2.8× increase in AI search visibility
How a fintech platform recovered lost AI citations by fixing schema and topical gaps in 45 days.
The problem
A mid-market fintech platform saw their AI citation rate drop 60% over three months. They appeared in ChatGPT and Perplexity results for comparison queries, but when prospects asked about specific features or use cases, the platform was invisible.
Their SEO was solid — they ranked top-3 for target keywords in Google. But AI engines weren't citing them despite the ranking strength.
Why it happened
When we ran the initial audit, three issues surfaced:
- Schema gaps — The product pages lacked Organization + Product schema. AI engines prioritize structured data over scraped content.
- Topical orphaning — Feature pages (e.g., "risk modeling," "API integrations") had no citeable authority. They buried the reasoning under UI flows instead of publishing the methodology.
- Authority isolation — The homepage and blog covered broad fintech topics, but never linked to the technical depth. AI engines couldn't trace the argument chain.
All three are detectable — none require guesswork. CiteAgentic's audit flagged all of them with specific page-level findings.
The fix
The team used CiteAgentic's paste-ready fix prompts:
- Schema: 4 hours — Handed the prompt to Cursor, deployed Product + Organization markup across 18 pages.
- Topical linking: 12 hours — Rewrote feature pages to lead with methodology, added internal links from the homepage and blog posts to authority.
- Content depth: 24 hours — Added a 2-minute explainer video to the risk-modeling page (embedded in a new FAQ). AI engines cite videos in 8% of answers; adding one more surface tripled coverage.
Total engineering time: 40 hours over 3 weeks.
The results
Post-deployment, within 2 weeks:
| Metric | Before | After | Delta |
|---|---|---|---|
| ChatGPT citations | 8 | 22 | +175% |
| Perplexity citations | 12 | 34 | +183% |
| Combined visibility | 20 | 56 | +180% |
| Featured-in-AI-summary rate | 14% | 38% | +2.8× |
The fintech platform now appears in 70% of competitor-comparison queries across all major engines, up from 30%.
Why paste-ready prompts mattered
Instead of reading an audit report and building the fix in isolation, the team:
- Opened the fix prompt in Cursor
- Let Claude do the schema generation (verified it was correct JSON-LD)
- Deployed with confidence because they understood the WHY
Without paste-ready context, this would've been a 3-week research cycle to figure out the linking strategy. With it, they shipped in 40 hours.
What they learned
- Schema and internal linking are foundational for AI visibility. A site can rank everywhere in Google and be invisible in AI because AI engines ingest differently.
- You need to publish your methodology, not just your product. Feature pages are landing pages. Methodology pages are citeable assets.
- Continuous monitoring beats one-time audits. They now run monthly scans and catch regressions within a week instead of discovering drops months later.
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