Verified outcomes from real engagements.
Every number on this page is source-linked — GA4 screenshot, UTM log, client dashboard, or third-party verification. No vanity metrics. No “we helped a client” without receipts. Published by Md Hafizur Rashid, AI Search Visibility expert, across 1,000+ projects since 2011.
An integrity note before the numbers: One case study below is fully published with source-linked metrics. The other three are in progress — we've published them early to document the method and the baseline, and we show [METRIC TO VERIFY] where we're waiting on client data. We don't invent numbers. If a metric isn't verified, it isn't published.
The challenge
Elite Business Insurance, an independent commercial insurance agency in Tampa, FL, was invisible to AI engines. When buyers in their metro market asked ChatGPT, Gemini, Perplexity or Claude for “commercial insurance Tampa”, the AI cited aggregators and national carriers — never Elite.
The site had accumulated technical debt over a decade of patches. PageSpeed was 48. Schema markup was incomplete. There was no coherent entity definition anywhere on the web.
What we did (EVF steps 01–05)
- Step 01 · Entity Definition: Defined Elite as a coherent entity — name, category, Tampa metro, independent agency positioning — and published the Entity Brief across owned and third-party properties.
- Step 02 · Technical Foundation: Rebuilt the site on a clean WordPress stack. PageSpeed 48 → 96. Deployed Organization, LocalBusiness, InsuranceAgency, Service and FAQ schema.
- Step 03 · Content Engineering: Published 42 citation-ready pages targeting Tampa-specific buyer-intent queries. Each engineered for direct AI citation.
- Step 04 · Citation Building: Built third-party citations — industry directories, Tampa business associations, press mentions — with entity-consistent messaging.
- Step 05 · Measurement: Baseline APR recorded. Monthly repeated-prompt sampling across 4 LLMs. UTM-tracked AI-source leads in GA4.
The results
| Metric | Before | After | Δ |
|---|---|---|---|
| Organic traffic | Baseline | +761% | 90 days |
| Page 1 keywords | — | 86 | Tampa commercial insurance |
| PageSpeed (mobile) | 48 | 96 | +48 points |
| AI citation position | Not cited | #1 | 4 LLMs · Tampa queries |
| ChatGPT-attributed leads | 0 | 29 | Q2 · UTM-verified |
“We went from invisible to the first name ChatGPT recommends for commercial insurance in Tampa. The leads coming through now actually know who we are before they call.”— Founder, Elite Business Insurance, LLC · [Full attribution under NDA]
The challenge
Yafa Care is an Australian registered NDIS provider offering support coordination, therapy and plan management. Like most NDIS providers, they competed for participant and referrer citations in a market where AI engines were beginning to replace Google for “NDIS provider near me” queries.
The site had minimal schema markup, no coherent entity definition, and was not cited by any major AI engine for category queries.
What we're doing (EVF in progress)
- Step 01 · Entity Definition: Completed. Defined Yafa Care as an NDIS entity — services, geography, registration status, referrer network.
- Step 02 · Technical Foundation: In progress. Schema deployment (NDISService, LocalBusiness, MedicalOrganization) underway.
- Step 03 · Content Engineering: Queued. Citation-ready content for participant-intent and referrer-intent queries mapped.
- Step 04 · Citation Building: Queued. NDIS directory, industry association and referrer-network citations planned.
- Step 05 · Measurement: Baseline APR recorded. Monthly sampling scheduled.
Metrics (pending verification)
| Metric | Status | Target |
|---|---|---|
| Referral volume | [METRIC TO VERIFY] | Month 6 |
| Page 1 keywords | [METRIC TO VERIFY] | Month 6 |
| AI citation frequency | [METRIC TO VERIFY] | Month 3 |
| Participant inquiries | [METRIC TO VERIFY] | Month 6 |
The challenge
ICG Medical is a US-based healthcare staffing agency competing for both qualified applicant traffic and client-side (hospital/clinic) citations. In a market where AI engines increasingly answer “best healthcare staffing agency for X” queries, ICG needed to become the named recommendation — not one of five anonymous options.
What we're doing (EVF in progress)
- Step 01 · Entity Definition: Completed. Defined ICG Medical as a healthcare staffing entity — specializations, geography, client profile.
- Step 02 · Technical Foundation: Completed. Schema deployment (EmploymentAgency, Organization, Service). PageSpeed improvements documented.
- Step 03 · Content Engineering: In progress. Applicant-intent and client-intent content mapped and being published.
- Step 04 · Citation Building: In progress. Industry association, press and directory citations underway.
- Step 05 · Measurement: Baseline APR recorded. Monthly sampling scheduled.
Metrics (pending verification)
| Metric | Status | Target |
|---|---|---|
| Qualified applicant volume | [METRIC TO VERIFY] | Month 6 |
| Cost-per-hire | [METRIC TO VERIFY] | Month 6 |
| AI citation frequency | [METRIC TO VERIFY] | Month 3 |
| Client-side inquiries | [METRIC TO VERIFY] | Month 6 |
The challenge
Hotell Strand is an independent hotel in Sweden competing against OTA giants (Booking.com, Expedia) for direct bookings. As travelers increasingly ask AI engines “best hotel in [location] for [use case]”, Hotell Strand needed to become the named recommendation — not a listing buried in an aggregator.
What we're doing (EVF in progress)
- Step 01 · Entity Definition: Completed. Defined Hotell Strand as a hospitality entity — location, positioning, guest profile, differentiators.
- Step 02 · Technical Foundation: Completed. LodgingBusiness, Hotel, LocalBusiness schema deployed. PageSpeed improvements documented.
- Step 03 · Content Engineering: In progress. Traveler-intent content mapped (use-case-based queries: “best hotel in X for Y”).
- Step 04 · Citation Building: In progress. Travel directory, press and review-platform citations underway.
- Step 05 · Measurement: Baseline APR recorded. Monthly sampling scheduled. PMS integration for direct-booking tracking in planning.
Metrics (pending verification)
| Metric | Status | Target |
|---|---|---|
| Direct booking share | [METRIC TO VERIFY] | Month 6 |
| OTA commission saved | [METRIC TO VERIFY] | Month 6 |
| AI citation frequency | [METRIC TO VERIFY] | Month 3 |
| Organic traffic | [METRIC TO VERIFY] | Month 6 |
Every number. Source-linked.
We don't publish numbers we can't verify. Every metric on this page comes from one of five sources — and we'll show you the receipt on request (under NDA where client data is involved).
If a case study shows [METRIC TO VERIFY], it means the engagement is in progress and we're waiting on client-side data. We don't invent numbers. We don't estimate. We don't round up.
This is the opposite of how most agencies publish case studies. It's slower. It's more honest. It's the only way we know how to work.
GA4 + UTM tracking
Every AI-source visit is tagged with a UTM parameter. Leads are tracked through the full funnel — visit → form → booked call → client. No guessing.
Repeated-prompt sampling (APR)
The same buyer-intent prompt, run across ChatGPT, Gemini, Perplexity and Claude, every month. We record whether your brand is cited, in which position, with what context.
Google Search Console
Keyword rankings, impressions, clicks, CTR — all verifiable, all exportable, all source-linked in every report.
PageSpeed Insights
Mobile and desktop Core Web Vitals — LCP, CLS, INP — measured before, during and after every technical engagement.
Client dashboards (where shared)
ATS, PMS, CRM — only used when the client provides access and consent. Never inferred, never estimated.
Four verticals. Deep work.
Commercial Insurance
Independent agencies and MGAs competing against aggregators and national carriers — especially in mid-size metro markets.
NDIS & Allied Health
Australian registered providers — support coordination, therapy, plan management — competing for participant and referrer citations.
Healthcare Staffing
Staffing agencies competing for both qualified applicant traffic and client-side (hospital/clinic) citations in a two-sided market.
Hospitality
Independent hotels competing against OTA giants for direct bookings — especially when travelers ask AI engines “best hotel in X for Y”.
Questions about the results.
No single result is “typical” — every engagement has a different starting point, category competitiveness and timeline. The Elite Business Insurance case (+761% in 90 days) is one of our strongest published outcomes. Other engagements move slower, especially in competitive national categories. What's consistent is the method: baseline APR, documented EVF execution, monthly measurement. We publish what we can verify — not what sounds best.
Because we don't invent numbers. When a case study shows [METRIC TO VERIFY], it means the engagement is in progress and we're waiting on client-side data — usually from an ATS, PMS, or CRM the client controls. We publish the case study early to document the method and the baseline; we update the metrics when the client verifies them. This is the opposite of how most agencies publish case studies.
Yes — under NDA. During a strategy call, we can walk you through the GA4 reports, UTM logs, APR sampling spreadsheets and PageSpeed Insights records behind any published case study. We don't show client-identifiable data without consent, but the method and the numbers are open for verification.
No. No ethical SEO or AI visibility provider can guarantee specific results — Google and LLMs change their algorithms continuously, and every business has a different starting point, category competitiveness and timeline. What we can guarantee is a measurable, verifiable process: baseline audit, documented EVF execution, and monthly reporting on AI Prompt Rate, PageSpeed, and conversion. Every claim in our case studies is source-linked.
Most engagements begin showing AI citations within 60 to 90 days, depending on the starting authority of the domain, the competitiveness of the category, and how quickly entity signals are deployed. Local service businesses in less competitive niches (like the Elite Business Insurance case) often see results sooner; national professional services typically take longer. The full EVF cycle runs 6–12 months.
We have published case studies in commercial insurance (US), NDIS/allied health (Australia), healthcare staffing (US) and hospitality (Sweden). If your industry isn't listed, book a strategy call — we may have unpublished work in your category, or we can tell you honestly whether we're the right fit. We don't take engagements outside our depth.
Your case study, next
Want results like these?
30 minutes. Free. We audit your current AI visibility, map your entity gaps, and tell you honestly whether EVF can produce similar outcomes for your business — no obligation.