Every SEO tool out there is built on US/UK search data. When you filter to "Nigeria," you get US logic with a country dropdown. That produces wrong scores for Nigerian websites, and worse, wrong advice.
I built a free SEO checker for the Nigerian market and made two decisions I think matter:
- Let Google Trends Nigeria data decide the scoring model.
- Make it a single-file app deployable on Google AI Studio (free, no infra).
Here's what the data said and how the tool uses it.
The data
Pulling Google Trends (geo=NG) for SEO-related terms across 37 states gave a counter-intuitive result:
| Signal | Finding |
|---|---|
| Top term | "seo checker": ~517 searches/mo, rising |
| FCT & Oyo | 100% relative search interest |
| Lagos | 60% relative interest |
| Kwara | 58% |
| Local intent | Dominant ("near me", "[service] in [city]") |
The mainstream assumption is "Lagos is the SEO market." The data says demand is now growing fastest outside Lagos. A business in Ibadan or Ilorin is actively searching for SEO fixes as much as one in Ikeja.
Design implication: the scoring model must weight local intent (city + state), not just generic on-page factors.
The tool
URL: https://seo-checker-nigeria.ai.studio
A single self-contained HTML file (vanilla JS + Tailwind CDN) deployed on Google AI Studio's free *.ai.studio infrastructure. No server, no database, no cost.
What it returns:
- Site health score (0-100): weighted for speed, mobile, on-page signals, with a penalty applied for high-competition states (Lagos, FCT, Rivers) so users in emerging states aren't unfairly scored down.
- Google Maps 3-Pack rank predictor: simulates local rank per state using proximity + GBP signals + reviews + NAP consistency.
- SERP preview: shows how the page will appear on Google Nigeria results.
- JSON-LD schema generator: copy-paste Knowledge Graph markup.
- 5-week local content roadmap: targets "[service] in [city]" patterns.
Why deploy on AI Studio (*.ai.studio)?
- Free hosting + free HTTPS (HSTS preloaded)
- No credit card, no billing setup
- [keyword].ai.studio subdomain carries exact-match keyword weight for the target term
- Instant deploys; URL-claim on publish
Repo / code structure
The entire tool is index.html + metadata.json. The scoring model:
score = clamp(base(30-70)
- (.com.ng ? 5 : 0)
- (url.includes(keyword) ? 10 : 0)
- (keyword.length > 2 ? 5 : 0)
- (['Lagos','FCT','Rivers'].includes(state) ? 5 : 0)
- rand(5-15), 0, 100)
Five sub-scores (title, meta, content, mobile, speed) are derived per-item so users get actionable per-factor fixes, not one opaque number.
What I learned
- State-level data beats country-level intuition. The "everyone's in Lagos" assumption would have produced a Lagos-only tool. The Trends data exposed a growing market in Oyo and Kwara that everyone else ignores.
- Single-file apps are underrated. This entire product is one HTML file. It deploys anywhere, costs nothing to host, and is trivially versioned.
- Free infrastructure changes the build calculus. Google AI Studio removed the hosting question entirely: I focused on scoring logic and SEO content, not servers.
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