01
Hypothesis
Define a specific question about how AI shopping systems perceive a product, category, or merchant signal.
Laboratory · 01
Agentic Commerce Laboratory.
The Agentic Commerce Laboratory is our applied research practice for agentic commerce readiness: the product data, merchant signals, schema, feed structure, and trust architecture an autonomous shopping agent needs to discover, evaluate, and transact with a brand. It runs controlled experiments on Shopify, WooCommerce, and marketplace storefronts to identify which signals reliably move products into AI-generated shopping answers.
Focus areas
What this laboratory investigates
Product entity modeling for AI shopping systems.
Merchant data quality, policies, and trust signals.
Product feed structure for emerging agentic protocols.
Structured review and rating architecture.
Category and collection page semantic design.
Transaction-readiness signals for autonomous agents.
Methodology
How the laboratory operates
02
Instrumentation
Build test catalogs, schema configurations, and feed variants on representative storefronts.
03
Observation
Probe AI assistants and shopping surfaces with structured prompt sets and capture behavior over time.
Active experiments
What we are currently testing
Product attribute completeness vs AI selection probability
Measuring how attribute coverage and structured specs influence whether AI agents shortlist a product.
Schema depth in collection pages
Testing the impact of nested Product, Offer, and AggregateRating schema on retrieval into AI shopping answers.
Merchant policy clarity
Examining how shipping, returns, and warranty clarity influence agent confidence in recommending a merchant.
Review structure and agent trust
Studying how structured, verified review data changes recommendation behavior across AI assistants.
Applied to
Shopify BrandsWooCommerce BrandsMarketplacesDTC Retail
FAQ
Frequently asked questions
Follow this laboratory's research.
Findings from this laboratory are published as the research programme develops.