Skip to main content

The 5 recommendation types

What each AI Recommendation type covers and when to expect it.

J
Written by Jakka Pranav swaroop Naidu

Jakka groups recommendations into five types. Every card carries a tag so you can filter and prioritize.

Content quality

Recommendations to improve depth, readability, grammar, intent match, and freshness on existing pages.

Examples: "Add a FAQ section answering common pricing questions," "Tighten the first paragraph; readability is below your target."

Brand persona

Recommendations to bring content in line with your Brand Kit voice and persona settings.

Examples: "Switch from 'we' to 'you' on the pricing page to match your Friendly tone setting," "Avoid the banned word 'innovative' on this page."

Search and AI visibility

Recommendations to improve discoverability in traditional search and in AI answer engines.

Examples: "Add Article schema with author and datePublished," "The H1 on this page does not match the primary keyword from your brief."

Conversion and UX

Recommendations to remove friction and clarify intent on conversion-critical pages. Examples: "The CTA below the fold is hidden on mobile; promote it above the fold," "Add a trust badge near the pricing table."

Internal linking

Recommendations to strengthen the link graph and surface orphaned content. Examples: "Link from your homepage hero to the new case study," "This page has zero inbound internal links from any priority page."

How priority is calculated

Every recommendation has Impact, Effort, Confidence, and Reach chips. The priority score is roughly (Impact x Confidence x Reach) divided by Effort. High priority items appear first.

Related articles

Did this answer your question?