Rankings Methodology
The definitive benchmark for enterprise readiness in the agentic era. We measure whether AI agents can find you, transact with you, and trust you — the scorecard for the next decade of customer acquisition.
Scoring Framework
150 enterprise websites across 10 industries, scored 0–100 on five equally weighted pillars. McKinsey projects $1–5 trillion in agentic commerce by 2030 — our methodology captures the transition from traditional web performance to AI-driven customer acquisition.
| Pillar | Weight | What It Measures |
|---|---|---|
| Brand Discovery & GEO | 20% | LLM visibility, structured data, AI crawl policies, GEO citation readiness |
| Agentic Commerce | 20% | MCP/A2A protocol support, product feeds, agent checkout, API access |
| On-Site AI Experience | 20% | Chat quality, voice AI, multimodal capabilities, agent DOM interaction |
| Modern Tech & Architecture | 20% | Modern framework, legacy-free stack, CDN/edge delivery, real-time capability |
| Performance & Speed | 20% | Performance analysis, mobile perf, Core Web Vitals (LCP/INP/CLS/TTFB) |
Brand Discovery & GEO
As AI models become the primary interface between consumers and brands, discoverability shifts from search engine indexing to LLM citation.
- LLM Visibility
- Presence and quality of llms.txt / llms-full.txt — the standard for providing LLMs with structured site descriptions.
- Structured Data
- JSON-LD and schema.org coverage. Rich structured data drives accurate AI citations about products, services, and content.
- AI Crawl Policy
- robots.txt handling of GPTBot, ClaudeBot, Google-Extended. Sites allowing AI crawling signal agentic-era readiness.
- GEO Readiness
- FAQ schemas, expert authorship markup, and content optimized for extraction in AI-generated responses.
Agentic Commerce
AI agents will browse, compare, and transact on behalf of consumers. This pillar evaluates whether a site exposes the protocols, feeds, and APIs agents need.
- Protocol Support
- MCP server endpoints (/.well-known/mcp.json), A2A agent cards, and OpenAPI specs — standardized by Anthropic, Google, and the Linux Foundation.
- Product Feeds
- OpenAI product feed compliance, Google Merchant Center feeds, and catalog structure for AI shopping agents.
- Agent Checkout
- Agentic Commerce Protocol support, payment token handling, and programmatic checkout flows.
- API Access
- Programmatic endpoints for catalog queries, inventory checks, and order placement with agent-suitable auth.
On-Site AI Experience
Customer-facing AI features — the most visible dimension of AI readiness.
- Chat Quality
- Conversational AI interfaces: context retention, site tool integration, modern LLM infrastructure vs. legacy decision-tree systems.
- Voice AI
- Voice agent detection via ElevenLabs, Vapi, and Retell signatures. Target: <800ms response latency.
- Multimodal
- Image, video, and 3D content within AI experiences — visual search, AR/VR previews, cross-modal adaptation.
- Agent Interaction
- DOM traversability, form fillability, and action APIs for external agent operation.
Modern Tech & Architecture
Modern stack signals — the foundation for fast, secure, agent-compatible experiences.
- Modern Framework
- React, Next.js, Vue, Angular, Svelte — modern JS frameworks that support widget embedding and dynamic AI experiences.
- Legacy-Free
- No jQuery dependency, modern build tooling, and clean dependency trees that reduce conflict risk.
- CDN & Edge
- CDN delivery (Cloudflare, Fastly, Akamai, CloudFront), modern hosting (Vercel, Netlify), and CSP headers.
- Real-Time
- WebSocket support, streaming HTTP responses, and infrastructure for live AI interactions.
Performance & Speed
Performance audits and real-world Core Web Vitals — the speed metrics that matter for both users and AI agents.
- Performance
- Blended performance score (60% mobile, 40% desktop) — the industry standard for performance measurement.
- Mobile Perf
- Mobile-specific performance — critical as mobile traffic dominates and agents increasingly operate on mobile-first APIs.
- Core Web Vitals
- LCP (≤ 2.5s), INP (≤ 200ms), CLS (≤ 0.1), TTFB (≤ 800ms) — Standard UX metrics via CrUX with lab-data fallback.
Data Sources & Collection
Sources
- Performance Testing — lab audits
- Chrome UX Report (CrUX) — real-world vitals
- Tranco — domain popularity ranking
- Green Web Foundation — renewable hosting verification
Detection Methods
- HTML analysis — script tags, structured data, AI widget signatures
- API probing — MCP, A2A, OpenAPI, llms.txt, product feeds
- Header inspection — CDN, hosting platform, CSP, security
- Protocol detection — WebSocket upgrades, SSE, streaming
- CMS fingerprinting — WordPress, Drupal, Contentful, Sanity
Limitations
- HTML-only AI detection — server-side features behind auth are not observed
- Single-location lab tests — performance may vary by geography
- CrUX availability — some sites lack sufficient traffic for field data
- Protocol detection — existence verified, quality not fully evaluated
- Voice AI — limited to known provider script signatures
- Public-only — gated/internal features are not captured
Our detection is intentionally conservative — false negatives are more likely than false positives.
Version History
- v3.0 — Feb 2026: Restructured to 5 equally weighted pillars. Added Modern Tech & Architecture (CDN, hosting, CMS detection). Merged CWV + Trust into Performance & Speed.
- v2.0 — Feb 2026: Expanded to 6 pillars. Added Agentic Commerce, Real-Time Speed. Restructured AI Capabilities into On-Site AI Experience.
- v1.0 — Jan 2026: Initial launch. 150 sites, 10 industries, 4 pillars.
Contact
Questions about methodology or your score? Reach us at rankings@point11.ai or request a review.