# Tom Shivers

Tom Shivers works on SEO and ecommerce growth, diagnosing problems such as technical issues, mismatched content, and weak conversion paths. Shivers's posts also explain how ecommerce businesses can prepare for AI-led shopping.

- Profile: https://b2binfluencer.marketing/creators/tom-shivers/
- LinkedIn: https://www.linkedin.com/in/tom-shivers
- LinkedIn followers: 1,854
- Topics: artificial-intelligence, ecommerce, paid-ads, seo, agentic-commerce, paid-media, ecommerce-growth
- Based on 11 dated posts, latest 2026-06-30

## Summary

Tom Shivers is most useful for explaining ecommerce SEO fixes and AI shopping protocols to practitioner audiences.

- Best for: A B2B ecommerce software brand wanting a sponsored explainer or webinar on agentic commerce.
- Not for: A consumer brand or DTC apparel company seeking high-reach short-form video product promotion.
- Check first: Confirm recent post reach, engagement, and audience job titles on comparable agentic commerce topics.

### Takeaways

- A B2B ecommerce turnaround lifted revenue from $3.1 million to $7.5 million.
- Google's protocol moves the storefront into the feed; poor data means no recommendation.
- OpenAI and Stripe's Agentic Commerce Protocol lets AI agents shop.

## Main ideas

- **Stalled growth usually reflects a cluster of misdiagnosed problems, not one big failure**: Tom Shivers argues that when an ecommerce business stops growing, the cause is rarely a single failure. Several problems reinforce one another: weak rankings, technical issues that suppress visibility, content that misses high-intent demand, thin conversion paths, and paid traffic carrying more of the load than it should. Because these problems interact, the order of repairs matters. Fixing the right things in the right order unlocks the channel; fixing the loudest thing first does not.
- **The same five blockers recur across industries**: Drawing on work across B2B, B2C, SaaS, ecommerce, automotive, healthcare, home services, and food and beverage, Tom Shivers names five recurring blockers: misdiagnosed SEO issues; channel hype that creates a resource imbalance and starves parts of the system that are working; wasted ad spend; content that misses intent; and teams stretched too thin to fix root causes. The post argues that symptoms vary by industry, but the underlying mechanics do not, so the same diagnosis keeps applying. It promises to break down the blockers one at a time, starting with SEO misdiagnosis.
- **Agentic commerce arrived before most retailers noticed—and extends the stack rather than replacing it**: Tom Shivers argues that OpenAI and Stripe's Agentic Commerce Protocol (ACP) quietly bridged retailers and AI agents months before Google formalized its own approach. Inside ChatGPT, ACP enables AI-driven product discovery and comparison, conversational shopping, cart building, checkout through delegated payments, and post-purchase handling by the retailer. The retailer remains the merchant of record, answering the post's central question: how can an AI agent shop without becoming a marketplace? The open-source protocol is designed to be interoperable, allowing any agent, payment processor, or retailer to adopt it. ACP extends an existing ecommerce stack to AI agents rather than replacing it.
- **Google's protocol moves the storefront into the feed; poor data means no recommendation**: Tom Shivers describes Google's Universal Commerce Protocol (UCP) as enabling AI agents to compare products, check inventory, build carts, and complete checkout without visiting the retailer's website. Unlike marketplaces such as Amazon or Walmart, the merchant retains the transaction, post-purchase experience, and customer relationship. The post reframes the buyer path in three lines: the structured feed is the new homepage, the product graph is the new search results page, and the AI agent is the new buyer journey. Incomplete, inconsistent, or poorly structured data means a product will not be recommended. Merchant Center Next feeds, local inventory feeds, and structured data determine whether a retailer appears in AI Mode or qualifies for agent-led checkout. The four recommended actions are to fix product feeds, strengthen the brand entity with schema, publish authoritative content AI can cite and track citation share, and make payment, fulfillment, and policies machine-readable. The post offers a feed-readiness checklist for auditing ecommerce brands.
- **He writes and builds**: Tom Shivers covers ecommerce problems and builds a free calculator, using posts to put it in front of people. The approach favors practical resources over opinion alone.

## Work to read

- [How OpenAI and Stripe's Agentic Commerce Protocol lets AI agents shop](https://www.linkedin.com/posts/tom-shivers_last-week-i-summed-up-googles-universal-activity-7477796136594993152-Wug5)
- [Google's Universal Commerce Protocol and the four fixes it demands](https://www.linkedin.com/posts/tom-shivers_googles-new-agentic-commerce-standard-activity-7475574509262073856-p5my)
- [A B2B ecommerce turnaround from $3.1M to $7.5M](https://www.linkedin.com/posts/tom-shivers_a-midsized-b2b-ecommerce-company-came-to-activity-7472705762910441472-qSTg)
- [Five blockers that show up across every industry](https://www.linkedin.com/posts/tom-shivers_ive-worked-across-b2b-b2c-saas-ecommerce-activity-7473364458451578880-ccL8)
- [A free ecommerce ROI forecast calculator](https://www.linkedin.com/posts/tom-shivers_ecommerce-roi-calculator-forecast-profit-activity-7255235350137049088-6y2c)

## Partnerships

Tom Shivers has no documented partnership formats in these posts. Across five posts, none discloses a sponsorship, names a paying brand partner, or describes a format a brand could buy, such as a sponsored explainer, a paid webinar, or a newsletter placement. The two items closest to an offer are self-published resources—a free ecommerce ROI forecast calculator and a promised feed-readiness checklist—and neither carries a sponsor or a price. Their independent, diagnostic voice may suit a brand seeking an agentic-commerce explainer, but collaboration terms would need to be agreed directly. The LinkedIn profile is the only visible contact surface; there is no media kit, rate card, or partnership intake page. Ask directly about available formats and rates.

## Alternatives

- Amelia Van Camp: Choose Amelia Van Camp when the sponsor wants the enterprise-market and infrastructure story rather than a protocol walkthrough. The two posts are vendor launch and joint-research announcements: Mirakl Agentic Activation, with Agentic Product Enrichment and Agentic Channels connecting merchants to large language model platforms starting with Microsoft Copilot, and a Mirakl and Merkle readiness playbook presented with market figures — fewer than 1% of scanned product pages scoring above the threshold where AI agents reliably surface products, $67 billion of Cyber Week 2025 sales influenced by AI agents, 393% year-over-year growth in AI-referred traffic to U.S. retail sites, and a projection that 55% of U.S. ecommerce spending will soon be agent-assisted. That suits a sponsor that wants benchmark numbers and a marketplace-infrastructure framing, and it shows a comparator already speaking to enterprise buyers through a named research partnership.
- Abdo Mazloum: Choose Abdo Mazloum when the campaign needs a platform-level implementation checklist rather than a cross-protocol explainer. The posts are concrete about platform changes and what to do about them. One audits what businesses send to Meta as the company broadens use of shared activity beyond ads, listing five checks before a July rollout: pixel and Conversions API deduplication, purchase values and currencies matching store revenue, event coverage at the right stage, consistent event matching parameters, and documented consent and governance. The other works through Shopify's May 2026 announcement that merchants can customise /agents.md, /llms.txt and /llms-full.txt, then lists what to audit so AI systems can understand a store: product titles, collection structure, product page copy, schema and structured data, Merchant Center feeds, reviews and product context, shipping and return clarity, and AI-readable theme data. If the sponsor's readers run Shopify or Meta and want configuration-level steps, this is closer to their working day than a protocol overview.
- Sharon Gai: Choose Sharon Gai when a sponsored piece should focus on payments and checkout, or on the consumer-side shift driving agent-led buying. One post maps four agentic payment protocols side by side: Google's Agent Payments Protocol, Mastercard's Agent Pay, Visa's Trusted Agent Protocol and PayPal's Agentic Commerce Platform, including which card networks and payment companies back each. The other traces agentic commerce through eBay, Amazon, social commerce and short video, then uses the 'ChatGPT GlowUp' example of shoppers asking a chatbot for skincare advice. It also notes that traffic from answer engines is already around 10% for some sites. Together, the posts offer a useful spine for a webinar on how agent-driven transactions get authorised, who is competing for the payment rail and how shopping behaviour is changing.

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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/