative approach. By doing so, you can create a powerful, revenue-positive model of programmatic advertising that stands up to the challenges of today and is ready for the innovations of tomorrow. Reach out to Publift today to learn about how we’re implementing traffic shaping practices for our publishers.