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After each audit — initial or weekly snapshot — zued generates recommendations automatically. They are specific to each URL, chunk, and prompt: not generic advice, but concrete changes tied to the exact analysis that produced them.

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Four types of output

Alignment Gaps

Per prompt and per content chunk: what AI engines say versus what your page actually contains. Includes missing topics, format mismatches, and accuracy issues.

Technical Issues

Per URL: bot blocking, JavaScript rendering failures, Core Web Vitals problems, missing structured data.

Cross-URL Insights

For prompts spanning multiple pages: how your URLs work as an ensemble, internal linking gaps, and unified recommendations. See Cross-URL Analysis.

Quick Wins

A ranked list of the highest-impact, lowest-effort changes across your entire project — sorted by priority score.

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Priority score

Every recommendation has a priority score from 0 to 100. The score is calculated from impact, effort, and how many AI engines are affected. See Prioritization for the full formula. Recommendations are grouped into four categories:
CategoryScoreWhen to act
Quick Win80–100This week
Strategic Investment50–79Next sprint
Medium Priority30–49After quick wins
Low Priority0–29Deprioritize
Technical issues that block AI crawlers are always scored at Priority 100 — fix these before any content changes.

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Tracking progress

When you implement a recommendation and the next snapshot runs, zued compares the new scores against the previous snapshot. Resolved quick wins are tracked automatically — you can see which changes produced measurable improvements.