Resource library
Practical guides for AI product discovery, in four groups: checking product data, backing claims with evidence, publishing through channels and platforms, and observing what AI assistants say.
Product data checks
Start here when a product is hard for AI assistants, or shoppers, to understand: what is missing, unclear or inconsistent.
What a product data audit checks, how missing, conflicting and unconfirmed information are told apart, and a sample report.
ScoreWhat each of the six signals checks on a product page, and why the score is Hasmord's framework rather than any assistant's ranking.
ChecklistTen checks to run on one product page — identity, variants, units, use conditions, claims and sources — and how to record what you cannot confirm.
DiagnoseA layer-by-layer way to check crawlability, product information and channel eligibility — and what stays unknown when an AI assistant leaves a product out.
MarketplacesWhy the marketplace listing is often the easier thing for an assistant to quote, and what to put on your own product page so it answers the same questions.
AEOWhat AEO means for product pages, how it differs from classic SEO, and where product information fits in.
GEOThe same shift under its other name: making product content clear enough for generative answers to use accurately.
Evidence behind product claims
How to connect a claim to a source that matches the product, and separate what is supported from what still needs confirming.
How to connect a claim to a source that matches the product and model, with a worked before-and-after example.
WhitepaperHow AI answer engines surface products, how to observe your visibility, and the product-information levers worth checking — with worked examples. Read online or download the PDF.
Channels and platforms
Where your product information is published and how each store platform or shopping channel reads it.
How product results in ChatGPT differ from web citations, what merchant feeds and visible pages each need, and how to troubleshoot missing products.
ShopifyWhat Shopify already handles for you, what still depends on your product information, and a checklist for Shopify product pages.
WooCommerceProduct information checks for WordPress and WooCommerce stores, and why owning your markup helps.
BigCommerceThe information gaps to check in a BigCommerce catalog: custom fields, evidence and feed data.
AmazonHow to keep product information clear and consistent when the listing lives on Amazon and you cannot edit the page.
Amazon RufusHow Amazon’s shopping assistant compares products conversationally, and which listing information to review.
Observing AI answers
How individual AI assistants find and cite sources, and how to record what they say about your products over time. One assistant’s results do not stand in for another’s.
How ChatGPT cites web sources, what to check on your pages, and how to measure citations over time.
PerplexityHow Perplexity retrieves and cites sources, and what to check so your product pages can be read and quoted accurately.
Google AI OverviewsHow Google links sources in its AI summaries, and the product-page basics that still apply.
GeminiHow Gemini grounds answers in Google Search, and what to check on your product pages.
CopilotHow Copilot grounds answers in Bing’s index and cites sources, across Windows, Edge and Bing.
ClaudeHow Claude uses search and tools to ground answers, and what clear, trustworthy product facts look like.
Core references
Plans, comparisons and how Hasmord handles your data.
Plans, prices and limits: products, citation checks and features, plus how billing and cancellation work.
CompareHow Hasmord compares with SEO suites, agencies, AI writers and doing nothing — including where each alternative fits better.
FAQWhat AEO is, how citation checks work, plans and data handling — answered plainly.
TrustHow Hasmord protects your data: OAuth sign-in, encryption, tenant isolation, and GDPR-aligned handling.
AboutWho we are and how Hasmord approaches AI product discovery.