Organic leads 2,000 → 5,000 a month, in four months — in health insurance.
Deputy Manager, Marketing (SEO & AI Search) at ManipalCigna Health Insurance. Health cover is as YMYL as a category gets: Google is maximally skeptical, users are maximally cautious, and every page competes against aggregators with far larger content teams.
Situation
When I joined in November 2025, the organic program was steady but under-leveraged: roughly 107K organic users and 2,000 organic leads a month, with about 50K monthly clicks in Search Console against 2M impressions. The brand had authority; the site wasn't converting that authority into query coverage or leads at anywhere near its ceiling.
Constraint
Three at once. Health-insurance content is YMYL, so every claim on every page has to survive E-E-A-T scrutiny and internal compliance review — you cannot scale by publishing fast and loose. The competitive set includes India's largest insurance aggregators, who outnumber any insurer's content team. And leadership wanted results reported in leads and revenue, not sessions — reviewed weekly by marketing leadership and quarterly by the CXO group.
What I did
- Programmatic landing pages with structured data as a first-class citizen: shipped 1,000+ templated landing pages, each carrying full JSON-LD (FAQPage, Article, MedicalCondition and related types) — schema built into the template, not bolted on after.
- Competitive term capture: put 500+ competitive commercial terms into Google India's top 10 within 90 days of the template launches, tracked in Ahrefs and Semrush.
- A production AI-search (AEO) program: restructured key pages into answer-shaped content, consolidated entity signals, and tracked citations across LLM answer engines with Profound, Peec AI, and Otterly.ai. AI citations grew 2.9K → 49.9K and cited pages 1.1K → 11.9K in six months.
- Agency command: I manage the retained SEO agency — scoping the roadmap, holding output to the same evidence standard as in-house work.
- Revenue-literate reporting: built the GA4 attribution view that ties organic leads to roughly $32K a month in attributed revenue, so the program is defended in finance's language.
Result
| Metric | Before | After |
|---|---|---|
| Organic users / month | 107K | 215K |
| GSC clicks / month | 50K | 150K |
| GSC impressions / month | 2M | 40M |
| Organic leads / month | 2,000 | 5,000 |
| Attributed revenue / month | — | ~$32K (GA4) |
| AI citations (6-month window) | 2.9K | 49.9K |
| AI-cited pages (6-month window) | 1.1K | 11.9K |
Source: GA4, Google Search Console, Profound. Each row is a report I can open live in an interview.
Note the ratio: leads grew 2.5× while users grew 2× — the growth was engineered toward converting queries, not raw traffic. That is the difference between an SEO program and an acquisition program.
What transfers to Berry Law
The problem class is identical to ranking a VA-disability appeal page: high stakes, low trust tolerance, brutal SERP competition, and a reader making a decision they're afraid to get wrong. The market is India; the constraint set — YMYL scrutiny, E-E-A-T, compliance review, programmatic scale with full structured data — is exactly what Google applies to legal content in the US. And the AEO program is the part almost no law-firm SEO candidate has run in production.
What I'd do differently
Instrument lead quality from day one, not month two. Lead volume grew faster than our qualification scoring matured, which cost the sales team triage time before we tightened the funnel definitions. At Berry Law I'd define the "qualified consult request" event — and its quality criteria — before scaling anything, which is why it appears in Phase 01 of the 90-day plan.