How traffic-shaping tools powered by real-time demand insights are redefining programmatic efficiency

These inefficiencies manifest in wasted ad spend due to duplicate bid requests, reduced campaign performance from suboptimal inventory matching, strained technical infrastructure and increased operational costs and difficulty achieving campaign goals due to inconsistent access to desired audiences. Meanwhile, DSPs and SSPs face growing processing overhead as they manage an ever-increasing volume of bid requests, some of which never result in delivered impressions. 

This cycle of waste impacts everyone in the supply chain, ultimately making it harder for advertisers to maximize their return on ad spend and effectively reach their target consumers.

Why traditional traffic-shaping tools fall short of ad tech’s ambitions

Traditional traffic-shaping solutions — including supply path optimization (SPO), pre-bid filtering and query-per-second (QPS) throttling — have attempted to address these challenges. However, many of these methods lack real-time intelligence and instead result in missed opportunities and suboptimal performance.

“The fundamental issue is how the advertising system operates today,” said Mark McEachran, svp of product management at Yieldmo. “Suppliers flood the system with every possible ad opportunity, hoping to find the right match for advertisers. This creates a massive processing burden for DSPs and, ultimately, unnecessary costs and inefficiencies for advertisers trying to reach their audiences.”

This creates an environment where SSPs face pressure from DSPs to clean up traffic. Inefficient bid streams hurt publishers by lowering CPMs due to reduced bid competition for high-quality inventory. According to a 2023 Association of National Advertisers report, programmatic inefficiencies account for up to a 35% loss in potential ad revenue for publishers.

A new collaborative approach to traffic optimization

A more collaborative, sustainability-driven approach between DSPs and SSPs can potentially transform programmatic advertising — including meeting the growing demand for more sustainable ad-buying practices, improved monetization for publishers and better performance for advertisers.

For instance, Amazon DSP has launched a new collaborative traffic-shaping tool, Dynamic Traffic Engine (beta), that enables Amazon DSP to share real-time demand insights with SSPs. By enabling real-time communication of demand requirements, DTE helps SSPs deliver more relevant inventory while reducing unnecessary bid requests. This alignment of supply with actual demand not only reduces wasted impressions but also improves campaign performance and operational efficiency across the programmatic supply chain.

“Dynamic Traffic Engine is a key component of our strategy to help advertisers efficiently access quality inventory across the open web,” said Chris Conetta, head of supply at Amazon DSP. “By providing granular, real-time demand insights to SSPs, we can communicate exactly what inventory our advertisers need. This helps SSPs optimize their traffic to match our customers’ demand, ultimately, ensuring advertisers can effectively reach their target audiences while reducing wasted bid requests, leading to better campaign performance.”

DTE helps shape traffic patterns in real-time, ensuring more efficient use of resources across the programmatic supply chain. 

“With Dynamic Traffic Engine, Amazon proactively gives us instructions on the traffic they’re looking for, so we can shape it to their needs and send it faster once the campaign starts,” McEachran said.

During testing the tool reduced undesired or low-demand bid requests by over 40%, while Yieldmo reported a 7% improvement in fill rate and spend per million ad requests on participating traffic. 

“The solution was cost-effective to implement and reduced operational costs,” McEachran said. “Amazon’s granular instructions on which attributes to look at improved our efficiency significantly.”

The results of Yieldmo’s pilot also have implications for others in the industry.

“The results mean advertisers are getting more of the inventory they want, with less waste, leading to better campaign performance across the open web,” Conetta said.

Scaling privacy-safe demand insights across the programmatic supply chain

Amazon’s approach with DTE exemplifies how programmatic efficiency can be achieved while maintaining strong data privacy standards. 

The solution uses aggregated demand signals that protect advertiser data, enabling SSPs to optimize their traffic effectively. This privacy-centric design, combined with lightweight technical requirements, makes it easier for SSPs to implement DTE and immediately begin improving their inventory management.

“Every SSP is at a different stage of their journey in optimizing traffic flow,” Conetta said. “To be successful, they need technology solutions that can meet them where they are and grow with them as their capabilities evolve.”

When looking ahead, the potential for collaborative traffic shaping extends beyond its current capabilities, with more intelligent and responsive systems. 

“We see Dynamic Traffic Engine as a stepping stone towards a more intelligent programmatic solution that will benefit stakeholders,” Conetta said. “In the future, we envision Dynamic Traffic Engine predicting and shaping traffic patterns in real-time. This will help advertisers access the most relevant inventory for their specific goals, driving campaign efficiency and ROI. Agencies will be able to deliver improved results for their clients, while publishers and SSPs will experience better monetization of their inventory and reduced infrastructure costs.”

As the industry continues to evolve, collaborative traffic shaping powered by secure demand insights will play an increasingly crucial role in addressing programmatic inefficiencies. While challenges remain, the trend towards more intelligent, collaborative traffic shaping appears poised to transform the programmatic landscape in the years to come.

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