Podcast Summary
The Best SEO Podcast: Defining the Future of Search with LLM Visibility™
Episode Title: Building an AI Layer For B2B Commerce And Search
Host: Matthew Bertram (MattBertram.com, EWR Digital)
Guest: Rob Neumann (Netformic)
Date: November 10, 2025
Episode Overview
In this episode, host Matthew Bertram is joined by longtime mentor and AI/data expert Rob Neumann to dive deep into how artificial intelligence—particularly large language models (LLMs)—is revolutionizing B2B commerce, product search, and the way companies approach SEO and digital operations. They discuss the pivotal role of Product Information Management (PIM), Digital Asset Management (DAM), and the necessity of building unified, AI-ready data architectures for true omnichannel and LLM Visibility™. The episode provides actionable strategies for marketing, sales, and executive teams looking to future proof their businesses and seize early-mover advantages in the coming AI-driven search landscape.
Key Discussion Points & Insights
1. The Evolution: SEO Meets LLM Visibility™
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Matt discusses the decision to unify the podcast identity around the Best SEO Podcast as the focus moves from traditional SEO to AI-driven discoverability.
“We're going to just stick with the Best SEO Podcast...as the discussion continues to go further towards LLMs and visibility in those LLMs online.” [00:56] -
Emphasizes that if you aren’t visible to large language models, you will struggle to be found in future search paradigms.
"If you’re not visible to the models, you won’t be visible to the market.”
2. AI and B2B E-Commerce: A Fundamental Shift
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Buying habits are fundamentally different post-pandemic; 75% of the B2B customer journey now happens online.
"Everybody needs to start thinking like an E commerce company.” [04:15] -
Companies must deliver frictionless buying experiences and consider every business as an e-commerce business, regardless of industry.
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SEO’s evolving role: SEO drives traffic; CRO and AI-powered product discovery must then convert that traffic.
3. AI for Better Product Discovery and Personalization
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Why Findability Equals Sales:
Rob emphasizes, “If you’re not finding, you’re not selling.” [04:45]
In B2B, if a buyer can’t quickly find what they need, “in their mind, you don’t have it,” and they’ll move to a competitor. [04:30] -
Smart Product Recommendations:
- Presenting a few relevant options (not just one perfect answer) encourages purchases and increases satisfaction and cart value.
"There’s a higher satisfaction score to give them one perfect and then three options.” [07:27]
- Presenting a few relevant options (not just one perfect answer) encourages purchases and increases satisfaction and cart value.
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Enriching Product Data for Multiple Personas:
- Use AI and industry-specific LLMs to generate product descriptions tailored for different audiences (engineers, buyers, general public, etc.) and improve search engine and on-site search performance.
“I can take that same thing and tell it to describe this to a 5-year-old, describe this to a buying agent, describe this to an engineer, and describe this to the general public...” [11:16]
- Use AI and industry-specific LLMs to generate product descriptions tailored for different audiences (engineers, buyers, general public, etc.) and improve search engine and on-site search performance.
4. Building the AI Layer: PIM, DAM, and LLMs
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ERP ≠ Enough:
- Most ERPs provide basic data. True competitiveness comes from using a PIM/DAM layer enhanced by LLMs to:
- Clean, relate, and label messy data from multiple sources/vendors.
- Serve enriched, searchable, and persona-targeted content.
- “We’ve created an LLM specifically around their chemistry...and we can search it and serve up information without revealing the secrets.” [14:05]
- Most ERPs provide basic data. True competitiveness comes from using a PIM/DAM layer enhanced by LLMs to:
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Protecting Sensitive Data:
- Private LLMs are increasingly necessary for companies with proprietary information (e.g., pharma).
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Operationalizing with AI:
- AI reveals trends (demand forecasting, reorder timing, stock projections) in the backend—crucial for supply chain decision-making.
- “You can see the trends of what people are buying, how often...you can suggest these things to them to help them stay on top...” [17:56]
5. Practical AI Applications for B2B Operations
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Solving Multi-Channel Inventory:
- AI enables real-time optimization of inventory across Amazon, Shopify, distributors, multiple warehouses—replacing static “safety stock” methods that tie up capital.
- “Using AI...it can actually manage all the channels at one time.” [19:01]
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Streamlining Product Mapping Across Vendors:
- AI can unify product data and SKUs from diverse suppliers, enabling efficient re-labeling, white-labeling, and just-in-time delivery.
- “Where the PIM and the DAM come in is...the AI layer...can figure it out and tell you what’s at where, what store, what it is.” [20:05]
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Real-World Example:
- For a plumbing distributor, AI surfaced exact matches and higher-margin white-label options automatically in search—driving both customer satisfaction and profits. [22:50]
6. The Next Layer: AI-Driven Search Onsite
- Architecture:
- Enhanced PIM/DAM provides deeply structured product data.
- This feeds into AI-driven search layers, which can interpret nuanced queries and map to precise and related products.
- "We take all of that data, do some structure inside of the PIM...the AI-driven search is able to just go to town.” [24:43]
7. Monetizing Hidden Data & Expanding the Long Tail
- Surfacing ALL catalog data (not just popular products) is now feasible and profitable:
- Long tail sales increase as rare, specialized products become discoverable.
- Exposure of technical data (e.g., CAD drawings, detailed PDFs) led directly to higher site traffic (+12%) and sales (+3%) in a tubing industry case.
- “E-commerce and search does not care. Put all million up and the one time that somebody buys it, you are way ahead.” [28:44]
8. Conversion Rate Optimization in the AI Era
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Capture User Information Early:
- Don’t just provide a phone number—use “save for later,” loyalty programs, quizzes, calculators, and gated content to collect real emails and details.
- “No problem, give me your email address and I’ll save them [favorite parts] for you.” [33:36]
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Combat Cart Abandonment:
- Go beyond email reminders—try direct-mail postcards, SMS automation, and even physical incentives, which often break through digital noise.
- “They send automatic postcards...here’s a postcard, and by the way, I’ll give you 10% off.” [36:07]
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Leverage Data-Driven UX:
- Use heatmapping, analyze bounce and cart abandonment rates, and personalize funnel content for mid- and bottom-funnel users.
- “The only way you’re going to be able to do that is with data. And that’s the big differentiator today.” [31:57]
9. LLM Visibility™: The Urgency of the 18-Month Land Grab
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Why Early Action Matters:
- LLMs are rapidly solidifying their “knowledge base.” Early and frequent citation builds authority in the datasets—delaying means it will be “extremely hard to dislodge you as that authority...” [46:07]
- “Every recall does that...these LLMs are going to solidify and in 18 months it is going to be extremely hard to do that.” [46:07]
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Marketing as an Entity:
- Define your company and its key players as data entities.
- Organize and enrich data so LLMs understand and amplify your brand’s authority.
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Becoming an “AI First” Company:
- This is a C-level imperative. Winning companies will approach digital, sales, and marketing from an “AI-first” position, with full executive buy-in.
- “This is a CEO issue. This is strategy, this is vision. This is the future of the company for the next five to ten years.” [53:35]
10. The Human Side: Overcoming Resistance, Building Champions
- Real change requires both top-down and bottom-up adoption; cross-functional alignment from execs is critical for success.
- Staff must be educated to see AI as leverage (“how can we do more”) rather than a threat.
- “If you’re thinking AI is going to replace you, it is...someone leveraging AI will absolutely replace you if you’re not understanding it.” [52:50]
Notable Quotes & Moments
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On the shift from classic search to AI answers:
“Now people just want that answer, Give me that answer and you go do the research, synthesize the data and give it to me...they don’t go backwards.” — Matthew Bertram [47:28] -
On exposing the “long tail”:
“E-commerce and search does not care. Put all million up and the one time that somebody buys it, you are way ahead.” — Rob Neumann [29:55] -
On executive buy-in and urgency:
“If I want to be there in the future, I have to do this.” — (CEO quoted by Rob Neumann) [53:35] -
On the 18-month LLM land grab:
“The people that are planting that flag in the ground now and building those libraries and those data sets and becoming the go-to recall expert for these things are going to win.” — Matthew Bertram [46:23] -
On transformation being “fractured”:
“The companies that leverage this, that can move forward towards this AI First Company are going to crush other companies...” — Matthew Bertram [55:42]
Timestamps of Major Segments
- 00:56 – Why unify podcast/brand identity for LLM Visibility™
- 04:15 – COVID-era switch: Every business must think like an e-commerce company
- 07:27 – Power of product recommendations; Amazon as CRO example
- 11:16 – Persona-driven enrichment of product content with AI
- 13:55 – Definition of PIM/DAM and why ERP isn’t enough
- 17:56 – AI for trend analysis, supply chain, inventory management
- 22:50 – Real-world B2B AI wins; white-label profit maximization
- 24:43 – Two-step enrichment for AI-driven onsite product search
- 28:44 – Long tail marketing and exposing full catalog for incremental sales
- 33:36 – Conversion rate optimization tactics for B2B (loyalty, gated content, early data capture)
- 36:07 – Physical mail and multichannel tactics to close abandoned carts
- 46:07 – LLM authority, the 18-month land grab, and why NOW matters
- 53:35 – C-level buy-in and “AI first” as organizational vision
- 55:42 – Real-world “AI First” company case study; why fractured adoption leaves competitors vulnerable
Actionable Takeaways
- Audit and enrich all product and company data for LLM and omnichannel discoverability.
- Implement PIM/DAM and AI-driven layers for unified, searchable, and persona-relevant content.
- Adopt CRO tactics across the buyer journey and leverage both digital and physical re-engagement tools.
- Get executive alignment across IT, Marketing, and Operations—an AI-first strategy must be driven from the top.
- Move NOW—early adoption in LLM visibility sets long-term competitive moats that will be hard to breach.
- Expose long-tail/hidden products, technical documents, and varied formats (PDF, CAD, video, etc.) to increase both traffic and authority.
How to Connect with the Guests
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Rob Neumann:
- LinkedIn: linkedin.com/in/robneumann
- Company: netformic.com
- Email: rob.neumann@netformic.com
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Matthew Bertram:
- LinkedIn: linkedin.com/in/mattbertram
- Podcast/Web: MatthewBertram.com | EWR Digital
Further Listening & Resources
- Past episodes on Amazon Marketing, PIM/DAM, and AI-first company interviews.
- Upcoming webinars on LLM Visibility™ and operationalizing AI layers in B2B.
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