Demand path optimization: Why publishers must rethink demand efficiency in 2026

In 2025, SSP owners are under heavier pressure. SSPs now spend 4.9% of their revenue on cloud infrastructure. With a median of 8.6%, inefficient QPS eats into margins. Amidst this, major DSPs are actively reducing their supply paths, cutting off routes they consider low-quality or too expensive. This shift exposes real weaknesses: duplicated bid requests, inefficient routing, expensive log pipelines, and inconsistent access to buyers. 

MFA domains and duplicate traffic patterns are another reason for hidden costs. Even when MFA sites are filtered at the supply or demand layer, their behavior often slips through as hyper-inflated QPS, repetitive ad calls, or artificially refreshed page sessions. SSPs tend to spend $30–$60 per 100k QPS just to process and log requests.

Instead of flooding DSPs with every impression, demand path optimization offers the best way to restructure traffic. DPO logic ensures that only valuable, revenue-proven paths are used.

However, it’s not just about shortening the path between publishers and advertisers. For SSP owners, this digital advertising approach helps control costs, improve traffic quality, and balance query efficiency with revenue growth.

So, what exactly does DPO mean?

Demand Path Optimization reflects the principles of supply path optimization — they’re two parts of the same process. While SPO focuses on how advertisers find the best and most transparent routes to inventory, DPO flips the perspective. When applied together, they create a balanced environment where DSPs shorten the supply chain, while SSPs optimize the path to buyers. 

DPO is about understanding how advertisers and agencies reach a publisher’s inventory. With the data collected from DPO, publishers can see the different routes their ad impressions take before being purchased. This enables them to make intentional choices about every intermediary in their stack. 

The DPO process encourages publishers to research the benefits middlemen offer and weigh them against the fees they charge. If your partner doesn’t add any value, you’d rather do away with these additional costs. By prioritizing high-value demand partners and optimizing traffic flow, DPO helps SSPs reduce infrastructure costs per QPS. Instead of scaling by volume, growth is measured by how efficiently requests convert into revenue, not by how many are sent.

The new generation of DPO 

DPO today is all about aligning with SPO logic at a technical, analytical, and financial level. Modern SPO logic filters out intermediaries that don’t add clear, measurable value, cutting unnecessary routes. When the bidstream becomes clean and predictable, DSPs automatically raise partner quality scores, expand routes, and allocate more spend. Instead of static rules and manual filtering, the new generation of DPO relies on ML scoring models that evaluate partner value in real time. Taking into account bid density, response consistency, QPS-to-cleared impact, latency, win rate, and credit reliability, they automatically prioritize high-performing partners, throttle low-value traffic, and dynamically adjust routing tables to align with DSP expectations. Over time, the models learn inefficient patterns and predict which routes are likely to waste QPS.

To ensure their platform remains a preferred source of premium demand, SSPs should integrate ML into DPO. This is what separates the modern era from the 2021 DPO predecessor. DPO has evolved into an intelligent, real-time system for protecting SSP margins and optimizing demand paths.

The real impact of DPO for publishers 

With so many intermediaries involved, it’s not always clear where the money goes. Some of the fees are fair — like paying for tech, services, or access to premium advertisers — while others don’t add much at all. And sometimes they are entirely hidden. When that clarity is missing, you end up paying twice for the same access to demand. 

Each extra fee chips away at the publisher’s CPM. A study by ISBA and PwC found that publishers receive only about 51% of total ad spend. That number has improved to about 65%, showing the industry is moving in the right direction. But there’s still work to do.

Who are the key players and where do the fees come from?

Many SSP platforms operate with a duplicate-request rate of 35–60%. This means a huge portion of their traffic delivers zero value and only adds to server costs. For example, for some SSPs, the cost per 1M requests may vary from a few dollars to several dozen dollars, depending on the cloud setup, log storage, and bandwidth. And when you’re dealing with billions of requests per day, even small inefficiencies turn into expenses. More traffic doesn’t mean more money anymore. It just means more cost.

Financial efficiency

Every bid request consumes server resources — from processing power and bandwidth to log storage and API calls. With billions of queries per day, it is clear that duplicate requests are real cost centers. Many SSPs see this firsthand when their QPS jumps from 1B to 1.5B per day. However, their RPM stays the same.

Without DPO, SSPs often equate growth with scale: more traffic, more partners, more requests. The infrastructure has to work harder, consuming more compute, storage, and bandwidth. In practice, this shows a 40% increase in infrastructure spending without proportional yield growth. Teams start scoring, filtering, or throttling demand just to keep the system stable.

By cleaning up duplicate traffic and removing low-value routes, DPO helps SSPs lower their QPS and reduce infrastructure costs, enabling the platform to shift to a sustainable cost-to-revenue model.

By ensuring that every step in the supply chain contributes measurable value, the demand path becomes more efficient and transparent. Instead of scaling by volume, growth is measured by how efficiently requests convert into revenue, not by how many are sent.

Technical resilience

DPO is not a marketing initiative. It is a part of the SSP’s core architecture, defining how your routing tables evolve as partners’ behavior changes. DPO allows routing tables to update based on partner performance, latency patterns, or bid responsiveness so inefficient ones are automatically deprioritized or paused.

With a transparent and efficient demand path, SSPs can clearly demonstrate inventory quality to buyers, thereby increasing revenue. DPO allows SSPs to implement more advanced traffic-shaping techniques, including throttling partners that return high-latency or low-value bids. Some SSPs implement multi-layer throttling, where limits change based on time of day, region, partner category, or system load.

DPO also lets SSPs assign each route a predictive score based on historical win rate. High-scoring routes get prioritized in routing tables, while low-scoring ones are automatically throttled or removed.

Log-level data allows SSP owners to evaluate each partner's health using granular diagnostics that aggregate timeout rates, creative rejection frequency, invalid traffic alerts, payment behavior, and contribution to infrastructure cost.

This is a foundation for curated deals, allowing SSPs to package inventory not just by placement or audience, but by partner reliability, response quality, and technical efficiency. But to build true curatorial logic, you need to have a controlled demand path first. Otherwise, you will get chaotic requests without any logic.

DPO opens the door to preferred partnerships and more direct programmatic deals, which often come with premium pricing. The more visibility SSPs have over how buyers reach the inventory, the more leverage they gain in negotiations with DSPs and agencies.

Analytical intelligence

DPO connects log-level auction data with real-time operational decisions inside SSPs. Without granular request logs, predictive scoring, and ML-driven anomaly detection, it is hard to understand the full lifecycle of an impression. By transforming raw signals into decision-ready intelligence, DPO can analyze bid density and detect when partners start bidding less frequently than expected. The model detects the deviation long before the fill rate starts to fall, so SSPs can proactively reroute traffic, adjust filters, and deprioritize the partner.

Many partners can respond quickly during peak hours but slow down or time out at night. These may increase the number of impressions lost before an auction begins. With DPO, the SSP can monitor response-time variance, and detect unstable behavior. Some resellers may also consume significant QPS but contribute no cleared wins. DPO enables SSPs to restrict low-impact buyers and reduce unnecessary server load. If a partner shows strong bid signals but an increasing volume of failed creatives or poor credit behavior, their score decreases automatically, prompting the system to shift traffic toward higher-performing buyers.

The new standard for SSP efficiency 

The problem we all see now is not revenue but the infrastructure costs. SSP platforms are seeing growing demand, but their infrastructure is consuming too much. But SSPs can’t grow solely by sending more traffic — volume alone no longer guarantees access to premium demand.

I see DPO as a strategy for economic survival, not just a one-time setup to correct routing logic. TeqBlaze implements DPO logic at the technology level, not through manual configuration or UI shortcuts. Controlled, transparent demand paths lay the groundwork for curated deals and ML-based floor optimization, allowing SSPs to package premium inventory in ways buyers can trust.  With SPO pressure and systemic risks such as MFA, the new generation of DPOs transforms SSP into an intelligent, data-driven platform.

Nevertheless, we shouldn’t treat it as a marketing initiative. It needs to be a part of the SSP’s core architecture, defining how requests are routed, filtered, and prioritized before any ad is served. When you pair the DPO process with ongoing operational practices, its potential doubles, and complexity becomes an opportunity. 

It’s not about cutting demand — it’s about building a structure where every request serves a purpose and every QPS contributes to real value. Contact our team and explore how you can scale your SSP intelligently with every request justified by data, not guesswork.