Optimize content for Google + AI

You have existing articles, landing pages or shop copy and want to make them fit for modern search — for Google and for ChatGPT/Perplexity at the same time. The Content Optimizer scans, scores and suggests concrete changes.

What is the Content Optimizer?

Unlike the AI Content Editor, which generates articles from scratch, the Optimizer works on existing material. It pulls in the URL (or a plain text block), analyzes SEO factors (title, meta, heading structure, keyword density, internal links, schema), GEO factors (citation potential for LLMs, fact density, source attribution) and readability. Output: prioritized suggestions you can accept or reject one by one.

Start the analysis

In the UI: Content → Content Optimizer → New analysis. Via the API either with a URL:

curl -X POST https://rankion.ai/api/v1/content-optimizer/analyze \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"url": "https://mydomain.com/blog/vegan-protein"}'

…or with raw text + target keyword:

curl -X POST https://rankion.ai/api/v1/content-optimizer/analyze \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -d '{"text": "Lorem ipsum…", "keyword": "vegan protein"}'

Cost: 5 credits. Asynchronous — returns HTTP 202 and an analysis ID.

Poll the status

An analysis typically takes 10–20 seconds (scraping + score calculation + suggestion generation). The UI polls automatically. Via the API:

curl https://rankion.ai/api/v1/content-optimizer/{id} \
  -H "Authorization: Bearer YOUR_TOKEN"

When status: completed, the score and suggestions[] are populated.

Review suggestions

An analysis usually delivers 15–25 suggestions, each with:

• Category — title, meta, h1, keyword_density, semantic, faq, schema, citation, …
• Priority — high, medium, low
• Diff — before/after comparison (side by side in the UI)
• Rationale — why the suggestion lifts your score

Work through the high-priority suggestions first. Common bullseyes: title too long/too generic, missing H2 hierarchy, no FAQ schema, too few external source citations (critical for GEO).

Apply suggestions

Mark the suggestions you want to take and send them back:

curl -X POST https://rankion.ai/api/v1/content-optimizer/{id}/apply \
  -H "Authorization: Bearer YOUR_TOKEN" \
  -d '{"suggestion_ids": ["sug_123", "sug_124", "sug_125"]}'

Cost: 5 credits. The response contains the optimized text/HTML, ready to paste into the CMS.

Best practices

• Title — main keyword in the first third, max 60 characters, clear promise.
• Meta description — 140–160 characters, active phrasing, with a CTA.
• H1 — unambiguous, unique per page, contains the main keyword.
• Semantic keywords — sprinkle in the terms from related[] of your keyword research (Keyword research with the Explorer).
• FAQ schema — structured data + a visible FAQ section. Both: Google loves it, LLMs cite it disproportionately often.
• Citations — external reputable sources with links, back your own claims with data. Lifts the GEO score noticeably.

Content freshness as a follow-up

Optimization is not a one-shot job. Markets shift, and so do SERPs. Plan a refresh cadence (e.g. quarterly for top articles). The AI Content Editor supports automatic freshness checks and can generate optimized versions — see AI Content Editor and Articles API.

Whoever combines both — new articles via Your first article with the AI Content Editor and old URLs via the Optimizer — systematically builds a site present in Google SERPs and in AI answers.