From near-invisible to 3.9K organic visits/mo in ~5 months.
Understood Care helps families navigate Medicare and CDPAP with real human advocates - but in early 2026 it was nearly invisible to AI engines, pulling roughly 1.2K organic visits a month. Five months of answer-engine optimization took it to 3.9K monthly visits, 313 top-3 keywords and citations across AI Overviews, Perplexity and ChatGPT.
The results
Understood Care had something most of its category lacked - real advocates with first-hand Medicare and CDPAP experience - but none of that expertise was reaching AI answers. When families asked ChatGPT, Perplexity or Google's AI Overviews about CDPAP eligibility or Medicare coverage, Understood Care wasn't cited; national publishers and government sites were. We engaged in February 2026 and spent five months turning that hard-won advocate knowledge into the exact format answer engines retrieve - crawl-ready, answer-first and clearly attributed - which tripled organic traffic and earned citations across every major AI engine.
The challenge
- Near-invisible to AI engines - almost no AI Overview, Perplexity or ChatGPT citations for high-intent Medicare and CDPAP questions.
- ~1.2K monthly organic visits and few top-3 rankings despite genuine, first-hand subject-matter expertise.
- Real advocate knowledge existed, but it wasn't structured, extractable or attributed in a way engines could use.
- Established health publishers and government sites dominated the answers families actually saw.
How we did it
- 01
Sprint A - Indexability & answer structure (Weeks 1-3)
Made every Medicare and CDPAP question crawl-ready and answer-first: FAQ and Speakable schema, 40-80 word direct-answer blocks, and clean entity naming (CDPAP, Medicare Part A/B, care advocacy) so engines could extract the content and attribute it to Understood Care rather than a competitor.
- 02
Sprint B - Topical authority cluster (Weeks 2-12)
Built a Medicare + CDPAP content cluster - a pillar with interlinked children - covering the questions families genuinely ask, grounded in first-party advocate experience rather than the reheated, generic copy that fills the category and gives engines nothing new to cite.
- 03
Sprint C - Trust & citations (Weeks 6-20)
Strengthened credibility with references, consistent entity signals and original first-party data worth quoting - lifting reference domains from ~200 to 334 and earning citations across AI Overviews, Perplexity and ChatGPT.
Key AEO tactics applied
- Direct-answer blocks (40-80 word extractable passages) on high-intent Medicare/CDPAP questions
- FAQ + Speakable schema on every advice page
- First-party advocate data AI engines can't find anywhere else
- Entity clarity for CDPAP, Medicare Part A/B and advocacy terminology
- Interlinked pillar-and-children cluster to concentrate topical authority
- Consistent references and citations to lift trust signals
- Answer-first rewrites of existing thin, generic pages
Why it worked
On high-intent healthcare questions, AI engines reward first-party, clearly structured answers over sheer volume. Understood Care was never going to out-publish national health sites - its advantage was encoding real advocate experience as extractable, well-attributed content. That is exactly the signal ChatGPT, Perplexity and AI Overviews retrieve and cite, which is why a small advocacy site could win answers that far bigger publishers lost.
Want results like Understood Care?
We run the audit, the content, the publishing, and the monitoring end-to-end - so your brand becomes the one AI cites.