# PDP Radar - Full Content for AI Crawlers

This file is the long-form companion to /llms.txt. It contains the substantive content of PDP Radar's educational pages so that AI crawlers and language models can ingest the full text without executing JavaScript.

Site: https://pdpradar.com
Last updated: 2026-05

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PDP RADAR - WHAT IT IS
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PDP Radar is a free web tool that analyzes any Shopify product page and tells you whether AI shopping agents can actually find, understand, and recommend it. Shopify automatically feeds every product on every Shopify store into a Global Product Catalog, and AI agents from Google AI Mode, ChatGPT Search, Perplexity, Microsoft Copilot, and others query that catalog when shoppers ask for product recommendations. PDP Radar surfaces what those agents see, scores it, and gives merchants a prioritized fix list.

PDP Radar evaluates two distinct channels:

1. AI SEO channel: scores the on-page structured data (JSON-LD) that AI search engines crawl from your live PDP. This is the channel that matters when an AI summary or generative search result cites your page directly.

2. Agentic Commerce channel: scores the Shopify Global Product Catalog feed for your product. This is the channel that matters when an autonomous AI shopping agent (such as a future ChatGPT shopping mode) is comparing products to recommend or buy. For Shopify stores, this channel also checks for the four agentic discovery files: /llms.txt, /llms-full.txt, /agents.md, /sitemap_agentic_discovery.xml.

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THE SIX AI COMMERCE SCORING CATEGORIES
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1. Core Product Data (30% weight) - title, description, brand, GTIN, SKU, attributes, color, size, material, category. The fundamental identity of the product.

2. Pricing & Offers (15%) - price, currency, sale price, price valid until date, availability status, item condition.

3. Availability & Fulfillment (15%) - shipping cost, shipping speed, delivery time estimates, return policy, refund policy, in-store pickup.

4. Visual Assets (15%) - product images (count and quality), image alt text, OpenGraph image for social/AI previews, video.

5. Conversational Readiness (15%) - FAQ schema, feature lists, use cases, technical specifications, comparison data. The data AI uses to answer follow-up questions.

6. Trust & Reviews (10%) - aggregate rating, review count, individual review snippets, brand schema, manufacturer info.

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HOW AI SHOPS - HOW AI AGENTS DISCOVER AND RECOMMEND PRODUCTS
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When a shopper asks an AI assistant for a product recommendation ("find me the best wireless earbuds under $150"), the AI does NOT browse the open web like a human. It queries structured product catalogs and ranks the results based on the completeness and quality of the data those catalogs expose.

For Shopify stores, the relevant catalog is Shopify's Global Product Catalog. Every product on every Shopify store is included automatically, no opt-in required. The catalog exposes:

- Core product fields (title, description, vendor, product type, tags)
- Variants (size, color, SKU, price, inventory)
- AI-generated enrichment fields, including a unique selling point summary, top features list, and use cases, all generated by Shopify's AI from your existing product data

The quality of this data determines whether your product is recommended or skipped. AI agents prefer products with:

- Complete brand and identifier data (GTIN, MPN)
- Clear differentiators (unique selling points, key features)
- Pricing with availability
- Returns and shipping clarity
- Verified reviews and ratings

The same logic applies to AI search engines (Google AI Mode, Perplexity, ChatGPT Search) when they cite product pages directly. They rely on JSON-LD Product schema embedded in the HTML.

Why two channels matter: a product can rank well in AI search because its on-page JSON-LD is rich, while still being invisible to autonomous shopping agents because its catalog feed is incomplete. PDP Radar scores both so merchants can see exactly where to invest.

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GENERATIVE ENGINE OPTIMIZATION (GEO) FOR SHOPIFY
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GEO is the discipline of optimizing for AI-generated answers, not blue links. Traditional SEO maximizes click-through from search results. GEO maximizes citation, recommendation, and conversion inside AI responses. The mechanics are different:

- Crawl signals: AI crawlers (GPTBot, ClaudeBot, PerplexityBot, OAI-SearchBot, Google-Extended) need explicit allowance in robots.txt.
- Structured data: JSON-LD Product, Offer, AggregateRating, Brand, FAQPage, HowTo. Schema.org is the lingua franca.
- Agentic discovery files: llms.txt, llms-full.txt, agents.md, sitemap_agentic_discovery.xml. Shopify auto-emits these for stores that enable AI agent discovery in admin settings.
- Catalog feed completeness: every field on the product object that Shopify exposes via Catalog API v2.

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HOW TO OPTIMIZE YOUR SHOPIFY STORE FOR AI - PLAYBOOK
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Step 1: Audit a single product with PDP Radar. Paste the URL at https://pdpradar.com/analyze. Note your AI Commerce Score and which categories scored lowest.

Step 2: Fix Core Product Data first (highest weight). For each product:
- Title: include brand and primary attribute (e.g. "EKO Mirage X 80L Stainless Steel Motion Sensor Trash Can")
- Description: structured paragraphs, not marketing prose. Lead with what it is, what it does, who it is for.
- Brand / Vendor: must be set. PDP Radar reports vendor as missing if Shopify catalog returns no value.
- GTIN / Barcode: enter on every variant. AI agents use this to deduplicate across stores.
- Tags and product type: drive Shopify catalog enrichment.

Step 3: Complete pricing and availability. Shopify handles most of this automatically, but verify currency, sale-price-valid-until dates, and inventory status sync to the catalog feed.

Step 4: Add fulfillment policies. Shipping policy and return policy must exist as documents that Shopify can expose via the catalog. PDP Radar requires these via API only, never by scraping the storefront /policies/* URLs.

Step 5: Visual assets. Minimum five high-resolution images per PDP, alt text on every image, an OpenGraph image at 1200x630.

Step 6: Conversational readiness. Add a FAQ section with FAQPage schema, list key features in a structured block, include use-case scenarios. This is the data AI uses to answer "is this good for X?" questions.

Step 7: Reviews. Aggregate rating + review count + sample reviews exposed via JSON-LD AggregateRating. Reviews are the single biggest trust signal for AI recommendations.

Step 8: Enable Shopify's AI agent discovery in Admin > Online Store > Preferences. This auto-generates the four agentic discovery files at your store root and surfaces your catalog to autonomous shopping agents.

Step 9: Re-scan with PDP Radar after every change. Use the percentile benchmark to see how you compare to other scanned PDPs in our dataset (shown when sample size is statistically significant).

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PDP RADAR FEATURES
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Analyze: paste any Shopify product URL, get an AI Commerce Score and prioritized fix list in 10 to 30 seconds. No signup.

Agent View: search the way an AI agent searches. Enter a buyer-intent query ("organic face cream", "wireless earbuds under 150"). PDP Radar expands the query into 10 variations and shows every product an AI agent could surface, with each product's data completeness.

AI Agent Preview card: visualize what an AI agent actually sees on your PDP, including Shopify AI-generated unique selling points, top features, and missing-data hints.

Dual channel scoring: separate AI SEO and Agentic Commerce scores. See exactly where to invest.

Percentile benchmark: shown only once we have enough scans for a statistically reliable comparison (>=50 scans).

PDP Rocket: turns Reddit consumer insights into better product page content.

What's New: public changelog at /whats-new.

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RECENT UPDATES
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May 2026 - Shopify Agent Discovery files: PDP Radar now checks the four Shopify agentic discovery files and surfaces them in the Agentic Commerce report.

April 2026 - AI Agent Preview card: visualize what an AI agent sees, including Shopify AI-generated USPs, key features, and missing-data hints.

April 2026 - Agent View: search the way an AI shopping agent searches. Query expansion across 10 variations.

March 2026 - Dual channel scoring: separate AI SEO and Agentic Commerce scores.

March 2026 - Percentile benchmark: see how your PDP ranks against the rest of the PDP Radar dataset.

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