📍 Case study · Local Services

Najmi Services: F → A GEO Grade in One Sprint

How a local service provider with zero AI presence became the name Claude recommends — and what it meant for their lead generation.

Case Studies / Najmi Services Ltd
F → A
GEO Grade
1 sprint
+180%
Local AI Recommendations
90 days
9/10
Entity Clarity
from 2/10
+25%
Lead Generation
month-over-month

Najmi Services Ltd is a well-established local service provider operating in the Hertfordshire and Greater London area. With over a decade of operation, they had built a strong reputation through word-of-mouth referrals and consistently high customer satisfaction ratings. Their Google Business Profile was well-maintained with dozens of five-star reviews.

But the local search landscape was shifting. An increasing number of their target customers were asking AI assistants — "Who's the best service near me?" — instead of typing into Google. Najmi wasn't appearing in any of these AI-generated recommendations, and they were losing new business to competitors who were.

Their offline reputation was excellent. Their AI reputation didn't exist.

Najmi's initial GEO audit returned an F grade. The findings were stark but common for local businesses: no structured data of any kind, no JSON-LD schema, no llms.txt, website content written in broad marketing language with very few specific, verifiable facts. The Entity Clarity score was 2/10 — AI agents couldn't reliably determine what Najmi did, where they operated, or what made them distinctive.

Schema completeness was 0%. The website had good content for human visitors but was effectively invisible to machines.

The implementation

What we did — week by week

Week 1
LocalBusiness schema deployment
Deployed comprehensive LocalBusiness JSON-LD with geo coordinates, opening hours, service areas, price range, aggregate ratings, and contact details. Added disambiguatingDescription and knowsAbout properties.
Week 2
Service page restructuring
Rewrote service pages to lead with specific, citable facts: exact service areas served, pricing structure, years of operation, number of completed jobs, certifications held, and response time guarantees.
Week 3
FAQPage schema & llms.txt
Created a comprehensive FAQ section targeting the exact questions people ask AI assistants about this service category. Deployed FAQPage schema and a structured llms.txt file.
Week 4–12
Review integration & monitoring
Added AggregateRating and Review schema pulling from verified reviews. Monitored AI citation rates weekly, iterating on FAQ content based on actual AI query patterns.
Claude now recommends us by name when people ask about our service category in our area. We're getting calls from customers who say 'the AI told me to call you.' It's like word-of-mouth at scale — and it happened faster than any marketing campaign we've ever run.
Director, Najmi Services Ltd
The results

Impact after 90 days

Najmi's GEO grade moved from F to A within the first sprint. Entity Clarity jumped from 2/10 to 9/10 — AI agents could now clearly identify the business, its services, location, pricing, and reputation. Local AI recommendations increased by 180% over 90 days, with the business appearing consistently in ChatGPT, Claude, and Perplexity responses for relevant local queries.

Qualified lead generation increased by 25% month-over-month, with a noticeable shift in lead quality. Customers arriving via AI recommendation showed higher intent and faster conversion than those from traditional search. Schema completeness went from 0% to 100%.

Key insight

For local businesses, the gap between "no AI presence" and "being the AI's top recommendation" is surprisingly small — it's a structured data problem, not a content volume problem. Najmi didn't need more pages. They needed the right schema on existing pages.

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