Working with retailers and distributors in a way that drives mutual execution success is essential for surviving the shift into agentic commerce.
When you strip away the tech jargon, you and a retailer want the exact same thing: to sell more products to the consumers you serve. As AI increasingly influences what’s discovered, recommended, and purchased, brands need to get brilliant at the basics again.
Consistent, complete, and accurate product information has moved beyond traditional operational hygiene. In 2026, it's the essential foundation needed to execute your growth strategy.
Partner, Test, and Think Like a Modern Retailer
To win the buy-in of major distributors, brands must shift their perspective from vendor to co-innovator. Winning in the agentic era requires a collaborative approach to data strategy and a deep commitment to solving shared supply chain challenges.
Shared Vulnerability in Testing
Retailers are running rapid test-and-learn programs to understand how AI shopping agents interact with their platforms. No one has the playbook yet.
The winners won't show up with all the answers; they'll show up as design partners. You optimize the data. They test AI outcomes. Together, you discover what earns the recommendation.
Empathizing With the Retailer’s Real Bottlenecks
Retailers are hyper-focused on speed-to-market, reducing costly returns, and ensuring their sites become the preferred purchase destination for AI shopping agents and LLM-driven recommendations.
If your product data is incomplete or outdated, you’re creating operational drag for them. Thinking like a retailer means recognizing that your data quality directly impacts their supply chain efficiency, their ability to sell your products, and their bottom line.
Fierce Data Governance
Data governance is a competitive advantage. This is where strategy becomes execution and where winners separate themselves.
For example, if an LLM or autonomous shopping agent is making purchase decisions, the quality of its recommendations is only as good as the quality of the data it consumes.
Today’s organizations need to ask hard questions like:
- Who owns our master data?
- Where’s the trusted source of truth?
- Is it governed, standardized, and updated in real time?
- Are we enriching it with the attributes, relationships, and context that enable AI to understand our products, especially who they're for, when they should be recommended, and why?
Rearchitecting Product Content for the Agentic Era
In the era of AI commerce, data governance means making your products discoverable, understandable, and recommendable.
Everyone in your organization must execute on the mission, understanding that the agentic era is about more than adopting new tech. It’s about product content that’s readable, verifiable, and authoritative for AI. If your data is the foundation, your strategy determines the structure.
Below, let’s dive into each of these core areas of focus that are top of mind for retailers as they navigate this new landscape and for your organization to keep in mind as you build and refine your commerce strategy.
Pillar 1. Top-Line Growth: Selling to the AI Consumer
Don't abandon your search engine optimization (SEO) strategy — it remains the essential foundation for discoverability. However, in the agentic era, you must now build answer engine optimization (AEO) on top of it.
AEO is about deeply understanding your consumers' intent and personalizing your product information so that when they ask a large language model (LLM) a question, the machine doesn't just find your product; it identifies it as the exact solution they need, steering them to your brand over competitors.
There’s a massive emphasis right now on conversion optimization driven by deeper personalization, loyalty, and expanded paid media opportunities. But the biggest shift is the growing importance of LLM discoverability.
AI shopper agents — not only humans — are now evaluating, recommending, and selecting products on a brand’s behalf.
Connect Content to Your Consumers
Ensure there’s enough enriched data for all possible personas searching for your brand to have adequate information for making a purchase decision.
Get AEO-Ready
Build upon traditional SEO, keeping this as the foundation, and also include content aligned with AEO. This ensures your machine-readable data is optimized for conversational search and autonomous agents, providing direct answers to specific shopper intents.
The New Personal Shopper
The LLM is your consumers' new shopping concierge. But as Salsify’s 2026 Consumer Research Report shows, shoppers can be skeptical of AI results, often verifying them elsewhere.
To win here, you must be the source of truth. Selling to this new personal shopper requires more than “discoverable” content and requires authoritative, high-integrity data that builds trust from the first interaction.
Brands and retailers have never been more aligned. Both want to drive sales, build loyalty, and earn the next recommendation — whether from a consumer or an AI shopping agent. That starts with treating data quality as a shared investment, not a siloed responsibility.
Pillar 2. Profitability: Speed-to-Market and Operational Efficiency
In today's commerce environment, profitability requires two things: selling more and selling smarter. Retailers are focused on accelerating speed-to-market, creating frictionless supplier experiences, and reducing the operational costs that erode margin. High-quality product data enables all three.
Accelerate Product Content Execution
As retailers push to automate content curation and syndication, brands must optimize their own execution strategies to keep pace. Removing internal data bottlenecks is no longer optional; removing this friction is the key to accelerating launches, reducing operational costs, and deepening retailer relationships.
Turn Time Into Revenue
Every day a product isn't live is a lost selling opportunity. Automating the syndication and activation of complete, accurate product data shortens time-to-market, helping retailers capture demand while it's at its peak.
Reduce Costly Returns
Profitability doesn't end at checkout. Rich, accurate product data helps consumers — and increasingly AI shopping agents — select the right product the first time, reducing mismatched purchases, minimizing returns, and improving customer satisfaction.
Ultimately, modern commerce leaves no room for operational friction. Winning the shelf means ensuring every piece of data works to shorten the distance between a product launch and a profitable sale.
Pillar 3. Modernization: Building the Foundation for AI Commerce
Growth and profitability do not happen in a vacuum—they require absolute trust in your data, your systems, and your ability to execute consistently. True modernization is not a simple legacy technology swap, nor is it about adopting AI for AI's sake. It’s a strategic mandate to build a trusted, structured, and continuously governed data foundation.
When product information is complete and activation-ready, it eliminates friction across the entire ecosystem, transforming how you show up for retailers, consumers, and AI shopping agents alike.
To win on the modern digital shelf, brands and retailers must shift their mindset around technology:
The AI-Ready Data Foundation
True modernization isn't about chasing AI hype. It’s about structuring and governing your product data today so that automated shopping engines build consumer confidence rather than friction.
Modernization Is a Trust Upgrade
Upgrading your systems isn’t just about replacing legacy tech; it’s about building a trusted data foundation that empowers retailers, consumers, and AI agents to make confident decisions.
Frictionless Retailer Execution
Modernizing your content makes you the easiest brand to do business with. Retailers aggressively favor partners whose data is complete and activation-ready, naturally channeling growth to the most modern brands.
Ultimately, modernization is more than a technical milestone — it’s a commercial imperative. The brands that build a foundation of trust today will be the ones that own the digital shelf tomorrow.
The Bottom Line
The future of commerce won't be won by the organizations with the most AI — it will be won by the organizations with the best data. Growth, profitability, and trusted retailer partnerships all begin with a single foundation: product data that is complete, connected, and built for both people and machines.
Every AI recommendation begins with product data. The question is whether yours earns the recommendation — or loses it.
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