Commerce agencies face margin pressure from rising labor costs, channel expansion, and unclear AI expectations. Moving from episodic project work to AI-native Product Experience Management with Brandfuel enables agencies to reduce delivery friction, scale output without scaling headcount, demonstrate strategic AI leadership to clients, and transform project work into recurring revenue through ongoing product experience optimization.
Top-line revenue is growing. You are winning new business, launching new campaigns, and your team is busier than ever but margins are suffering. It’s a familiar pattern across digital commerce agencies. Growth is achievable, profitability is harder to sustain.
Labor costs continue to rise. Clients expect broader channel coverage, faster turnaround, and more personalization, often within fixed scopes. At the same time, AI has entered the conversation in a way that is difficult to ignore. Clients are asking how AI should reduce costs and improve performance, while competitors increasingly claim to be “AI-powered.”
At the same time, agency commerce teams are being asked to support more channels and more frequent updates. This work is often handled as periodic projects, reducing efficiency and reliable revenue. Continuing with outdated workflows and systems means the competition will continue to drive improvements and squeeze margins.
The path to sustainable margin is delivering new Commerce Service Offerings where you can set the market and bolster strategic leadership positions with clients while building reliable recurring revenue models.
The strain on agency margins is the result of several structural shifts happening at once:
Commerce agencies still rely heavily on labor-based delivery. Talent is expensive. At the same time, client teams push for predictable pricing and tighter scopes. When work expands beyond estimates, margins absorb the impact immediately.
A product launch is no longer limited to a storefront update. It now includes marketplace listings, paid social variations, email personalization, and channel-specific formatting requirements. Each surface introduces different rules and expectations. Clients expect comprehensive coverage. Budgets rarely expand at the same pace.
Agency leaders increasingly face questions about AI strategy. Why does product content still take so much time? How does AI improve outcomes, not just speed? What is the agency doing that clients cannot do themselves? In many cases, AI usage is fragmented. Point productivity tools are applied tactically mid-workflow rather than systemically, making it difficult to articulate a defensible strategy.
Product experience work includes some of the more labor-intensive and operationally complex areas of commerce delivery.
Product titles, descriptions, attributes, variants, metadata, and channel-specific adaptations require ongoing attention. As catalogs grow and channels multiply, the volume of updates increases. Seasonal changes, promotions, keyword shifts, and merchandising priorities all demand attention. Managing this work manually creates delivery friction. Spreadsheets, copy-paste workflows, and repeated approvals mean senior talent spends time on coordination rather than strategy. Updates take longer than expected, and small changes turn into larger efforts.
Product Experience Management, or PXM, offers a more sustainable approach.
PXM is the discipline of ensuring that product information, messaging, and context remain consistent, relevant, and optimized across every surface where customers discover and evaluate products.
Content creation and publishing are components of this work, but PXM operates at a higher level. It treats product experiences as a managed system rather than a collection of one-off deliverables. For agencies, this creates a few important outcomes.
Reduces the effort required to onboard and maintain product catalogs across channels
Treats product publishing as an ongoing, continuously optimized conversation with the market versus a one off activity
Creates a framework for more strategic, ongoing engagement with clients around product performance.
Many agencies have experimented with generative AI tools to accelerate content creation. These tools can be useful, but they are not designed to manage ongoing product experiences at scale. They lack awareness of brand voice, personas, and competitive context. They are not built to support large catalogs, governance workflows, or multi-channel publishing. Most importantly, they do not learn continuously as markets and performance signals change.
Addressing delivery friction requires more than faster writing. It requires an AI-native system purpose-built for Product Experience Management.
Brandfuel is an AI-native Product Experience Management platform designed for agencies managing multiple brands and catalogs.
Everything begins with the brand. From day one, Brandfuel is trained on a client’s brand personality, tone, personas, competitors, and market context. This foundation powers product-level content so that nothing is generic and everything aligns with the agency’s creative strategy.
From there, agencies can reduce the cost and time required to onboard and maintain product catalogs, generate channel-aware product experiences without duplicative manual effort, maintain consistent quality and brand voice across SKUs and surfaces, and continuously optimize product experiences as markets and discovery models evolve.
This approach allows agencies to scale output without scaling headcount. Writers and strategists move away from repetitive execution and toward editorial oversight, optimization, and client advisory work.
Operational efficiency improves, but more importantly, agencies gain leverage.
Clients are no longer impressed by isolated uses of AI. They want to understand how AI improves consistency, performance, and long-term outcomes.
Brandfuel enables agencies to demonstrate AI leadership in a practical way.
Rather than positioning AI as tools used specifically to productivity enhancements (e.g. faster, cheaper content) agencies can present an AI-native platform that manages product experiences strategically. AI is embedded into the system, learning continuously from brand inputs, competitive context, and performance data.
This allows agencies to connect marketing intent and ecommerce execution more effectively. Campaign context does not end when a shopper lands on a product page. Product experiences remain relevant throughout the journey.
This is not experimentation. It is infrastructure.
Most agencies handle product experience work episodically today. It appears during launches, seasonal refreshes, or SEO initiatives. With the right platform, this work can evolve into a more durable offering.
Agencies can introduce services such as ongoing product experience optimization, seasonal and campaign-driven catalog updates, rapid launch support for new product lines, and performance-informed testing and iteration. These services create recurring revenue and deepen client relationships. The agency becomes responsible not just for launching products, but for improving how products perform over time.
Discovery behavior is changing. AI systems increasingly rely on structured, contextual product information to surface and recommend products. Brands with fragmented or incomplete product experiences risk reduced visibility or inconsistent representation.
By maintaining rich, structured, and continuously updated product experiences, agencies help clients prepare without overcommitting to any single channel or prediction. This is a practical step toward resilience as commerce continues to evolve.
Margin pressure in commerce agencies is real. So is the opportunity.
Product Experience Management powered by Brandfuel can be a meaningful lever in growing an agency business profitably. When supported by an AI-native platform, it allows agencies to reduce delivery friction, lower content management costs, and engage clients more strategically.
To learn more about how Brandfuel can help agencies build differentiated, resilient AI-powered practices, contact us.
No. The goal of AI in this context is to remove the “drudgery” of commerce (managing variants, formatting, and data entry). This frees your creative team to focus on high-level brand strategy, campaign concepts, and creative direction. AI acts as a force multiplier for your humans, not a replacement.
Agencies are successfully shifting from “cost per word” or “hourly billing” to “value-based retainers.” You might charge a monthly fee for “Catalog Health & Optimization,” which includes continuous monitoring, seasonal refreshes, and channel-specific updates. Clients pay for the result (a high-converting, always-updated catalog), not the hours it took to write it.
This is a valid concern with generic tools. However, specialized PXM platforms allow you to train the AI on your client’s specific brand guidelines, tone of voice, and prohibited terms. The workflow should always include a “human-in-the-loop” review process. You pitch this to clients as “AI Scale with Human Control.”
Not at all. While the SKU counts of enterprise brands make the ROI obvious immediately, mid-market brands arguably need this more. They often have small teams and rely entirely on their agency to handle execution. AI allows you to offer enterprise-grade speed and volume to mid-sized clients who are desperate for growth.
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Kent Deverell is a digital commerce executive with 20+ years building and scaling innovative platforms and consumer brands. He co-founded Fluid, an industry leading ecommerce agency, launching the industry's first 3D product personalization engine for Reebok, Vans, The North Face, Polo, and Fender Guitars. Kent led DTC brands like Upper Playground through the full product lifecycle from development to fulfillment. He has advised major consumer and retail brands on streamlining operations, improving content performance, and driving conversion through better product storytelling.
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