AI systems do not browse your website the way humans do. They parse structured data, interpret entity relationships, and synthesize knowledge graph entries to form recommendations. Without proper schema markup and machine-readable infrastructure, your content is invisible to the answer engines that are rapidly replacing traditional search.
Conversion Insights builds the technical foundation that makes your brand legible to AI — from comprehensive Schema.org implementation to product feed optimization for emerging agentic commerce protocols.
Request a Technical AuditThe Problem
Invisible to AI
68% of websites lack sufficient structured data for AI systems to accurately parse their offerings.
Without schema markup, answer engines cannot determine what you sell, where you operate, or why you are authoritative.
The consequence: when a user asks ChatGPT, Gemini, or Google AI Overviews for a recommendation in your category, your brand does not exist.
Schema is not decoration. It is infrastructure.
The shift from search engines to answer engines has fundamentally changed what "being found" means. Traditional SEO optimized for crawlers that indexed keywords. AI systems require something entirely different: machine-readable, semantically structured data that communicates meaning, relationships, and authority.
Large language models do not match keywords to pages. They build internal representations of entities and their relationships. Schema markup is how you tell AI systems what your business is, what it offers, and how it relates to the broader knowledge graph. Without this, you are asking AI to guess — and it will guess wrong, or not guess at all.
Google's Knowledge Graph, Bing's entity index, and the internal representations used by ChatGPT and Gemini all depend on structured data to establish entity identity. If your Organization schema is missing, your business has no node in the graph. If your Product schema is incomplete, your offerings cannot be compared or recommended.
The next wave is not just AI recommending brands — it is AI agents autonomously purchasing on behalf of users. These agents need standardized, real-time product feeds with pricing, availability, and specifications. The Universal Commerce Protocol is emerging as the standard. Businesses without compliant feeds will be excluded from autonomous transactions entirely.
Our technical foundation work is not a one-time audit. It is a systematic buildout of the machine-readable infrastructure your brand needs to be visible, verifiable, and recommendable by AI systems across every major platform.
Comprehensive implementation of Schema.org vocabulary types across your entire digital presence. We audit existing markup, identify gaps, and deploy the full range of applicable schema types that AI systems depend on for entity recognition.
Implementation of JSON-LD as the primary structured data format — the format preferred by Google and most effectively parsed by AI systems. We build interconnected data blocks that communicate entity relationships, not just attributes.
Prepare your product and service catalogs for the emerging world of agentic commerce. We structure feeds so AI shopping agents can read inventory, pricing, specs, and availability without ever visiting your website.
Beyond traditional technical SEO. We optimize your infrastructure for AI crawlers, LLM indexing pipelines, and the vectorization processes that determine how your content is embedded in AI models.
Prepare for the protocol that will allow AI agents to autonomously transact. We build the technical infrastructure so your catalog is ready when UCP and ACP adoption reaches critical mass.
Establish and reinforce your entity node in Google's Knowledge Graph and the internal entity indexes used by major AI platforms. We ensure your brand is recognized as a distinct, authoritative entity.
Every business has a unique entity profile. We implement the precise combination of Schema.org types that maps your organization, products, services, and expertise into a format AI systems can parse with confidence.
Establishes your business as a recognized entity with name, logo, contact info, founders, and social profiles. The foundation of knowledge graph identity.
Defines individual products with pricing, availability, reviews, specifications, and brand attribution. Essential for AI shopping agents and comparison queries.
Maps your service offerings with descriptions, service areas, provider details, and offer catalogs. Enables AI to recommend your services for relevant queries.
Structures question-and-answer content for direct extraction by AI. FAQ schema is among the most frequently parsed types by answer engines for conversational responses.
Provides step-by-step instructional content in a machine-readable format. AI systems frequently cite HowTo content when users seek procedural guidance.
Identifies authored content with publication dates, authors, and topics. Critical for establishing topical authority and citation credibility in AI models.
Establishes individual expertise, credentials, and affiliations. Person schema connects founders and experts to their organizations, reinforcing entity authority.
Maps your physical presence with geo-coordinates, service areas, hours, and local attributes. Essential for location-based AI recommendations and local answer queries.
Defines site hierarchy and page relationships. Helps AI systems understand content organization, topical clustering, and the relative importance of pages within your domain.
The next frontier is not just AI recommending your brand — it is AI agents autonomously comparing, selecting, and purchasing on behalf of users. This requires a fundamentally different kind of product feed: real-time, comprehensive, and structured for machine consumption rather than human browsing.
We prepare your catalogs for the protocols that will define agentic commerce, ensuring your offerings are not just visible but transactable by AI systems.
Schema Layer
Schema.org markup establishes entity identity and product attributes on your website.
Feed Layer
Standardized product feeds distribute your catalog data to AI platforms, shopping agents, and comparison engines.
Protocol Layer
UCP and ACP compliance enables AI agents to query, compare, and transact against your catalog autonomously.
Transaction Layer
Secure, autonomous purchase execution by AI agents — the end state of agentic commerce infrastructure.
WHERE ARE YOU IN THE STACK?
Most businesses are stuck at Layer 0 — no schema at all. We build from the ground up.
We crawl your entire digital presence, audit existing schema markup, identify missing entity types, and benchmark against competitors who are already visible to AI systems.
We design a comprehensive schema strategy — mapping entity types to pages, defining relationships between entities, and planning the JSON-LD data graph that will represent your brand to AI.
We deploy JSON-LD structured data across your site, optimize product feeds, validate all markup through Google's Rich Results Test and Schema.org validators, and resolve any errors.
We monitor Rich Results performance, track AI visibility changes, and iterate as Schema.org evolves and new commerce protocols emerge. Your technical foundation is a living system.
Schema markup provides machine-readable context that AI systems use to understand what your business offers, how it relates to other entities, and whether it should be recommended. Without proper schema, your content is essentially invisible to answer engines like ChatGPT, Gemini, and Google AI Overviews. Structured data transforms unstructured web content into knowledge graph entries that AI models can confidently cite and recommend. It is the difference between being a webpage and being an entity.
Schema markup refers to the vocabulary (Schema.org) that defines entity types and their properties — things like Organization, Product, Service, and FAQ. JSON-LD (JavaScript Object Notation for Linked Data) is the implementation format recommended by Google and preferred by AI systems. It allows you to embed structured data as a script block in your HTML without modifying the visible page content. Think of Schema.org as the language and JSON-LD as the delivery mechanism. Together, they form the bridge between your content and the knowledge graph.
The Universal Commerce Protocol (UCP) is a machine-readable catalog standard that allows AI shopping agents to read your inventory, pricing, specifications, and availability without visiting your website. Preparing for UCP involves structuring your product and service feeds with comprehensive schema markup, ensuring data accuracy and real-time availability, and implementing standardized data formats that agentic commerce systems can parse autonomously. This is the infrastructure layer that enables AI agents to transact on behalf of users. Businesses that prepare now will have a significant first-mover advantage as adoption accelerates.
Traditional technical SEO focuses on crawlability, page speed, and indexation for search engine bots that rank pages. Technical SEO for AI goes further — it ensures your content is not just crawlable but comprehensible to large language models. This means implementing rich structured data, establishing clear entity relationships, building topical authority signals, and ensuring your content can be vectorized and embedded accurately in AI training pipelines. The goal shifts from ranking on a results page to being the recommended answer in a conversation.
The transition from search engines to answer engines is accelerating. Every day without proper schema markup is a day your brand is invisible to the AI systems your customers are already using. Let us build the technical infrastructure that makes you findable, citable, and recommendable.
Schedule a Technical Foundation Consultation