Transparency starts with supply: why comparison matters more than ever

Britany Scott

March 19, 2026

5

minutes read

Recent weeks have brought platform economics, fee scrutiny, and single-platform dependence sharply into focus. Audit findings, supply-path exits, and very public disagreements between major holding companies and buying platforms have rightly prompted a broader conversation about transparency in programmatic.

Table of contents

But most of that conversation has centred on the demand side—which DSP, which fee structure, which buying relationship. The less visible and equally important question is what's happening underneath: how inventory is sourced, routed, and priced before it ever reaches a buyer's dashboard. Transparency that stops at the demand layer is incomplete. If the industry is serious about accountability, supply deserves a far more central role in the conversation.

The supply-side blind spot

It's understandable that buyers focus on DSP selection, audience strategy, and creative. These are the visible, controllable levers. But beneath them, the same impression can travel through multiple SSPs, each adding its own fee layer before it reaches the buyer. Platforms can prioritize their own inventory or preferred partnerships. Default supply-path routing can steer spend toward paths that serve the platform's economics rather than the advertiser's outcomes.

ANA’s benchmarks leave little room for debate. In 2024, just 43.9 cents of every programmatic dollar reached the consumer. By Q3 2025, improved accountability practices had reclaimed an estimated $13.6 billion in working media value—genuine progress by any measure. The research also confirms, however, that significant waste persists, and its origins sit upstream: not in how media is bought, but in how inventory enters the supply chain.

Pic. ANA Q3 2025 “Cost Waterfall including CTV” (Source).

Why comparison changes the equation

After-the-fact reporting is only one dimension of supply transparency. The more consequential dimension is the ability to evaluate and compare supply sources objectively while a campaign is still in flight.

When a buyer can evaluate multiple SSP paths side by side, assessing cost efficiency, directness, viewability, fraud risk, and KPI performance, they gain a fundamentally different level of control. Without comparison, they're trusting a single route and hoping it's the best one. With comparison, they can verify.

The broader market is moving in this direction. The MRC's 2026 Digital Advertising Auction Transparency Standards now require auctioneers to disclose technical fees, bid multipliers, and supply-chain intermediaries, formalizing the expectation that buyers should be able to see what's happening inside the paths their spend travels through. 

The problem with bundled and default supply paths

This is where the recent industry tensions become a supply-side story. When platforms bundle supply-path products into their buying stack—identity layers, publisher-direct integrations, inventory selection tools—and auto-enrol buyers, the supply path becomes a black box. Costs accumulate across the chain, incentives aren't always aligned with advertiser outcomes, and the buyer loses the ability to compare alternatives.

Reporting from the Digiday Programmatic Marketing Summit captured a growing concern among agency executives that AI is increasingly being positioned as a cover for greater vagueness in pricing and performance optimization, compounding existing opacity rather than resolving it.

A different black box is not the answer. What works is a supply strategy that judges paths on their merits: directness, cost, quality, and performance measured against real business KPIs, rather than following whatever route the platform favours.

What supply-first thinking looks like

In practice, this means evaluating SSP relationships based on directness and cost transparency. It means filtering out indirect traffic and unnecessary bid hops—the kind that can inflate a $25 CPM to $34 or more before it reaches the buyer. It means prioritizing KPI performance over margin structures or platform defaults. And it means maintaining the flexibility to adjust supply paths as conditions and campaign objectives change.

None of this happens automatically. It requires deliberate supply-side intelligence—the kind that treats supply selection as a strategic function, not an afterthought of the buying process.

How we approach it

This is exactly the thinking behind Smart Supply, our approach to supply-side optimization at AI Digital. Every supply path we build is outcome-driven and custom to the client's KPIs—not pulled from a static library or routed through a default stack. We work agnostically across DSPs and SSPs, filtering for direct paths, eliminating unnecessary cost layers, and making decisions based on what's actually driving efficiency and performance. There's no added cost to the buyer and no platform bias in how inventory is selected.

If supply transparency is something you're actively rethinking, or if you'd like to explore how a more comparative, KPI-driven approach could work alongside your existing buying strategy, we'd welcome the conversation.

Inefficiency

Description

Use case

Description of use case

Examples of companies using AI

Ease of implementation

Impact

Audience segmentation and insights

Identify and categorize audience groups based on behaviors, preferences, and characteristics

  • Michaels Stores: Implemented a genAI platform that increased email personalization from 20% to 95%, leading to a 41% boost in SMS click through rates and a 25% increase in engagement.
  • Estée Lauder: Partnered with Google Cloud to leverage genAI technologies for real-time consumer feedback monitoring and analyzing consumer sentiment across various channels.
High
Medium

Automated ad campaigns

Automate ad creation, placement, and optimization across various platforms

  • Showmax: Partnered with AI firms toautomate ad creation and testing, reducing production time by 70% while streamlining their quality assurance process.
  • Headway: Employed AI tools for ad creation and optimization, boosting performance by 40% and reaching 3.3 billion impressions while incorporating AI-generated content in 20% of their paid campaigns.
High
High

Brand sentiment tracking

Monitor and analyze public opinion about a brand across multiple channels in real time

  • L’Oréal: Analyzed millions of online comments, images, and videos to identify potential product innovation opportunities, effectively tracking brand sentiment and consumer trends.
  • Kellogg Company: Used AI to scan trending recipes featuring cereal, leveraging this data to launch targeted social campaigns that capitalize on positive brand sentiment and culinary trends.
High
Low

Campaign strategy optimization

Analyze data to predict optimal campaign approaches, channels, and timing

  • DoorDash: Leveraged Google’s AI-powered Demand Gen tool, which boosted its conversion rate by 15 times and improved cost per action efficiency by 50% compared with previous campaigns.
  • Kitsch: Employed Meta’s Advantage+ shopping campaigns with AI-powered tools to optimize campaigns, identifying and delivering top-performing ads to high-value consumers.
High
High

Content strategy

Generate content ideas, predict performance, and optimize distribution strategies

  • JPMorgan Chase: Collaborated with Persado to develop LLMs for marketing copy, achieving up to 450% higher clickthrough rates compared with human-written ads in pilot tests.
  • Hotel Chocolat: Employed genAI for concept development and production of its Velvetiser TV ad, which earned the highest-ever System1 score for adomestic appliance commercial.
High
High

Personalization strategy development

Create tailored messaging and experiences for consumers at scale

  • Stitch Fix: Uses genAI to help stylists interpret customer feedback and provide product recommendations, effectively personalizing shopping experiences.
  • Instacart: Uses genAI to offer customers personalized recipes, mealplanning ideas, and shopping lists based on individual preferences and habits.
Medium
Medium

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