Agentic commerce marketing tips: How to optimize your feed for AI agents

The landscape of online shopping is undergoing a massive shift as consumers move away from traditional search engine result pages (SERPs) and toward autonomous AI assistants.

Navigating this new frontier requires a fundamental transformation in how eCommerce brands and digital marketing agencies manage, structure, and distribute their product data. To help you navigate this transition, we’ve gathered essential agentic commerce marketing tips from our Agency Partner Day guest speaker, Navah Hopkins, to ensure your brand remains visible, credible, and profitable in an AI-driven marketplace.

Key takeaways

• The agentic shift: eCommerce is rapidly moving away from traditional search engine result pages toward autonomous AI assistants that curate shopping feeds, deliver 25% higher personalization relevance, and execute checkouts natively within the chat interface.

• Feed hygiene: Maintaining a structurally clean, automated product catalog via platforms like Channable is mandatory, as poor feed data architecture causes AI agents to completely exclude your brand from recommendations, even when a customer
  explicitly requests your product.

• AI optimization (AEO & GEO): To be seen on AI recommendations, marketers must focus on technical search visibility using standard adapters like Model Context Protocol APIs (AEO), gather robust off-page review trust signals to build authority (GEO), and retain distinct human creativity.

• New eCommerce metrics: Digital agencies must update client reporting by replacing current KPIs with modern AI metrics, specifically tracking agent visitation (bot scraping), citations (explicit source links in responses), and share of model responses (overall share of voice).

• AI marketing tactics: Smart brands can utilize new strategies like impression-based remarketing, which allows you to build compliant custom audiences from users who contextually saw your product in an AI chat and sequentially target them with search or Performance Max campaigns.

Understanding the shift: Marketing in the agentic web shift

To build a winning agentic commerce strategy, you must first understand what makes agentic AI unique. While traditional generative AI focuses on retrieving data and generating text responses, agentic AI acts as an autonomous unit working in partnership with or on behalf of a human user.

In this agentic marketing web era, consumers are transitioning from one-click checkouts to direct, in-cart checkouts occurring entirely within an AI agent's interface. For example, systems like Microsoft Copilot can now curate personalized shopping feeds, remember past consumer conversations, and execute purchases natively.

Data from Microsoft indicates that ad placements within Copilot yield up to 25% more relevance than standard search ads because the personalization engine is highly precise. If your products aren't optimized for these models, you are missing out on high-intent, high-converting buyers.

Why feed hygiene is crucial for AI agent-driven commerce

When preparing for AI agent-driven commerce, your product feed acts as your brand's voice. If an AI agent cannot seamlessly parse (skim through) your catalog, your products simply cease to exist within that model's ecosystem.

Consider this real-world scenario: An incredibly loyal customer inputs a highly specific prompt into an AI assistant, explicitly asking to buy a custom sweater from a designated merchant. However, because that merchant's product catalog is built with poor technical architecture and isn't cleanly crawlable, the AI agent is forced to apologize to the user and recommend two alternative products from direct competitors. The brand loses a guaranteed sale from a loyal customer purely due to poor feed infrastructure.

For multichannel brands and Amazon sellers, utilizing a marketplace automation platform like Channable is the fastest way to minimize time-to-value. Automated feed management ensures that your attributes, stock levels, and product descriptions are instantly structured in an AI-friendly format across thousands of global channels and can even be used to scale with our AI suite.

eCommerce Optimization for AI agents: The three pillars of success

To learn how to thrive in agentic commerce, brands and digital marketing agencies must anchor their strategies around three core principles: being found, being credible, and being human.

Pillar	Focus area	Practical action item
Be found	Technical ingestability & content	Optimize merchant feeds, use clean API connections (like MCP), and maintain high-quality brand content.
Be credible	Trust signals & verification	Accumulate user reviews, secure your domain, and ensure fulfillment paths sync reliably with your CRM.
Be human	Creativity & branded experience	Inject unique brand perspective and original insight that AI cannot easily replicate or synthesize.

1. Be found (AI engine optimization - AEO)

Being found goes beyond basic indexing. Your content must be technically digestible. AI engines utilize Model Context Protocol (MCP) APIs to act as universal adapters between different LLMs and database systems. By structuring your catalog through data management platforms, you build a single source of truth that easily scales across any AI framework.

2. Be credible (Generative Engine Optimization - GEO)

AI models recommend brands they trust. GEO focuses heavily on off-page authority signals. The AI scans web indexes, authoritative platforms, and third-party review sites to verify your legitimacy. If your business lacks verified reviews or transparent business practices, the AI agent will filter your products out to protect the consumer from potential scams.

3. Be human

While leveraging automation is critical for scale, your brand identity must remain distinct. AI tools excel at amplification, but they cannot replace original human creativity, specialized business acumen, or deep emotional connections with an audience.

Shifting your measurement: Tracking the new AI metrics

As AI search engines change the conversion funnel, legacy key performance indicators (KPIs) like standard web traffic are getting competition. When managing client accounts, digital marketing agencies need to introduce a new reporting framework optimized for agentic ecosystems.

• Agent visitation (The new website traffic): This measures how often autonomous AI bots and scrapers access your digital properties to gather information for user queries.

• Citations (The new click-through rate): Instead of standard organic listings, look at how frequently your brand link is explicitly cited as a trusted source inside an LLM's response block.

• Share of model responses (The new share of voice): This tracks the percentage of time your brand or products are recommended when a user submits a category-relevant prompt to a tool like Copilot or Gemini.

To capitalize on these interactions, smart marketers are turning to privacy-compliant strategies like impression-based remarketing. Platforms like Microsoft Advertising allow you to capture audiences who viewed your product inside an AI chat experience and sequentially target them with highly specific search or Performance Max (PMAX) campaigns.

Take control of your agentic commerce strategy

The transition to an agentic marketplace doesn't mean throwing away your foundational SEO guidelines. Instead, it requires evolving those principles into structured data, flawless feed hygiene, and unshakeable trust signals.

By automating your data management and keeping your product information perfectly optimized for AI web crawlers, you protect your market share and drastically reduce your time-to-value across global channels.

Ready to bulletproof your product feeds for the next generation of AI-driven commerce? Explore how Channable's automation solutions can optimize your multichannel strategy today and watch the entire keynote presentation on this topic.