Voices of Search Podcast

Episode: Using SEO Principles to Optimize Product Feed Visibility

Host: Jordan Cooney
Guest: Katie Morrow, Director of Managed Services, ProductsUp
Date: April 6, 2026

Brief Overview

In this insightful episode, host Jordan Cooney sits down with Katie Morrow of ProductsUp to deep-dive into how SEO principles are evolving to optimize product feed visibility in an era increasingly shaped by AI-driven agentic commerce. The discussion extrapolates the impact of structured product data, the changing role of consumer Personas, measurement complexities, and tactical prioritization for ecommerce brands. Together, they examine how companies must adapt their product data strategies for AI discovery and ever-evolving consumer behaviors, all while maintaining relevance and effectiveness in a rapidly mutating digital marketplace.

Key Discussion Points & Insights

1. Introduction to ProductsUp & Katie’s Background

• [01:30-03:51]
  • ProductsUp supports 2.2 trillion product transactions monthly, optimizing and normalizing product data for the largest global retailers across multiple channels—search, social, affiliate, etc.
  • Katie’s 15-year journey: from early agency days focusing on bid and feed management, through Google Merchant Center specialization, to embracing low/no-code solutions with ProductsUp.
  • Notable quote:
    • “Self-proclaimed data diva.” (Katie, 03:51)

2. The Rise of AI Agents and Household Personas

• [03:52-07:45]
  • AI agents are redefining discovery, facilitating smarter and more contextual product recommendations—even for consumers who don’t know the right questions to ask.
  • The concept of “sphere of influence” is expanding: marketers now must account not just for individuals, but households where multiple members and their devices influence purchasing.
  • Example: Katie notes ads for e-bikes: “I’m not in the market…but my household for sure is…watching content about it.” (Katie, 07:21)

3. Measurement Complexity in an AI World

• [07:45-10:33]
  • Measurement is under strain as AI platforms emerge.
  • “Structured data” and a “solid product catalog” are foundational.
  • Actionable advice:
    • Start small—pilot with top products or categories before unleashing the full catalog to AI agents for easier impact tracking.
    • “If you go and expose 50,000 SKUs...you’re not going to be able to track that.” (Katie, 09:40)

4. Prioritization: Sitemaps, Product Catalogs, and KPIs

• [10:33-15:36]
  • LLMs won’t crawl every product like Google used to; prioritization matters more than ever.
  • Prioritize by top-performing categories or SKUs, using internal KPIs:
    • Revenue, new customer acquisition, or traffic as segmentation levers.
  • Avoid catalog “bloat”—don’t send every small item (e.g., “fuzzy socks”) unless it supports strategy.
  • Notable quote:
    • “We should already understand our data set…what’s driving revenue, high margin drivers?” (Katie, 12:24)

5. Refinement Data and Strategic Product Exposure

• [15:36-18:16]
  • Marketers must align data structure (attributes like color, size) with prioritization logic.
  • For platforms like social, sending every variant is often unnecessary; focus on what inspires discovery or conversion on that platform.
  • “For some channels like Social, [sending every variant] is absolutely unnecessary. It is a visual discovery stage.” (Katie, 16:40)

6. The New Rules of Product Data for AI Discovery

• [18:16-23:00]
  • Product data must be dynamic—seasonality, trends, and media influence are more critical in the agentic era.
  • Marketers need agile tools to quickly surface “what’s new,” what’s trending, or what supports rapid cultural shifts.
  • Notable anecdote: The sudden surge in demand for a toy (Neato), and how being tied to real-world inventory cycles is now a marketing challenge.
  • “You’re going to miss a lot of opportunity this year and ongoing because this is just the beginning.” (Katie, 22:58)

7. Discovery Shopping and Brand Challenges in the Age of Agents

• [24:34-29:34]
  • Discovery-based (social, emotional) shopping is supplanting transactional, keyword-focused browsing.
  • Data completeness—ensuring every relevant attribute, keyword, and Persona information is present—is vital.
  • Potential concern: Agents may limit exposure to new brands or types if a consumer’s profile becomes too rigid.
  • “My lack of autonomy on my decision making as well as my surprise and amazement on how quickly I can be influenced by something I don’t know anything about.” (Katie, 39:23)

8. Brand Differentiation Amid Homogenized Product Listings

• [29:34-32:00]
  • How do retailers differentiate if all sell the same product data?
    • Pricing, local availability, same-day/curbside delivery, and experiential associations may become key.
    • “Rich content at the SKU level…will it be a price war?...Is it available curbside?...Can it be door dashed?” (Katie, 31:01)
  • Completeness/readiness across all customer needs is now expected.

9. ProductsUp’s Platform & Approach to Agentic Commerce

• [32:00-35:22]
  • ProductsUp is pioneering agentic commerce with first-to-market solutions, embedded AI data services (to convert a single SKU into multiple Persona-ready formats), and templated approaches for LLM readiness.
  • Strategic catalog segmentation: don’t send everything—identify and isolate high-impact products for agentic submission.
  • “Please don’t send all 300 million products…you’re never going to know the impact.” (Katie, 34:25)

10. Speed vs. Completeness: Strategy for Readiness

• [35:22-37:21]
  • Top-down pressure for AI initiatives is intense, but speed shouldn’t trump quality or system readiness.
  • Take a breath, pause to strategize, then launch chosen segments to avoid negative long-term impacts from poor-quality feeds.
  • “The worst thing we can do is expose bad product content to the agents.” (Katie, 36:56)

Lightning Round Highlights

[37:54-41:16]
Quick takes from Katie Morrow:

• Biggest AI commerce mistake?
  “They don’t know how people are gonna actually buy their products and they can’t see that that’s where it came from.” (38:03)

• Making good decisions amid tracking ambiguity:
  “Expose just a small subset of your product catalog and watch it every day.” (38:18)

• Single most important catalog segmentation for AI:
  “What’s my KPI?...Segment my catalog as granular as possible and grow.” (38:37)

• Biggest surprise as AI changes discovery:
  “My lack of autonomy on my decision making...how quickly I can be influenced by something I don’t know anything about.” (39:23)

• Concern about limited choice in AI shopping?
  “Absolutely…It’s like the very early days of Google frugal shopping where I have five things to look at. And so I do find myself abandoning my agent’s recommendation out of a lackluster experience.” (40:08)

• One metric to stop using?
  “Nothing. Give me more information. More granular…I want it at the SKU level, if not the variant level.” (40:57)

• Fastest AI revenue test?
  “Just send one SKU and see how long it takes.” (41:11)

Notable Quotes

• “Now we have to influence something that is very intangible. And so it’s bringing us all as marketers back to kind of brainstorm… ideate on what does that look and feel for the consumer to discover a product to allow these agents to I guess algorithmically see us.” — Katie, [04:29]
• “Look at your catalog holistically… what are your KPIs at their base? If it’s high traffic, then you only expose high traffic SKUs, high traffic categories.” — Katie, [13:31]
• “It’s not a set it and forget it...being on top of those ever shifting changes is our responsibility and how we expand expose it.” — Katie, [19:39]
• “The worst thing we can do is expose bad product content to the agents. Because at that point, you’re building a bad historic presence with those that are making future buying decisions on our behalf.” — Katie, [36:56]

Episode Timestamps

• [01:30] ProductsUp & Katie Morrow’s background
• [04:29] AI agents and product discovery
• [06:19] Personas & household shopping influence
• [08:31] Readiness KPIs & measurement
• [10:33] Prioritizing catalogs for agentic discoverability
• [15:36] Refinement data & prioritization advice
• [19:39] The new cadence—seasonality & speed
• [24:34] Discovery (social/emotional) vs transactional shopping
• [29:34] Brand uniqueness when selling identical products
• [32:41] How ProductsUp supports agentic readiness
• [35:22] Speed vs completeness in AI feed deployment
• [37:54] Lightning round (concise strategy tips & predictions)

Takeaways for Listeners

• Structured product data and catalog segmentation are now deeply strategic, not just operational.
• Piloting focused product sets, measuring impacts, and iterating fast beats “boiling the ocean.”
• Brand differentiation in an agent-driven world may be as much about data completeness, fulfillment options, and real-time relevance as about the product itself.
• As AI systems mediate ever more of the shopping journey, marketers must become more targeted, agile, and experimental than ever.

For more insights or to connect with Katie Morrow, visit ProductsUp or check the episode show notes for links.