# Karl Simpson

Karl Simpson works in ecommerce, with a focus on Amazon, product data, merchandising, and the processes that help businesses manage product catalogues and prepare for AI-driven shopping.

- Profile: https://b2binfluencer.marketing/creators/karl-simpson/
- LinkedIn: https://www.linkedin.com/in/karlsimpson
- LinkedIn followers: 3,638
- Topics: artificial-intelligence, ecommerce, ecommerce-operations, ai-in-ecommerce, amazon-marketplace
- Based on 10 dated posts, latest 2026-10-07

## Summary

Karl Simpson is most useful for explaining how product data and process affect Amazon and AI shopping.

- Best for: A B2B ecommerce SaaS brand running content on catalogue governance and AI readiness.
- Not for: A consumer home goods brand seeking paid social video with large consumer reach.
- Check first: Confirm recent results for comparable topics and formats before booking.

### Takeaways

- Process, not better tools, often solves delayed launches and inconsistent supplier data.
- Product information needs context, use cases and comparisons for AI shopping searches.
- Brand knowledge of Amazon shapes the help it needs from agencies.

## Main ideas

- **Process comes before tools**: Simpson argues that ecommerce teams over-attribute performance to software because they are already financially and emotionally invested in what they have bought. In their experience, growth and performance usually follow better process. They make process the first pillar of what they call the PREPARED ecommerce operating system, and preview a linked article with four claims: process should enable rather than restrict people; supplier data is a process problem before it is a data problem; better process is the foundation for AI, automation and scalable growth; and every ecommerce business should understand seven operational processes. Their definition is deliberately un-bureaucratic: "Good process isn't bureaucracy. It's simply a better way of getting important work done, consistently."
- **Product data decides where a product can show up, including in AI shopping**: Simpson sees AI shopping tools shifting the basis of competition for product records. Keywords and metadata still matter for search, but context, use cases, comparisons and problem solving matter more as AI-assisted buying spreads, because AI sessions start with a problem rather than a chosen product. The practical consequence is catalogue work: accurate specifications, data enrichment and product governance determine how widely a product can surface.
- **How much a brand knows about Amazon shapes the help it needs**: From inside Amazon marketplace work, Simpson observes that the hardest part of agency-side work is the range of client situations, not any single technical problem. There are many business types to understand quickly; each client is at a different stage of its Amazon journey, with its own commercial challenges and understanding of what successful selling on the platform takes. Advice and education need to match each client's maturity rather than follow one standard playbook.
- **Turning market signals into questions operators should answer about their own data**: Across the posts, Simpson takes an external signal — a ChatGPT email about shopping, a research release, a platform change — and turns it into questions ecommerce operators can apply to their own catalogues, systems and processes. The posts make the argument actionable, then leave readers with a question that invites discussion.

## Work to read

- [Process first: the argument behind the PREPARED ecommerce system](https://www.linkedin.com/posts/karlsimpson_why-process-is-the-first-pillar-of-ecommerce-activity-7475689128861548545-LneL)
- [AI shopping, the Nielsen IQ numbers, and why product data has to change](https://www.linkedin.com/posts/karlsimpson_chatgpt-is-now-emailing-users-about-how-to-activity-7472546862508625920-m3kr)
- [The Product Data Advantage: where the longer writing lives](https://www.linkedin.com/posts/karlsimpson_for-years-i-believed-smaller-product-catalogues-activity-7469540045008384001-p_Ns)
- [One month on the agency side of Amazon, and the experience behind it](https://www.linkedin.com/posts/karlsimpson_so-after-1-month-of-living-on-the-agency-activity-7400461167623819264-AAmL)

## Brand relationships

- **Unified Retail** (employment)
- **The Product Data Advantage** (owned_business)

## Partnerships

Karl Simpson's four LinkedIn posts, published between late November 2025 and late June 2026, and profile document no partnership offer, sponsor policy, rate card, media kit, paid brand engagement, or way to submit a partnership request. They do show a self-published newsletter, The Product Data Advantage on Substack, which they describe as free weekly content on product data, ecommerce, merchandising, retail, and AI. This shows where their writing appears and that readers are not charged for it; it does not establish whether paid placements, sponsored articles, or consulting work are available. The posts also provide no commercial terms, deliverables, exclusivity, turnaround, or pricing. Ask Simpson directly via the LinkedIn profile listed under their name whether they accept sponsorships or paid work, including sponsored content, consulting, or webinars, and on what terms.

## Alternatives

- Haider Ali: Choose Ali when a campaign rewards a repeatable AI workflow an operator can copy the same week, rather than a governance argument. The posts show a working method: saving a prompt as a Gemini skill in Chrome so it runs across open Amazon tabs and returns listing comparisons, review themes, brand-store positioning and three content or product gaps formatted for a creative brief. The setup steps and prompt are published for readers to reuse. The second post is a plain-language explainer on agent-driven purchasing — the Universal Commerce Protocol, agent checkout, OpenAI ads via ACP and Amazon Rufus — arguing that sellers who cannot be found and bought from by an AI agent will miss the purchase. For a SaaS series aimed at sellers who want a usable prompt and a straightforward account of how AI agents buy, this is a closer fit. Both posts invite feedback, making them suitable for a webinar Q&A or working session.
- Vincenzo Toscano: Choose Toscano when the campaign should focus on live events and peak-season advertising rather than product data. The posts describe hosting a packed Amazon EU Accelerate meetup at the London Chamber of Commerce and Industry and keynoting the first Amazon Ads EU Business Accelerator, with Ecomcy named as an event sponsor and a podcast recorded with a Rising Stars brand. The advice to the room is concrete and seasonal: stop treating Q4 advertising as “spend more and hope”; use AMC and DSP to see who actually buys rather than who clicks; build audiences before peak so cost-per-click spikes do not eat margin; and retarget into January because the sales cycle does not end on Black Friday. A campaign on advertising strategy for European expansion, or a series needing a speaker who can carry a room, fits better than the catalogue-quality argument.
- Brendan Ducie: Choose Ducie when the audience is new to selling online and needs vocabulary and a cautionary framing rather than operator-level detail. One post explains the difference between digital marketing, online marketing and ecommerce, using a website sales example to distinguish marketing that builds a brand from the system that takes the order. The other warns about buying and selling on Amazon: wholesale and retail arbitrage are brutally competitive, anyone can undercut your price, the only leverage in wholesale is logistics through your own warehouse, shipping or drop-shipping, and long-term success means selling on your own site or through affiliate sales. The posts answer entry-level questions about what these terms mean and whether marketplace selling is worthwhile, in plain language.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/