B2B Trust Signals for Google, ChatGPT and Claude

By Abhinav Panse, founder of Profitonium Apps · Sources checked 27 October 2026

A business buyer needs to verify who is selling, what the exact order includes and which terms apply. Your website should let that buyer find the evidence without piecing it together from vague claims and conflicting pages.

Build trust by making your business identifiable, your claims verifiable and your purchasing terms clear. Keep those facts consistent across pages and feeds, and make the evidence accessible to buyers, search engines and AI assistants.

The 40 checks below turn that approach into a website review. First, here is what Google, OpenAI and Anthropic actually document, and where practical B2B recommendations begin.

What Google, ChatGPT and Claude actually document

How this guide was prepared: This guide draws on the official platform sources linked below and applies them to common B2B buying tasks. The research and drafting used AI assistance to organise and compare the documentation. It is a documentation-based checklist, not a ranking experiment. I build ecommerce tools at Profitonium Apps, so I have a commercial interest in this subject; the checklist separates published platform guidance from practical recommendations.

The platforms do not publish a shared trust score or one common list of ranking factors. Their guidance also covers different surfaces:

Platform or feature	What the public guidance supports	What it does not establish
Google Search, including AI Overviews and AI Mode	Helpful, reliable content; accessible pages; useful internal links; accurate structured data.	A universal trust score or special AI markup that guarantees inclusion.
Google Shopping and Merchant Center	Consistent business identity, transparent policies, genuine reputation evidence and accurate offers.	That complying with shopping policies automatically improves ordinary organic rankings.
ChatGPT search and shopping	Search-crawler access, plus factual and current product data for supported shopping integrations.	That a feed, schema block or review count guarantees a recommendation.
Claude web search and Research	Access to sources, citations and documented attention to source quality in its Research system.	A published B2B merchant ranking formula or evidence that Claude applies Google's E-E-A-T framework.

Google provides the clearest public guidance on trust. Its explanation of helpful content discusses experience, expertise, authoritativeness and trustworthiness: E-E-A-T.

“Of these aspects, trust is most important.”: Google Search Central

Google also explicitly says E-E-A-T is not a specific ranking factor. Quality raters help evaluate results; their ratings do not directly determine rankings. Google's helpful-content guidance.

Google Merchant Center is more concrete. It recommends consistent business details, accessible contact information, clear policies, authentic reviews and a functional website. Google's merchant trust guidance.

ChatGPT has separate search and shopping considerations. OpenAI identifies OAI-SearchBot as its search crawler and GPTBot as a crawler for potential model-training data. Their controls are independent. Allowing training is not a prerequisite for allowing search. OpenAI's crawler documentation.

For shopping integrations, OpenAI documents structured product feeds containing factual descriptions, identifiers, prices, availability and other item details. Its commerce guidance also identifies rich media, reviews and performance signals as useful to ranking, relevance and user trust, without publishing their weights. That guidance concerns commerce experiences. OpenAI's commerce guidance.

Claude's documentation gives us more detail about access and evidence than merchant ranking. Anthropic separates Claude-SearchBot, which supports search, from Claude-User, which fetches pages in response to users, and ClaudeBot, which collects potential training material. Anthropic's crawler documentation.

Anthropic's account of building its Research system describes evaluating source quality, including whether agents used primary sources rather than lower-quality secondary material. That supports a practical emphasis on evidence. It is not an ecommerce ranking specification for every Claude answer. Anthropic's Research-system explanation.

Use the checklist to inspect the facts, evidence and buying journey your site presents.

1. Make the supplier's identity easy to verify

A buyer should be able to establish who will fulfil the order and handle problems. Explain the relationship between your trading name, legal business and the brands you sell.

• State the business name and explain any difference between the legal name and trading name.
• Explain whether you are the manufacturer, an authorised distributor, an independent reseller or a marketplace.
• Provide usable contact details and accurate business hours, including the time zone where relevant.
• Make your About and Contact pages specific: who operates the business, what it supplies and which markets it serves.
• Keep business details consistent across your website, applicable merchant accounts and relevant external profiles; explain legitimate differences such as separate office and warehouse addresses.

“A leading global supplier” gives a buyer little to verify. A clear description of your actual role and operating history gives them a starting point. Publish only history and locations you can substantiate.

2. Put evidence beside claims that influence a purchase

An authorisation claim should identify the relationship it describes. A certification should make its scope clear. A document covering one model should not be presented as approval for the entire catalog.

• Support authorised-dealer claims with a current manufacturer listing or other verifiable evidence where available.
• Identify the issuer, scope and validity of certifications when making certification claims.
• Link technical claims to the applicable manufacturer datasheet, test report or other primary source.
• State the relevant model, revision, conditions and exclusions beside compatibility or performance claims.
• Remove unsupported superlatives, accreditation logos and claims of affiliation or endorsement.

Google Merchant Center's misrepresentation policy explicitly addresses false affiliations, misleading business information and offers a merchant cannot fulfil. The B2B application is straightforward: publish a claim at the same level of specificity as the evidence supporting it. Google's misrepresentation policy.

3. Identify the exact product and selling unit

Business purchases often depend on details that generic descriptions leave out. A buyer may need a particular revision, a pack rather than an individual unit, or an item that works with existing equipment.

• Record the actual brand, manufacturer part number and assigned GTIN where applicable; keep your internal SKU distinct.
• Specify the selling unit, pack quantity and included components or accessories.
• Publish the deciding specifications with units, and distinguish product dimensions from packaged dimensions.
• Give each variant its own accurate attributes, availability and offer details, with a link that selects it where supported.
• Keep unresolved specifications unresolved until someone verifies them; do not invent identifiers or compatibility claims to fill empty fields.

Google's product-data specification requires accurate identifiers and consistent offers. OpenAI's feed specification similarly distinguishes individual items and variants, and requires factual product descriptions. A complete-looking record is useful only when its values describe the item being sold. Google's product-data specification, OpenAI's product-feed specification.

4. Explain how the commercial relationship works

A B2B website may have account pricing, minimum order quantities, freight charges or made-to-order products. Make those conditions understandable before a buyer commits.

• Explain minimum order quantities, order multiples, pack pricing and the total minimum purchase where relevant.
• State whether a displayed amount is a unit price, pack price or other price basis, and explain applicable tax and freight treatment.
• Distinguish stock on hand, supplier availability, backorders and made-to-order items; separate dispatch estimates from delivery estimates.
• Explain quotation steps, purchase-order acceptance, account approval and payment terms where offered.
• Make warranty responsibility, return restrictions, cancellation conditions and restocking charges easy to find before ordering.

For Google Merchant Center, minimum-quantity offers have specific pricing rules: the submitted price must represent the minimum purchasable quantity, with the minimum total prominently shown on the landing page. A public offer must be purchasable at its submitted price; do not substitute a negotiated account price unavailable to that buyer. Google's product-data specification.

A quotation-only business can still publish valuable information for ordinary search. Google's merchant-listing experiences have purchase eligibility requirements. Do not invent a public price or a purchasable offer to satisfy a shopping validator. Google's merchant-listing documentation.

An example: turn supplier claims into facts a buyer can check

Imagine a fictional office-supplies wholesaler selling copy paper. All quantities, prices and terms below are invented to illustrate the method; they are not results from a merchant audit.

Before: a claim that leaves questions	After: an exact fact, if verified	Evidence to check before publishing
“Premium office paper”	“A4 paper, 80 g/m², 500 sheets per ream, five reams per case.”	The specification for that exact paper and the pack label.
“From $5”	“$25 per case. Minimum order: two cases, $50 before applicable tax and freight.”	The selling unit, minimum-order rule, public price and matching cart total.
“Fast shipping”	“Estimated dispatch within two business days. Transit estimates are shown separately for your destination.”	Current fulfilment rules and the delivery estimate for the buyer's destination.
“Easy returns”	“Unopened cases can be returned within 14 days of delivery; the buyer pays return freight.”	The applicable return policy, including any product or account exceptions.
“Authorised supplier”	“An authorised reseller of the named paper brand in the stated market.”	A current manufacturer record or written authorisation covering that relationship and market.

The useful change is the connection between a claim, the exact order and its supporting evidence. If the evidence is unavailable, leave the claim unresolved until it can be checked. A well-formatted table cannot establish whether any of these facts is true.

5. Show expertise through the work itself

Useful technical content explains how to make a decision, which evidence supports it and where the advice stops applying. Adding an author biography cannot compensate for incorrect guidance.

• Identify the author or qualified reviewer of technical guides where readers would reasonably expect that information.
• Describe relevant experience accurately and link to a meaningful profile; avoid invented credentials.
• Explain test methods and conditions whenever you claim that you tested a product or measured performance.
• Cite the specific primary sources supporting substantive technical statements.
• Review content when facts change, record meaningful updates and keep displayed review dates consistent with that work.

Google's “who, how and why” guidance supports making authorship, production methods and purpose clear. My practical extension for B2B content is to make responsibility traceable: someone should own the factual accuracy of a comparison, selection guide or compatibility statement. Google's helpful-content guidance.

6. Make independent evidence discoverable

Your own website can explain your business. External records can help a buyer check whether those explanations hold up.

• Keep genuine manufacturer dealer listings and relevant trade-association records accurate where applicable.
• Use authentic customer reviews and distinguish reviews of the supplier from reviews of a particular product.
• Attribute testimonials and obtain permission for customer names, logos and identifiable project details.
• Publish case studies with clear scope and supported outcomes; distinguish completed work from forecasts.
• Pursue relevant editorial coverage and legitimate industry relationships without buying ranking links or manufacturing endorsements.

Match external evidence to the claim it supports. A manufacturer directory can corroborate authorisation; customer feedback can describe a buying experience. Google also documents link-analysis systems, including PageRank, and prohibits manipulative link schemes. Google's ranking-systems guide, Google's spam policies.

7. Make the evidence accessible and the journey usable

Information has limited practical value if visitors cannot locate it or an intended crawler cannot retrieve it. Keep commercially sensitive account details private while making suitable public facts accessible.

• Put essential product facts and procurement answers in readable page text, with links to full supporting documents.
• Link guides to relevant collections or enquiry routes, and check that link destinations fulfil their labels.
• Align category groupings, filters and comparison information with verified attributes buyers actually use.
• Test mobile navigation, product selection, forms and checkout where offered; confirm that enquiries reach the intended recipient.
• Check HTTPS, accidental indexing restrictions, robots rules and CDN challenges for the pages and crawlers you intend to make accessible.

Supporting PDFs can contain valuable evidence. Summarise the deciding facts on the page and link the document so the context remains available.

For Google's AI features, the published foundations include indexability, snippet eligibility, internal links and textual content. Google says these features do not require a special AI text file or additional schema type. Google's AI-search guidance.

8. Make all versions of the information agree

A website can contain several representations of the same business or product: visible text, structured data, feeds, policy pages and transactional records. Review their agreement after changing a fact.

• Keep price, currency, availability and purchasing terms consistent for the same variant, quantity, market and customer entitlement across the applicable page, feed and checkout.
• Check that product and organisation structured data accurately represents the business and visible content.
• Inspect combined markup from themes, apps and custom code for conflicting representations of the same entity; multiple blocks alone are not an error.
• After editing a page, inspect older lower sections, FAQs, banners and other places that repeat the changed claim.
• Validate markup and relevant platform diagnostics, then inspect the real page and buying journey as separate checks.

Google says organisation markup can help it understand and distinguish a business. Its general structured-data rules require accurate, relevant content, and a successful validation does not guarantee a rich result. Schema can describe your evidence; it cannot manufacture it. Google's organisation markup guidance, Google's structured-data policies.

Check the platforms separately

For Google, check indexing and relevant Search Console reports. If you use Merchant Center, inspect its product and policy diagnostics separately. An organic result, a valid rich result and an approved shopping offer are different outcomes.

For ChatGPT, check the intended search access through OAI-SearchBot and the published network guidance. If you have a supported product-feed integration, verify its current data and scope. OpenAI's crawler documentation, OpenAI's product-feed specification.

For Claude, check the access you intend to provide to Claude-SearchBot and Claude-User. When testing answers, record whether web search actually ran and inspect the cited pages. Anthropic warns that Claude can misinterpret sources or produce incorrect responses; a citation is not a verification badge for the merchant. Anthropic's web-search guidance, Anthropic's explanation of incorrect responses.

Start with one buying decision

Choose an important product or category and write down the questions a real buyer needs answered. Include the exact item, order quantity, delivery constraints and relevant commercial terms.

First test discovery without naming your business. Then provide your URL and test whether the assistant correctly understands your information. These answer different questions: whether the business was found and whether a supplied source was interpreted accurately.

Record the date, tool, search setting, question, cited URLs and claims that were correct, wrong or unresolved. Repeat under comparable conditions. Track qualified enquiries and orders separately from mentions and citations.

My confidence is high in the documented platform requirements. The visibility or sales effect of applying this checklist remains unknown until measured.

Open one important product page now. Can a new buyer verify who is selling the item, establish exactly what they will receive, and understand the terms of buying it? Fix the first answer they cannot find or check.

Sources and further reading

These are the official sources used in this guide. Each supports the subject stated beside it; the B2B checklist combines that guidance with practical buying-journey recommendations.

Google Search and structured data

• Creating helpful, reliable, people-first content: E-E-A-T, trust, authorship and the “who, how and why” of content.
• AI features and your website: access, eligibility and established SEO practices for AI Overviews and AI Mode.
• A guide to Google Search ranking systems: documented ranking systems, including link analysis.
• Spam policies for Google web search: manipulative links and other practices that violate Search policies.
• Organisation structured data: identifying and distinguishing the business through markup.
• General structured-data guidelines: accuracy, relevance and rich-result eligibility limits.
• Merchant listing structured data: product, offer and purchase requirements for merchant-listing experiences.

Google Merchant Center

• Building trust with your customers: business identity, transparent policies, reputation and website presentation.
• Misrepresentation policy: misleading business claims, false affiliations and unfulfillable offers.
• Product-data specification: identifiers, variants, availability, pricing and minimum purchasable quantities.

OpenAI

• OpenAI crawlers: the separate roles and controls of search, training and user-triggered access.
• Agentic Commerce key concepts: structured product feeds and recommended commerce attributes.
• Product-feed specification: product records, factual descriptions and item-level offer data.

Anthropic

• Anthropic's web crawlers: Claude-SearchBot, Claude-User and ClaudeBot.
• How Anthropic built its multi-agent Research system: Research-system evaluation, source quality and primary evidence.
• Using Claude's web search: web-search behaviour and citations.
• Incorrect or misleading responses from Claude: why source-linked answers still need checking.

Related guides by Abhinav Panse

• Your Next Customer Won't See Your Store First. Their AI Will.: how AI changes ecommerce discovery.
• Your Best Product Descriptions Are Quietly Making AI Skip You: writing product descriptions that expose the deciding facts.