A basic GEO engagement can begin with an audit of how a brand appears across AI platforms. Agencies test prompts based on the questions consumers are likely to ask, then examine whether the brand is mentioned, which sources are cited, how competitors appear and whether the information presented about the brand is accurate
How much would a brand pay to be mentioned by ChatGPT?
There is no standard answer yet. In India, the emerging GEO market is throwing up monthly spends ranging from Rs 1 lakh to as much as Rs 15 lakh, with agencies also testing 10-12 week pilots, one-off audits and low-cost tracking products.
Agencies are already charging for AI visibility audits, prompt-level tracking, content restructuring, entity optimisation, digital PR and ongoing monitoring. And the brands pay as per the scope of work.
But GEO comes with a problem that traditional search marketing did not face in quite the same way. Agencies can influence the information an AI model finds, the sources it cites and how clearly a brand is represented. But they cannot tell an AI model what answer to give tomorrow.
And even when a brand does appear, proving that the visibility translated into a sale is still difficult.
And if AI platforms themselves are getting better at measuring how brands appear in their answers, how much of this work will continue to sit with specialist GEO agencies?
What exactly are brands paying for?
For now, the answer depends on how far a brand wants to go.
A basic GEO engagement can begin with an audit of how a brand appears across AI platforms.
Agencies test prompts based on the questions consumers are likely to ask, then examine whether the brand is mentioned, which sources are cited, how competitors appear and whether the information presented about the brand is accurate.
The next layer is optimisation.
That can involve restructuring website content, cleaning up brand and product entities, improving structured data, and building credible third-party citations.
The third layer is ongoing monitoring.
This is also why GEO pricing is difficult to compare across agencies. One agency may primarily sell a tracking product, another may bundle SEO and content work, while another may include digital PR and ongoing measurement.
Sini Magon, COO and Global Partner, Grapes Worldwide, said brands typically start with a 10-12 week pilot covering an audit and initial optimisation. Such projects in India can cost Rs 3 lakh-Rs 10 lakh.
For continuing engagements, the range can be around Rs 1 lakh-Rs 2 lakh a month for mid-sized brands and Rs 4 lakh-Rs 5 lakh for larger enterprises. Globally, comparable retainers can reach $8,000 to $20,000 a month.
Pankaj Srivastava, Founder and CEO, UnoSearch, puts the starting point lower for audits and strategy, at around Rs 1 lakh-Rs 5 lakh. Enterprise retainers, depending on the number of AI platforms monitored, content scale, digital PR requirements and industry complexity, can range from Rs 3 lakh to Rs 15 lakh a month.
GEO is still largely being sold as an extension of existing digital marketing mandates rather than as a mature standalone budget category.
Rajiv Dhingra, Founder and CEO, ReBid, said most brands are either working with their existing SEO partners on GEO or asking their current digital agencies to add it to the mandate.
“The GEO mandate typically has three parts: tracking, how to get more visibility, and then the service layer, which varies by category, business and exposure,” he said. That service layer is where pricing starts to diverge.
The difference in pricing reflects how early the market is. There is no standard GEO scope yet, and agencies are effectively packaging different combinations of consulting, technology, content and monitoring under the same label.
In search, agencies work within a system where there is at least a visible relationship between a query, a ranking and a link. AI answers work differently.
Agencies can change the information available about a brand. They can improve content, entities, structured data and third-party authority. They can monitor thousands of prompts. But they cannot control the model generating the answer.
“You cannot control how much activity ranks in AI answers. You cannot optimise for it. GEO cannot solve it,” Dhingra said.
The problem is that AI platforms can change how they interpret information or which sources they rely on without an agency making any corresponding change.
Dhingra cited an 86% drop in ChatGPT citations from Reddit as an example of how quickly the information ecosystem can change. That creates a commercial problem for agencies. A brand may have done everything recommended by its GEO partner and still see its AI visibility change because the underlying model has changed.
Magon said agencies therefore have to be careful about what they promise. “The base retainer exists because no agency can guarantee what the AI model generates,” she said. Therefore, agencies need to focus on visibility, citations and representation rather than promising a fixed AI response.
An agency can work towards making a brand more visible to AI systems, but it cannot sell ownership of the final answer. Srivastava said this is why GEO needs capabilities that go beyond conventional SEO and paid media.
“AI discovery needs capabilities beyond conventional SEO/paid media: LLM understanding, prompt analysis, entity management, structured data, content authority, continuous response monitoring,” he said.
This is where GEO gets particularly interesting for marketers. The visibility itself can be tracked.
Agencies can run hundreds or thousands of prompts across AI platforms and record how often a brand appears, which sources are cited, what competitors are being mentioned and how the response changes over time.
But tracking visibility is different from proving commercial impact.
Magon breaks measurement into three levels. The first is visibility – share of AI voice, prompt coverage and representation accuracy.
The second is demand – AI referral sessions, branded search lift and new-to-site visitors.
The third is business impact – assisted conversions and what she calls “share of model”, or the weight a brand carries in what AI systems retrieve and say.
The difficulty comes from what happens after the AI answer.
A consumer can ask an AI assistant for a recommendation, read the answer and then leave. That person might later search for the brand on Google, visit its website directly or buy through another channel.
The eventual conversion may therefore look like a conventional organic, paid or direct conversion even though AI influenced the consumer much earlier.
Dhingra said this is one of the biggest differences between traditional search and AI discovery.
“With search, there is a direct click and a trail to the site. In AI, a person can take the answer, make a decision and search later,” he said.
This creates a measurement paradox. AI visibility is relatively easy to count but much harder to value in revenue terms.
According to Srivastava, the industry will eventually have to connect AI visibility with commercial metrics. “The next stage connects AI visibility to leads/revenue/CAC,” he said.
The scale of that opportunity could be substantial if AI becomes a regular part of consumer research. Srivastava cited a Google study that found 93% of Indian automobile buyers use AI experiences during their research. He expects similar behaviour to emerge across categories such as healthcare, finance, travel and consumer products.
For marketers, that makes the question less about whether a brand appeared in an answer and more about whether being there changed consideration, demand or conversion.
The industry is still some distance from answering that conclusively.
What happens to GEO agencies if their services become a commodity?
As AI platforms improve their own measurement and more tools enter the market, some of the services agencies are charging for today could become standard, cheaper and easier for brands to access directly.
Google has already introduced AI Overview mentions tracking in GA4, making at least part of AI visibility measurable within a platform marketers already use. Other GenAI platforms are expected to follow suite.
Dhingra said the tracking layer is already moving in that direction. There are hundreds of tools tracking AI answers across AI Overviews, Gemini, ChatGPT, Perplexity and Claude, while Google has brought AI Overview mentions into GA4.
That adds another pressure layer. What happens to the agencies if their moat becomes a commodity?
If a brand can buy a tool, run its own prompts and see where it appears across AI platforms, simply reporting AI visibility may become a difficult service to defend at a premium.
Magon believes the answer will lie in the layer between measurement and execution. She said specialists currently have an advantage because GEO requires a combination of capabilities that may not sit together within a traditional agency, including digital PR, content engineering, structured data and data science.
But even that advantage may narrow as larger agencies build the capabilities internally.
Does GEO have a shorter shelf life than the business it is creating?
The irony is that agencies may build a sizable business around GEO without GEO itself becoming a permanent agency category.
Magon expects specialist GEO capabilities to remain relevant for the next three to five years, but believes the label could have a shorter shelf life of two to three years. The fee premium attached specifically to GEO could eventually disappear as the work becomes standard.
Srivastava expects the category to follow a pattern seen across digital marketing, where a new capability first creates specialist agencies before being absorbed into larger agency offerings.
“GEO is likely to follow the path of performance marketing, analytics and social media: specialised first, core capability later,” he said.
That could leave GEO agencies facing a familiar agency-industry problem: building a business around a capability that they ultimately help make mainstream. The opportunity, therefore, may not be in owning the GEO label.
It may be in owning the data, intelligence and systems that help brands understand how AI platforms discover, represent and recommend them.
What may survive is the specialist measurement and model-intelligence layer, much like SEO tools continued to exist even as SEO became a standard capability across digital agencies.
For specialist GEO firms, this makes speed and depth of expertise important in the near term, while longer-term survival could depend on whether they can build proprietary measurement, model intelligence or optimisation systems that are difficult to replicate.
Dhingra is more cautious about the standalone agency opportunity in India. He does not see enough spending today to support 100-200-person GEO-only agencies. A smaller specialist business may survive, but he expects much of the work to sit within broader digital marketing relationships.
Dhingra sees “agentic media optimisation” as a potentially larger opportunity, as agencies begin using AI agents to automate and optimise parts of paid-media planning and execution.
That could eventually make the current GEO conversation look like an early step in a much larger change in how brands are discovered and marketed to.
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First Published on October 1, 2026, 08:55:00 IST
