Retail media in 2026 is data-rich and operationally disconnected. The gaps between data silos are precisely where performance is lost.
As retail media networks continue to multiply, advertising teams face a compounding challenge: more tools, more reporting dashboards, and more rules to navigate—across both retailer platforms and their own internal systems. Ad data, sales data, inventory signals, and merchandising context all exist in separate environments, rarely speaking the same language.
That disconnect makes two critical questions surprisingly difficult to answer:
- Where should I invest? When reporting is inconsistent across retailers, comparing campaign performance—let alone allocating budget with confidence—becomes a guessing game.
- Which SKUs will lead to the best business outcome? Is the product you’re advertising actually in stock? Is the PDP optimized for conversion? What’s the margin likely to be once the sale is made?
This guide breaks down the real cost of retail media fragmentation—what we call the ‘Silo Tax’—and the practical steps leading brands are taking to reduce it by connecting data, unifying reporting, and aligning teams around shared commercial goals.
What Is Media Fragmentation?
Media fragmentation happens when the platforms, data, and workflows teams rely on to plan, execute, and measure retail media are disconnected from each other—and from the broader commerce operation.
It’s accelerating. Retail media spend is on pace to grow 15% annually, reaching $230 billion by 2028. But growth in investment hasn’t been matched by growth in operational clarity. The result: more data, more tools, more reporting—and less ability to see what’s actually working.
Three structural forces are driving this:
- Retailer walled gardens that protect first-party data but limit interoperability—turning each network into its own media silo.
- Disconnected technology stacks that solve isolated problems without integrating data or streamlining workflows across the broader commerce operation.
- Organizational silos where media, sales, merchandising, and operations teams operate with separate goals, tools, and definitions of success.
“You look at midsize and challenger brands — they’re creating that one strategy, one connected team around the consumer. They’re doing more with less spend — but they’re showing up way better in market.”
Wendy Salisko — Co-Founder, Wade
Why the Fragmented Media Landscape is Accelerating in 2026
Retailers have built media businesses on the foundation of their first-party shopper data, and that data is now a core revenue stream they’re actively expanding. As inventory grows from bottom-funnel search ads to full-funnel video, in-app placements, and in-store display, each retailer’s ecosystem becomes more sophisticated, and more distinct.
Unique audience segments, proprietary measurement frameworks, and different auction mechanics are features for advertisers building retailer-specific strategies. But for teams managing campaigns across multiple networks, those same differences create real operational friction:
- Inconsistent metrics that can’t be directly compared
- Duplicated workflows rebuilt from scratch for each retailer
- Incrementality that’s nearly impossible to prove across channels
- Limited cross-platform visibility into how campaigns perform together
Retailer-specific ecosystems reinforce this fragmented media landscape, but when teams also operate in silos internally, it compounds the problem.
Defining Data Silos Across Media, Commerce, and Operations
A data silo exists wherever information is created, stored, or analyzed in isolation, without a connection to the systems and decisions it should be informing. In retail commerce, this plays out across every function:
- Media teams optimize campaigns against platform KPIs without visibility into inventory levels, PDP readiness, or margin contribution.
- Sales and eCommerce teams track revenue and market share without context on which campaigns drove incremental demand.
- Merchandising and supply chain teams manage forecasts and inventory without sight of planned promotional activity or media investment.
When these functions operate independently, data must be manually stitched together or reconciled after the fact, introducing delays, errors, and decisions made with incomplete information.
How Fragmentation Holds Back Performance
“Fragmentation is an annoyance. It’s an inconvenience for an organization, but it’s also a drag on your business — and it is going to be a bigger and bigger drag as we see investment increase.”
Luke Balestri — Head of Business Solutions, North America, Pacvue
Fragmentation is more than an operational challenge, it restrains performance. Ad teams are optimizing campaigns without either the full business context or a cross-retailer view. As a result, planning and budgeting decisions miss the mark.
Strong ROAS Can Mask Weak Commercial Performance
Platform-reported ROAS is one of the most widely used metrics in retail media—and one of the most misleading when used in isolation. A campaign can consistently report strong ROAS while promoting low-margin products, pushing items with limited availability, or capturing sales that would have happened organically.
When media decisions are made without inventory, margin, or pricing signals in the loop, those decisions are often optimizing the wrong outcome: efficiency in a reporting dashboard rather than profitability and incremental growth in the business.
The Disconnect Between Media Metrics and Business Outcomes
The deeper issue is structural. Most advertising teams are measured on platform KPIs (ROAS, CPC, conversion rate while the commercial health of the business is tracked by an entirely different set of people using different data. These worlds rarely meet until after the damage is done.
“Everyone is looking at platform KPIs instead of shared business outcomes.”
Kavita Cariapa — Head of Commerce Media, EMEA, Dentsu
Fixing this requires more than better reporting tools. It requires aligning teams on shared definitions of success and connecting the data that enables those shared definitions to exist.
Where Data Silos Cause Real Problems
The issues fragmentation causes can be seen across execution, measurement, and planning:
- Execution is disjointed across retailers
Campaigns that span multiple retailer systems are difficult to launch, scale, and optimize because they lack a unified control layer.
- Planning is misaligned and budgeting is reactive
Forecasts are developed without sight of demand or inventory signals. Meanwhile, budgets are adjusted based on ROAS by channel rather than profitability, lift, and total impact, because internal data is fragmented too.
- Measurement is inconsistent
Without centralized reporting, platform performance is impossible to compare, attribution is mismatched, and it’s difficult to see how channels have performed together.
“We need to build measurement around what is actually capturing the consumer journey. And we’ve got to align spend to influence, not only conversion. If we think of our media spend purely as conversion, we’re missing such a large part of what those dollars are really meant to go out there and do.”
Luke Balestri — Head of Business Solutions, North America, Pacvue
The ‘Silo Tax’: Quantifying the Cost of Fragmentation
The Silo Tax is what you pay when every team is reporting success, but the business is underperforming. It’s the cumulative cost of disconnected systems, misaligned incentives, and operational drag—and it’s larger than most teams realize.
Unlike general inefficiency, the Silo Tax is quantifiable. It shows up in four specific areas:
- Sales at risk from execution gaps: stockouts, Buy Box loss, and content issues that erode conversion before media spend even has a chance to work.
- Inefficient media spend from misaligned signals: budget allocated to products that aren’t conversion-ready, running on platforms where the fundamentals aren’t in place.
- Labor drag from fragmented workflows: manual reporting cycles, delayed optimization decisions, and redundant processes across teams.
- Ongoing profit leakage across the business: chargebacks, pricing inconsistencies, and missed revenue recovery that compound over time.
“It’s not a data problem alone — it really, truly is a structural problem. The silo tax is created by the org structure, but the retailer ecosystem really reinforces that, and then you layer on the agency ecosystem, and really, everyone is overwhelmed because there’s no one seat that can really step up and solve the challenge.”
Wendy Salisko — Co-Founder, Wade
Pacvue’s Silo Tax Calculator is a tool that estimates the cost of fragmentation and silos in your specific business to approximate lost revenue, wasted spend, operational cost, and profit leakage into a concrete dollar figure. It’s a useful starting point for teams building a business case for connected operations.
From Fragmentation to Competitive Advantage
Solving the problem of fragmentation, or reducing the impact, can give brands a competitive advantage over others struggling with legacy processes and outdated operational models.
“It’s not about outspending your competition. It really goes back to being able to have that model and structure where you’re all connected as one and can fluidly look at new metrics.”
Wendy Salisko — Co-Founder, Wade
What a Connected Commerce and Media Strategy Looks Like
Connecting commerce with media starts with an awareness of where the gaps exist and the problems these gaps cause. A connected approach means:
Co-ordinating Media Strategy
- Playing to the strengths of each channel and developing full-funnel ad strategies
- Understanding how channels work together for business outcomes that go beyond ROAS (such as profitability, true lift, total impact)
- Managing multiple RMNs but comparing performance on equal terms
“We are seeing more brands probably over-invest in that demand capture part of the funnel versus demand creation — and that’s tremendously where we have to really start bringing more media back to life and measuring everything holistically.”
Kavita Cariapa — Head of Commerce Media, EMEA, Dentsu
Joining Internal Dataflows
- Eliminating inventory discrepancies and gaining clarity on availability
- Making commerce signals visible to marketing (price, content-readiness, Buy Box status, and profitability by SKU)
- Achieving a single operating view across key performance drivers
Faster Decisions and Optimization
- Using real-time signals to eliminate the lag between insight and action through AI-powered automation.
- Applying dayparting, rules-based optimizations, and automated budget management across campaigns—so teams spend less time on routine decisions and more time on strategy.
- Streamlining access to retailer first-party data tools without requiring teams to work inside each native platform.
“Speed, agility — that’s the reward you get for breaking down these silos.”
Kavita Cariapa — Head of Commerce Media, EMEA, Dentsu
In our recent Women in Commerce interview, Gabi Viljoen, VP & Head of eCommerce, Nestlé Health Science discusses some of the challenges with disconnected operational models.
Turning Fragmentation into a Competitive Advantage in 2026
Retail media will continue to expand, and complexity will increase with it. Brands that continue to operate with data silos will see more data, more tools, and more reporting, but less clarity, slower decisions, and weaker commercial outcomes.
An AI-powered Commerce Media OS changes that trajectory. By unifying media, commerce, and operational data, it removes the guesswork and puts decisions into a real business context. Teams share goals linked to profitability, incrementality, and total impact. When margins are under pressure and competition is intensifying, a connected operating model offers a clear advantage.
