Every retail marketing leader we talk to at CommerceNext says a version of the same thing: the budget grew, the team grew, the channel count grew, but the results didn’t keep pace. Somewhere between the strategy deck and the campaign going live, operational drag ate the upside.
That gap between investment and outcome is where the problem lives. If you’re running marketing across ecommerce, stores, and local channels, the seven bottlenecks below are probably familiar. Some you’ve named already. Others might be hiding inside processes you’ve accepted as normal.
Why does retail media fragmentation stall growth before it starts?
Retail media is now the fastest-growing channel in digital advertising, with U.S. spend expected to surpass $69 billion in 2026. But the structure of the channel itself creates a scaling ceiling. A Skai and Stratably survey of 166 retail media advertisers found that brands are currently active on an average of six retail media networks, with that number projected to reach 11 by year’s end.
Each network operates as its own walled garden with its own data formats, attribution windows, reporting dashboards, and campaign workflows. For a marketing team running campaigns on Amazon, Walmart Connect, Instacart, and three or four additional regional networks simultaneously, this means six or more separate interfaces, six sets of login credentials, six reporting cadences, and six optimization approaches that don’t map to each other.
The practical result: your team spends more time reconciling data across platforms than acting on it. According to the same Skai/Stratably study, only 15% of retail media advertisers report strong confidence in their cross-network measurement. That low confidence level doesn’t just slow optimization; it stalls the budget conversations that fund growth.
The fix starts with honest triage. You don’t need to be on every network. Assess which networks actually drive incremental revenue (not just last-click attribution), consolidate where possible, and standardize your internal reporting framework before adding the next network to the mix.
What happens when your content production outpaces your approval workflows?
Retail marketing has become a volume game. The Chili publish Brandwidth 2026 report, based on a survey of 256 grocery retail marketing leaders, puts concrete numbers on it: 57% of campaigns now generate between 50 and 200 asset variants per campaign, with 21% producing up to 500. Over half of teams run three to ten campaigns per month, and nearly half of those campaigns cover 500 or more store locations.
That is manufacturing-scale output running on workflows designed for a fraction of the volume. More than half of the marketing leaders surveyed said they still rely on parallel production tracks across internal teams and external vendors, with only 42% describing their production as mostly automated. The rest are working with manual approvals, version control spreadsheets, and review chains that add days to timelines.
The downstream cost is real. 60% of respondents in the Brandwidth report said production failures hit revenue directly through missed promotional windows. Most of those incidents cost between 10,000 and 50,000 euros, and the longer-term damage to retail partner relationships can cost far more.
If your production volume has tripled in the last two years but your approval process hasn’t changed, that’s the bottleneck. Automating templated asset production, centralizing brand governance, and compressing approval chains from five steps to two are the kinds of infrastructure investments that unlock capacity without adding headcount.
Why can’t marketing teams connect in-store and digital campaigns?
Nearly half of commerce media professionals view in-store channels as the biggest frontier for incremental growth, according to a joint IAB, IAB U.K., and SMG study of 281 commerce media marketers. But 40% of those same professionals say physical channels are the hardest to connect.
The disconnect is structural. Only 14% of respondents reported always planning multichannel campaigns from a single brief, and an equal share said they consistently receive unified reporting across channels. Creative was cited as the discipline most in need of improvement, followed closely by planning and measurement. Brands, agencies, and retail media networks don’t even agree on where the value lies: 38% of brands picked in-store digital as their top driver of incremental value, while only 13% of RMN operators agreed.
For you, this bottleneck shows up as two teams operating on parallel tracks. Your ecommerce team optimizes digital placements with one set of KPIs while your field or shopper marketing team runs in-store activations measured by a completely different set. When a customer sees a digital ad on Tuesday and picks up the product in-store on Saturday, neither team gets a clear picture of what drove the conversion.
Closing this gap doesn’t require a single unified platform (those don’t fully exist yet). It requires a shared brief, aligned KPIs, and a post-campaign review that forces both teams into the same room with the same data. Start there.
How does measurement inconsistency erode your ability to scale spend?
You can’t allocate budget to what you can’t compare. And right now, every retail media network defines success differently. Attribution windows, definitions of ‘conversion,’ and the availability of incrementality testing all vary from network to network, making apples-to-apples comparisons nearly impossible.
Forrester’s analysis of the retail media landscape highlights this directly: 38% of marketers cite difficulty connecting performance across networks, and 31% point to fragmented retail sales data as a key challenge. Retail media budgets are also largely reallocated rather than incremental, with 20% of advertisers funding retail media from trade budgets and another 20% drawing from shopper marketing.
The compounding effect: when you can’t prove incrementality with confidence, every budget review becomes a negotiation rather than a data-driven decision. Marketing leaders end up defending spend rather than redirecting it.
Practically, this means building your own measurement layer. Blended marketing efficiency ratio (total net revenue divided by total marketing spend) gives you a channel-agnostic view of performance. Pair it with controlled incrementality tests on your top two or three networks, and you’ll have a defensible framework for allocating spend that doesn’t depend on any single network’s self-reported numbers.
What makes local marketing so hard for multi-location brands?
The operational math of local marketing is punishing. A 500-store retailer running a regional promotion needs localized creative, localized pricing, localized inventory checks, and localized compliance review, all multiplied by every format (digital display, social, email, in-store signage) and every market (which may have different regulatory requirements, languages, or cultural considerations).
Most organizations solve this by either over-centralizing (one version of everything, applied everywhere, with diminishing local relevance) or under-centralizing (local teams make their own assets, and brand consistency evaporates). Neither approach scales.
The middle path is a templated production model where central teams create the strategic framework, approved brand elements, and core messaging, while local teams adapt within guardrails that are enforced by the production system rather than by an approval committee. The Brandwidth 2026 data backs this up: the highest-performing retail marketing organizations are the ones that have automated their templating and brand governance, reducing the time from brief to published asset while keeping error rates low.
This is where the gap between digital-first and store-first brands becomes most visible. If your local marketing still runs through email chains and shared drives, you’re competing against organizations that have turned it into a system.
Why does the talent gap multiply as you add channels?
Every new retail media network, every new social platform, every new in-store media format requires specialized knowledge. The targeting capabilities on Amazon’s advertising platform are fundamentally different from those on Walmart Connect, which are different again from what’s available through Kroger Precision Marketing. Expertise built on one platform doesn’t automatically transfer.
The Skai/Stratably survey found that 56% of retail media advertisers cite a lack of technical expertise as their primary obstacle to scaling, whether the topic was incrementality measurement, AI adoption, or cross-network optimization. That same resource gap compounds with every network added to the portfolio.
You’ve likely felt this on your own team. The person who runs your Amazon campaigns is fully loaded. So you hire for Walmart, then Instacart, then your retail partners launch their own networks and expect your participation. Each hire fills a gap but doesn’t build a bench, because the skills don’t overlap enough.
The counterintuitive answer is investing in process and automation that reduces platform-specific work (manual bid adjustments, pacing corrections, report formatting) so your team can focus on the strategic decisions that genuinely require human judgment and cross-network thinking.
How do disconnected data systems hold back personalization at scale?
Personalization is the promise of every ecommerce platform pitch. But the execution depends entirely on your data architecture, and most retail organizations have data sitting in silos that were never designed to talk to each other.
Your ecommerce platform knows what a customer browsed and bought online, your POS system captures in-store purchases, your CRM tracks email engagement, and your loyalty program holds tier status and preferences. On top of those, your retail media partners maintain their own closed-loop data on ad exposure and purchase.
In theory, combining these sources creates a complete picture of the customer journey. In practice, most retail marketing teams are working with partial views because the integration between these systems is either incomplete, delayed, or nonexistent. SAP Engagement Cloud research highlights how this plays out in real campaigns: a recommendation engine trained without order and return data can end up putting a returned product back in front of the customer who sent it back.
A single customer data platform that magically unifies everything doesn’t exist for most retail organizations. Prioritize the specific integrations that drive the most value for your highest-impact campaigns instead. Start with connecting your order data (including returns) to your marketing automation platform. That single integration prevents the most visible personalization failures and gives your campaigns a foundation of accuracy.
Retail marketing has never had more channels, more data, or more technology at its disposal. The constraint is the operational architecture that connects them all. The seven bottlenecks above aren’t exotic problems reserved for the largest retailers. They show up at every scale, in every format, in every market.
Fixing all seven at once isn’t realistic, and it’s not necessary. Pick the one that’s costing you the most right now, whether that’s production capacity, measurement confidence, or talent coverage, and build the system that solves it before moving to the next. The brands that grow fastest in digital retail aren’t the ones with the biggest budgets. They’re the ones that removed the drag between strategy and execution.
At CommerceNext, this is the conversation we hear again and again from the retailers, DTC brands, and technology leaders who make up our community. The Growth Show and our year-round events exist to put these operational challenges on the agenda alongside the strategic ones, because fixing the plumbing is how you unlock the growth.
