Hulm Solutions: Ranking on Google, Google AI Overview, ChatGPT and the Local Map
Client: Hulm Solutions (POS & business suite, Pakistan) Scope: Technical SEO + AEO + GEO + Local SEO
The Problem and Fix
The Problem in One Line
Hulm’s page was indexed but invisible, with 40–80 impressions/day, buried past page one, written in feature-speak (“inventory module”) instead of buyer-speak (“POS software Pakistan”). Good product, wrong language for both Google and AI models.
The Fix: Three Engines, One Page
SEO (get found): Killed layout shift and load-time drag, then rewrote headers/meta around actual buyer queries instead of internal feature names. Crawlers re-score UX before they re-score copy fix the pipes first.
AEO (get answered): Rewrote every FAQ so the answer lands in sentence one, backed by a hard fact in sentence two: “Hulm costs PKR 2,500/month, FBR-compliant, 14-day trial” not “affordable and reliable.” Models extract facts. They discard adjectives.
GEO (get cited): Turned the competitor comparison into a labeled table (entity → attribute → value), because that structure is what a generative model lifts cleanly into an answer. A paragraph gets summarized. A table gets quoted.
Google Search Console 3-Month Result
8.78K
Total Organic Impressions (with a 2x visibility surge in April)
6.7
Average SERP Position (Solidly established on Page 1)
344
High-Intent Organic Clicks
3.9%
Average Click-Through Rate (CTR)
Showing Up Beyond the Blue Link
Google AI Overview:
When someone asks “best POS software in Pakistan,” the answer Google surfaces comes straight from structured, fact-first content same FAQ schema, same direct-answer pattern. This is where AEO pays off in a channel traditional SEO tools don’t even measure yet.
ChatGPT / Perplexity / Gemini prompt ranking
GEO isn’t a ranking position it’s a citation. Track it by literally prompting the models with buyer questions (“I want to know which pos software is best in Pakistan?”) and screenshotting whether Hulm gets named, and why (usually: it’s the only source with the specific number the model needed).
Local SEO Winning the Map, Not Just the Web
For a Pakistan-based SME product, Google Business Profile ranking often converts harder than organic — it’s what shows up when someone searches “POS software near me” or “best POS Karachi/Lahore.” The levers that move it:
- Review velocity + response rate: Hulm’s 4.9★ Google rating is a ranking signal, not just trust signal; respond to every review, keep it recent.
- Category + service area precision:Â “Point of Sale System Provider” as primary category, service areas mapped to actual client cities, not just “Pakistan.”
- NAP consistency: same name/address/phone across GMB, site footer, and directories; mismatches quietly cap local ranking.
- Geo-modified content: city-specific proof (client logos, testimonials by city) feeds both GMB relevance and the “near me” query cluster.
Expert Takeaways
- Fix Core Web Vitals before content; a slow page discounts every word you write.
- FAQ schema is your cheapest ticket into both featured snippets and AI Overviews.
- Replace adjectives with numbers everywhere; that’s what gets extracted and cited.
- Tables beat paragraphs for GEO. Always.
- Track the floor (baseline lift), not the peak; that’s what proves the fix was structural.
- Local ranking runs on reviews + category precision, not just backlinks.