How Would an AI Agent Browse Your Website?

How Would an AI Agent Browse Your Website?

Site Discovery in QueryBurst simulates an AI agent exploring a site over 10–15 autonomous turns — querying, reading results, refining its understanding, and querying again, just as AI assistants do through iterative retrieval. Every retrieved page, relevance score, and synthesised understanding is logged. Run it in general discovery mode to see what an agent finds naturally, or goal-focused mode to test whether it can reach specific content. Pages it never surfaces are effectively invisible to AI, regardless of their quality.

Two Discovery Modes

General Discovery

Explores your entire site broadly to understand:

Goal-Focused Discovery

Enter a specific question (e.g., "Which mattress is best for back pain?") and watch AI try to answer it using only your website content. This reveals whether your content can answer real user questions.

Understanding the Exploration

Live Exploration View

During discovery, you see a split-pane view:

Left Panel - Exploration Stream:

Right Panel - Turn Details:

Turn Anatomy

Each turn represents one autonomous exploration step:

Element Description
Search Query What the AI is looking for
Pages Found Pages matching the search with scores
Pages Selected Top pages chosen for deep reading
Chunks Retrieved Specific content sections extracted
Summary AI's understanding from this turn
Confidence High/Medium/Low based on content quality
Gaps What the AI couldn't find

Confidence Indicators

Query Expansion

When initial search fails, the AI expands the query with synonyms and related terms. Expansion being triggered indicates vocabulary gaps—your content uses different terms than users search for.

Understanding the Report

Executive Summary

AI-generated overview of what was learned about your site.

Clearly Understood

Topics where high-confidence information was found. These are your discoverability wins.

Partially Understood

Topics with incomplete information. May indicate thin content or buried information.

Could Not Find

Topics the AI searched for but couldn't locate. These are content gaps or severe discoverability issues.

Gap Validation (Deep Search)

After identifying gaps, the system does a secondary deep search to check if content actually exists but wasn't surfaced. This distinguishes between:

Retrieval Diagnostics

Metric Meaning
Top Surfacing Pages Which pages appeared most often in results
Queries Expanded How many searches needed query expansion
Boilerplate % Navigation/footer content in results
Issues Specific problems detected

What This Reveals

Discoverability Problems

  1. Content exists but doesn't surface - Gap validation shows content is there, but AI couldn't find it through normal search
  2. Vocabulary mismatch - High query expansion rate means your terms don't match user language
  3. Thin content - Low confidence or partial understanding despite topic coverage
  4. Boilerplate pollution - High boilerplate % means navigation drowns out content

Content Gaps

Topics in "Could Not Find" that have no content in gap validation are true gaps—opportunities to create content users and AI are looking for.

Best Practices

Improving Discoverability

✅ Do use the same terms users search for
✅ Do ensure important topics have dedicated, focused pages
✅ Do include clear headings that signal topic coverage
✅ Do repeat key terms naturally throughout content
❌ Don't bury important information in unrelated pages
❌ Don't rely on brand-specific jargon users won't search
❌ Don't put key content only in images without alt text

Acting on Results

  1. Low confidence turns - Review and expand that topic's content
  2. Query expansion triggers - Add the expanded synonyms to your content
  3. Top surfacing pages - These are your SEO power pages, optimize them
  4. Boilerplate issues - Improve content-to-navigation ratio

Timing

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