GEO is a reputation problem, not a page problem
Traditional SEO is something you do to your website. GEO is mostly something you do everywhere else. When a model is asked to recommend a business, it is not ranking pages. It is summarising what the internet appears to agree on. Your own site is one voice in that, and the least trusted one, because every business says it is the best.
What moves the answer is consensus: several independent sources describing you the same way. A directory listing, a comparison article, a forum thread, a review platform, a news mention. When four unrelated places say you are an SEO agency in Hafizabad, the model states it as fact. When only your homepage says it, the model has nothing to repeat.
The short version
Be described consistently on many independent sites. Get into the listicles and comparisons people ask about. Have reviews on platforms models read. Be specific about what you do and who you do it for, so you fit a narrow question rather than a broad one. Then test the actual prompts, monthly.
GEO or AI SEO? They overlap. AI SEO is the broader programme, making your site readable and quotable across every AI surface. GEO is the sharper end of it: being named when someone asks for a recommendation, which is decided mostly by third-party signals. Most clients take AI SEO and GEO together; taken alone, GEO suits businesses whose site is already in good shape.
How a model decides who to name
Nobody outside these companies has the exact recipe. But the patterns are consistent enough across systems to work from, and they are what we build against.
Consensus across independent sources
STRONGESTSeveral unrelated sites describing you the same way. One source is a claim; four agreeing is a fact the model will state confidently. This is why GEO is mostly off-site work.
Specificity of the association
MOST WINNABLEBeing tied to a narrow thing, a platform, a city, a customer type, rather than a broad category. Models recommend confidently when the match is precise and hedge when it is vague.
Reviews and ratings volume
HIGH WEIGHTReal reviews on platforms these systems read, with enough volume and recency to look like an operating business rather than a website.
Presence in comparison content
DIRECT ROUTEListicles, roundups and directory pages are exactly the format a recommendation question is answered from. Absence from all of them usually explains absence from the answer.
Clarity of the entity itself
FOUNDATIONOne name, one description, one address, one set of facts everywhere. Contradictory data leaves the model unsure you are a single business, and unsure businesses do not get named.
What the work covers
Win the narrow question first
"Best digital marketing agency in Pakistan" has hundreds of contenders and decades of established coverage behind them. "Shopify SEO agency for COD stores in Punjab" has almost none. The narrow question is winnable now, and the customers asking it are closer to buying than the ones asking the broad one.
Hard to win
Broad category questions with national or global scope. Established players dominate the sources models read, and shifting that takes years of coverage rather than months of work.
Winnable now
Service plus city, service plus platform, service plus customer type, service plus constraint. Fewer competitors, thinner existing coverage, and buyers with a clear brief.
Getting into the lists models read
A large share of recommendation answers is assembled from "best X in Y" articles, directories and comparison pages. If you are absent from all of them, you are absent from the answer regardless of how good your site is. This is unglamorous work and it is the highest-leverage part of GEO.
Sector directories
Industry-specific listings carry more weight for recommendations than general business directories, and often send direct traffic too.
Local and national listings
Pakistani business indexes and city directories, which is where local recommendation answers frequently source their names.
Roundup articles
"Best X in Y" pieces on blogs and publications. Getting included is outreach work: a real pitch with real credentials to a real editor.
Review platforms
Google, Facebook and any platform standard in your sector. These are read heavily and are the fastest signal to build honestly.
Community threads
Reddit, Quora and Facebook groups get cited surprisingly often. Genuine participation only, planted posts are obvious and counterproductive.
Partner and supplier pages
Client lists, partner directories and supplier pages on other companies' sites. Easy to arrange, and carry real third-party weight.
Everything here is earned or openly paid-and-disclosed. We do not fabricate reviews, plant fake forum posts or buy links from networks. Those get detected, and the cleanup costs more than the work was worth.
How this gets measured
Named or not
For each question in the set: are you mentioned, at what position in the list, and described how. The core number.
Share of voice
How often you appear against each named competitor across the whole question set, tracked month to month.
Cited sources
Which pages the answers draw from. This tells us exactly where to place next, rather than guessing.
Description accuracy
When you are named, is what the model says about you correct. Wrong facts are traceable to a wrong source.
Assistant referrals
Visits from chatgpt.com, perplexity.ai and similar. Low volume, unusually high intent. These people arrived pre-recommended.
Brand searches
People searching your name directly, which is often where an assistant recommendation first becomes visible in your own analytics.
One caveat worth stating: these systems are not deterministic. The same question can produce slightly different answers to different people on different days. We test a fixed question set repeatedly and read the trend, not any single result.
How the engagement runs
Honest timelines
GEO is slower than technical SEO and less predictable than local SEO, because you are waiting on third parties to publish and on models to absorb it. The narrow questions move first.
Who this is for
Worth doing
Businesses people ask for recommendations about, agencies, clinics, law and accounting firms, software houses, schools and institutes, contractors, B2B suppliers. Anything where the buyer asks around before choosing.
Not yet
Brand new businesses with no track record, no reviews and no coverage. GEO amplifies a reputation; it cannot manufacture one. Build the delivery record and the reviews first, then this work has something to spread.
Questions we get asked
How is GEO different from AI SEO?
AI SEO is the whole programme: making your site crawlable, quotable and structured for every AI surface. GEO is the sharp end, being named when someone asks for a recommendation, which is decided mostly by third-party sources rather than your own pages. Most clients do both; GEO alone suits businesses whose website is already in good shape.
Can you pay to be included in AI answers?
There is no ad slot to buy inside these answers today. What you can pay for is placement in the sources they read, sponsored directory listings, disclosed paid inclusion in some roundups. We use those where they are legitimate and disclosed, and we tell you which is which.
ChatGPT says something wrong about our business. Can that be fixed?
Usually, but indirectly. The model repeats what it read, so the fix is finding and correcting the sources, an outdated directory entry, an old article, a wrong Business Profile. We trace where it came from and correct it there. Expect weeks to months for the change to propagate.
Do you write fake reviews or forum posts?
No. Review platforms detect fabricated reviews and strip every review you have, genuine ones included. Planted forum posts get removed and damage the reputation you are trying to build. Everything we do here is earned or openly disclosed.
We are a new business. Should we start with this?
Not first. GEO amplifies a reputation that exists. It cannot create one from nothing. Build delivery history, collect genuine reviews, get the local and technical SEO right, and then this work has real material to spread.
Why do we get different answers on different days?
These systems are probabilistic, and answers vary by phrasing, account history and region. That is why we test a fixed question set repeatedly and read the trend rather than reacting to any single result.
Does this work for Urdu or mixed-language questions?
Increasingly, though English still dominates in these systems for Pakistani queries. We test both where it makes sense for your market, and the underlying work, consistent entity data and third-party coverage, helps in either language.
What does it cost?
It depends on how many questions you want to compete on and how much placement work is needed. The baseline mention check is free and comes with a scoped quote, so you can see where you stand before deciding.
See who gets named instead of you
Tell us the recommendation questions your customers would ask. We run them through ChatGPT, Gemini and Perplexity and send you the answers, which businesses get named, which sources they came from, and where the gap is. No charge.
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Related topics
Guides on generative engine optimisation from our team
AEO and GEO: How to Get Cited by ChatGPT and AI Overviews
Answer engine optimisation explained, what AEO and GEO are, how AI search picks sources, and the page structure that gets you quoted.
GuideChatGPT SEO: How to Get Your Business Mentioned
How ChatGPT decides which businesses to name, and the seven things that make yours one of them. Written from testing against live accounts, not speculation.
GuideHow to Appear in Perplexity and AI Overviews
Perplexity and AI Overviews pick sources differently from ChatGPT and from each other. What each one rewards, and how to be cited by both.