Relevant Digital Added Automated Floor Price Tool

Publishers using the Relevant Yield platform now have access to a machine-learning engine that dynamically adjusts floor prices.

Updated on Sept. 23, 2026 in Advertising

Isometric editorial illustration featuring cascading metal cubes, representing dynamic adjustment of digital pricing systems.
Relevant Digital has integrated a machine-learning engine into its Relevant Yield platform, allowing publishers to automate floor price adjustments in real-time. AI Illustration. Upload story photo >

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Relevant Digital has integrated an automated floor price optimization engine into its Relevant Yield platform. The tool is designed to boost publisher revenue by dynamically adjusting floor prices based on real-time auction signals.

Why it matters

The tool replaces static pricing rules with dynamic adjustments, allowing publishers to better navigate shifting auction environments. This automation helps capture more value from ad inventory without requiring manual intervention for every price change.

The system processes 60 auction metrics and dimensions to drive a reported revenue uplift of 2% to 4% for publishers. The feature is now available to all current platform users at no additional cost.

The players

Relevant Digital

A digital advertising technology firm that provides yield management platforms for publishers.

Relevant Yield

An advertising management platform that integrates multiple auction sources and ad servers.

The details

The engine uses machine learning models that update multiple times throughout the day to react to changing auction data. It supports integration with Prebid, ad servers, Amazon TAM, and OpenAds. Publishers maintain operational control through configurable minimum floor prices and the ability to enable the system at the individual placement level.

Timeline

  1. September 23, 2026: Relevant Digital launched the automated floor price optimization tool.

Market Landscape

This move reflects the broader industry shift from static floor pricing to algorithmic, signal-based management in programmatic auctions. It follows a growing pattern where ad-tech platforms integrate machine learning to automate yield optimization across multiple supply sources.

Publishers should evaluate whether their existing placement-level floor settings provide the necessary guardrails for this new automated engine. Operators should monitor revenue performance across their specific ad inventory segments to determine if the 2-4% uplift holds under their unique traffic mix.

The takeaway

Automating price floors can help maximize inventory value in volatile programmatic auctions. Publishers should consider running an A/B test on a single placement to benchmark the tool's performance against their historical revenue baseline before a full rollout.

Further reading

For more on evolving digital monetization strategies, see our Advertising section.

Source note: This article includes information reported by Exchangewire.

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Do you trust automated machine learning systems to manage your business pricing strategies?