
Website GEO: an evidence-first guide to AI search visibility
Separate mentions, citations, and accuracy. Build an AI-visibility review around observations you can actually inspect.
IDEAS, EVIDENCE & NEXT STEPS
The Analysis Journal. Practical guides to websites, keywords, code, and AI—written for the people building what comes next.

Separate mentions, citations, and accuracy. Build an AI-visibility review around observations you can actually inspect.

Build a task-specific evaluation loop with reviewed cases, clear criteria, and evidence behind every judgment.

Keep queries, locations, devices, and collection methods attached to every search-result comparison.

Turn prompt changes into focused experiments. Compare paired cases and catch the regressions an average can hide.

Review repository structure, setup instructions, and test organization with clear scope and revision-level evidence.

Preserve original phrases, define intent, and map useful clusters to real editorial actions—without invented metrics.

Give observations, recommendations, missing values, and partial results a predictable place in your response format.

Define coverage, inspect metadata and links, then prioritize evidence-backed changes that your team can verify.

Build a clear failure path for timeouts, invalid JSON, partial batches, credentials, and cached reports.

Start with a decision, preserve the evidence, and design a report both humans and software can understand.
Explore by topic: Search & Discovery · AI & Evaluation · Code & Repositories · API Engineering
Explore the workflows. Inspect the evidence. Build something useful.