David Tyler
Retail Media Networks (RMNs) are booming.Adsspend is surging, brands are reallocating budgets, and retailers are racing to monetize their first-party data.
But beneath the growth headlines lies a growing constraint: operations.
By 2026, RMNswon’tstruggle to attract demand,they’llstruggle to execute it accurately, consistently, and at scale.
Retail Media’s Operational Reality Check
According to eMarketer, retail media ad spend is expected to surpass $160 billion globally by 2026. Yet many RMNs are stilloperatingwith:
As volume increases, these inefficienciesdon’tstay invisible, they surface as performance gaps and trust issues.
Complexity Is Growing Faster Than Teams
Retail media operations sit at the intersection of:
Marketing Dive notes that RMNs are under pressure to deliver platform-level sophistication with retailer-sized teams,an impossible balance without external support.
Operational cracks appear fast:
Why This Matters to Advertisers
Brandsdon’tjust want reach,they want repeatable, reliable performance.
A 2024 Business Insider report showed that over 60% of brands cite “measurement inconsistency” as a top frustration with retail media.
Without strong ops, RMNs risk losing long-term trust,even if demandremainshigh.
Operations Are Now the Differentiator
As RMNs mature, the next wave of competitionwon’tbe about audience size,it will be about:
In short:operationalefficiency.
This is where specialized managed services become essential.
How Paragon Supports Retail Media Scale
Paragon augments in-house teams rather than replacing them,providing experienced resources that work within existing tools, platforms, and time zones.
The Cost Advantage of Getting Ops Right
Retailers often assume scaling ops internally is the safest route.It’sthe most expensive.
Paragon helps clients lower operating costs by up to72%, freeing budget for:
More importantly, it ensures RMNs can scale without sacrificing precision.Retail media’s growth storyisn’tslowing. But the winners in 2026won’tjust sell inventory,they’lldeliver error-free execution at scale.