It seems like GEO comes up in every marketing team meeting these days. I get that we need to get our brand mentioned on ChatGPT or Perplexity, but when someone asks, “So how do we know if it’s actually working?” it’s hard to give a straight answer.
Looking at search data, it’s clear that we’re not the only ones grappling with this issue. The monthly search volume for the keyword “GEO” in South Korea increased by approximately 189%, from 5,570 in January 2024 to 16,110 in January 2026 (Source: ListeningMind), and searches for “GEO marketing” first appeared in June 2025, growing to 910 monthly searches in just six months. This means many marketers are currently typing similar questions into search engines.
If you're just getting started with GEO, check out the article below!
GEO Optimization Basics Guide: Essential SEO/GEO Glossary for B2B Marketing
So, starting early this year, the Elephant team began actively exploring tools that could quantitatively measure visibility in terms ofmentions and citations related to AI. We searched for AI tools, reached out to providers directly, and even tested some beta versions. I wrote this post to honestly share what our team learned and experienced throughout that process.
Just to be clear, this post isn’t the definitive answer. The GEO measurement market itself is still quite volatile, and we’re still learning as we go. I’ve put this together in the hope that it might be of some help to marketers who are facing similar challenges.
Data for GEO performance should be analyzed in three categories
As I began exploring tools, the first thing I had to figure out was exactly what I wanted to measure when it came to “GEO performance.” As I looked into it, I realized that the tools currently available on the market actually use different metrics and criteria.
Just as traditional SEO has utilized various tools to analyze the funnelof “keyword search volume (demand) → search result visibility → clicks (traffic),”GEO (Generative AI Optimization) appears to be evolving in a similar direction.
The current tool market is evolving by leveraging its own data and expertise to predict and capture this new funnel, which follows the pathof "prompt demand → AI response exposure → website traffic."
Explore data for GEO performance across these three layers.
Step 1. Prompt Demand: What are people asking AI?
Just as keyword volume data serves as the starting point for content strategy in SEO, in GEO, the actual questions people ask AI form the foundation of our strategy.
However, AI prompts differ fundamentally from traditional keywords in terms of structure. Rather than short keywords like “GEO marketing tool,” they often consist of long, natural-language questions such as “I’m a B2B SaaS marketer—how do I measure the effectiveness of implementing GEO?” Even when the intent is the same, the way it’s expressed can vary widely. This is why traditional search volume data doesn’t correspond one-to-one with AI prompts.
If you don’t fully understand this step, you’ll end up setting the prompts to be measured in Step 2 based on guesswork. Since there’s no point in measuring SOV for questions that actual users don’t ask, this step—where we first define which prompts should include mentions of our brand—serves as the foundation of the GEO strategy. Tools capable of measuring this stage with data are only just beginning to emerge globally, and there are currently no tools available that cover domestic Korean data.
Step 2. Exposure Share: How often are AI responses cited?
This is the area that most GEO tools currently measure. It involves repeatedly running specific prompts through an AI to crawl the responses and then tallying how many times our brand is mentioned.
There’s an important distinction here. SOV is a supply-side metric that measures how often AI mentions us when generating answers. This metric alone doesn’t tell us whether actual users saw the answer or clicked the link. “The AI mentioned us” is not the same as “a person visited our site through that answer.”
Therefore, by considering not only the number of mentions but also qualitative aspects of SOV—such as the order in which they appear in responses, whether the context is positive or negative, and how they compare to competitors—you can gain a more comprehensive understanding of the current situation.
Step 3. Inbound Traffic: So, did they actually visit the website?
This step is based on user behavior. It checks whether a person actually clicked the link and visited the site when the AI referenced it.
There are two main methods of measurement. One is the estimated data method, which allows for comparisons with competitors; while this is useful for understanding the competitive landscape, it is based on estimates rather than actual figures, so it is best suited for identifying relative trends compared to competitors rather than absolute values.
Another method involves using analytics tools installed directly on your own website, which allows you to view actual traffic figures rather than estimates. However, this approach has the limitation that you can only view your own data. You can read about the Elephant Team’s specific method for measuring AI traffic using GA4 in this article.
These three metrics don’t always point in the same direction. If your SOV is high but AI traffic is low, it means that while AI is citing you, the links are missing or your position in the results is too low to drive clicks. Conversely, if you have AI traffic but a low SOV, it could mean you’re being quietly cited in long-tail queries. That gap itselfprovides strategic insight.
With the introduction of GEO services, Global has already set the standard.
Before exploring domestic services, I first looked into the criteria used overseas to evaluate GEO tools. As explained earlier, among the three stages, the area where the majority of tools currently compete in the market is Stage 2: AI Share of Voice (SOV) measurement. The six evaluation criteria that repeatedly appear inglobal researchprimarily address the factors to consider when comparing services at this stage.
- LLM Model Coverage: How many models do you track, such as ChatGPT, Gemini, and Perplexity?
- Key visibility metrics: Share of Voice, number of mentions, citation frequency, and sentiment analysis—which ones should you measure?
- Competitor Analysis: Can we compare AI mentions across competing brands?
- Depth of Data Processing and Analysis: Is it merely data collection, or does it provide insights?
- Action Orientation: Does It End with Measurement, or Does It Lead to Content Improvement?
- Usability and Target Audience: Who Is This Tool For?
However, there is one issue that domestic companies need to consider. Tools that offer global servicesoften lack data from the domestic market. Tools that are gaining recognition in overseas markets either do not currently support Korea or collect data primarily through English-language prompts.
In Korea, AI response data based on Korean prompts is crucial; however, since most global tools collect data primarily in English, it is difficult to accurately gauge the actual AI visibility of domestic brands. Furthermore, we determined that specialized measurement tools tailored to the Korean market are necessary to reflect the unique search patterns of Korean users, which differ from those of global audiences.
How can domestic companies find GEO services?
Since Elephant Company began its full-scale research on GEO tools in January 2026, we’ve compiled a list of over 10 services. As we explored them, we realized that each service was quite different in nature, and that even the category of “GEO performance measurement” itself is still defined in various ways.
Our team is currently focusing on the secondof three stages : AI impression measurement tools. We’re tracking AI traffic (Stage 3) directly through GA4, and as for prompt demand (Stage 1), there are currently no tools that adequately cover domestic data. Therefore, we’re starting by examining Stage 2 services, where the most tools are competing and where discrepancies in domestic data accuracy are most pronounced.
When you look at which of the three stages each tool covers, their nature becomes much clearer.
GEO Performance Measurement Tool: The Two Criteria That Led the Elephant Team to Decide on a Paid Subscription
First, can you view the raw data from the prompt responses directly?
The GEO measurement market is still in its early stages. No service has reached the point where it can claim, “This is the industry standard.” This means that rather than simply trusting the numbers provided by the tools, you need to be able to interpret and evaluate what lies behind those numbers yourself.
So, what the Elephant Company team looked at wasn’t the aggregated data, but the raw data behind it. We need to be able to verify firsthand how the AI responded to specific prompts and which URLs it cited in order to interpret the results according to our own criteria. Rather than focusing on a figure like “our brand’s SOV is 35%,” we prioritized a service that allowed us to see which prompts generated that number and what the actual response text looked like.
Second, do you transparently disclose your relationships of trust with clients?
GEO is an area where results aren’t immediately visible. That’s why I believed it was important to offer a service that transparently shares specific results alongside the names of actual clients. As you can see in the table below, only a few domestic services actually disclosed client names on their websites or blogs.
The domestic services that met both of these criteria were OnTheAI and BlueDot, and we also included Ahrefs—which we were already using—as a point of comparison on a global scale.
[Comparison Table of Domestic and International GEO Services]
| Services | Domain | Measurement phase | Key Indicators | Plan |
|---|---|---|---|---|
| Ahrefs | ahrefs.com | Step 2: AI Visibility (SOV) | Brand mentions, referring domains, AI traffic | Lite $129/month and up |
| Semrush | semrush.com | Phase 2 + Phase 3: AI Exposure + AI Traffic | SOV, Mentions, Citation Rate, AI Traffic | Pro $139.95/month and up |
| Profound | tryprofound.com | Phase 1 + Phase 2: Prompt Demand + AI Exposure | Prompt Volume, AI SOV, Mention Frequency | Starter $99/month and up |
| On the AI | onthe.ai | Stages 1, 2, and 3 combined | SOV, Citation Share, Query Fan-out, AI Traffic | Pro: Starting at 500,000 won/month |
| Blue Dot Intelligence | bi.bluedot.so | Step 2: Precise Measurement of AI Share of Voice (SOV) | BII, Citation Rate, Frequency, Location, and Sentiment Visibility | Starter Plan: Starting at 490,000 won/month |
| Chain Shift | trychainshift.ai | Phase 1+2: Prompt Demand + AI Share of Voice (SOV) | AI visibility, citation rate, query volume, query fanout, brand risk score, website GEO score | Starter $89/month and up |
| OPT GEO | optigeo.kr | Step 2: AI Visibility (SOV) | GEO Score (Citations + Brand) | Inquiry-based |
| A-Nect | ainnect.co.kr | Step 2: AI Visibility (SOV) | SoA, Citation Rate, AVI | Inquiry-based |
| Prompt Architect | promptarchitect.app | Step 1: Prompt Requirement | Query volume, query volume by model | Inquiry-based |
| GPTO | gpto.kr | Step 2: AI Visibility (SOV) | Brand Recommendation Rankings, Exposure Status by Model | Inquiry-based |
After doing some research, I noticed a few patterns.
First, most domestic tools focus on measuring second-tier AI visibility (SOV). Since the GEO market itself is still in its early stages, it appears that SOV—which most intuitively shows “how often a brand is mentioned in AI”—was the first metric to be commercialized.
Second, OnTheAI stood out as a domestic tool that covers all three stages. What sets it apart from other domestic services is its integrated structure, which connects Stage 1 (demand identification, or "Query Fan-out"), Stage 2 (exposure), and Stage 3 (inbound traffic) all within a single tool.
Third, while global services offer broad coverage across multiple tiers, they lack domestic data. Semrush covers tiers 2 and 3, and Profound covers tier 1, but neither supports data based on Korean prompts. This is why it’s difficult for domestic brands to use global tools as-is.
Another point worth noting is Semrush’s three-step measurement method. Semrushestimates AI-driven traffic—including that of competitors—based on clickstream panel data. Unlike GA4, which only shows your own data, this is valuable because it allows you to assess your relative position compared to competitors. However, since these are estimates rather than actual measurements, it’s best to use them to identify trends and patterns rather than relying on absolute numbers. The Elephant team first encountered this information during a session at the 2026 DMS Conference and is currently studying it. We’ll share our monitoring results separately in the future!
Ahrefs, OnTheAI, BlueDot: A Review Based on Three Months of Hands-On Monitoring
① Ahrefs Brand Radar: You can track AI-related mentions across your industry alongside your SEO performance.
Our team was already using Ahrefs as an SEO analysis tool. With the introduction of the Brand Radar feature, we can now track AI-generated mentions and see how often our clients’ brands are mentioned on platforms like ChatGPT and Perplexity.
In terms of measurement stages, Ahrefs Brand Radar focuses on Stage 2 AI Share of Voice (SOV). Since Ahrefs primarily handles English-language prompt data, I found that it has limitations when it comes to accurately reflecting citation trends in the Korean query environment. While it is perfectly usable for monitoring purposes, I concluded that it should be treated as a supplementary metric rather than a primary tool for measuring performance in the Korean market in detail.
Ahrefs Brand Radar Dashboard
Who is this solution best suited for? Teams that are already using Ahrefs and want to add AI-powered visibility monitoring. We recommend it for companies in the expansion phase targeting global markets.
- Measurement Phase: Phase 2 AI Share of Voice (SOV)
- LLM Platform Coverage: ChatGPT, Google AI Overview, Gemini, Perplexity, Claude
② OnTheAI: Tell me why the AI didn't cite our website
The first thing that caught my eye when I saw OnTheAI was its AI content gap analysis feature.
While most GEO tools simply tell you “how many times our brand was mentioned in this prompt,” OnTheAI goes a step further. It identifies pages that were crawled but not actually mentioned in the AI’s response as “opportunities” and even suggests ways to revise them so they can be cited.
From a three-stage perspective, what makes OnTheAI unique is that it connects allthree stages— Stage 1: Prompt Demand → Stage 2: AI Exposure → Stage 3: AI Acquisition—within a single tool. Among domestic tools, it offered the most detailed analysis of gaps between stages, such as “We’re getting citations but no clicks” or “We’re missing out on queries with high demand.”
OnThe AI Dashboard
Which teams is this best suited for? Teams that want to go beyond simply assessing their current situation and see a roadmap for content improvement all at once. If you want to quickly implement a GEO strategy, we recommend OnTheAI.
- Measurement stages: Stages 1, 2, and 3
- LLM Platform Coverage: ChatGPT, Gemini, Perplexity
③ Blue Dot: You can even gauge the sentiment with which AI mentions our brand
BlueDot takes a different approach. It uses BM25, a technology based on RAG (Retrieval-Augmented Generation), and semantic similarity algorithms to predict the likelihood of AI-generated content citing a brand, and monitors brand standing on a daily basis using its proprietary metric, the BII (BlueDot Intelligence Index).
In terms of measurement metrics, this tool provides the most in-depth analysis of Stage 2 AI Search Visibility (SOV). Its key feature is that it breaks down data not just by the number of mentions, but by frequency visibility, position visibility, and positive/negative sentiment scores. You can check whether competitors appear at the top of search results for certain prompts while your brand does not, and even verify whether your brand is mentioned in a positive context within the responses.
Since it’s the tool best suited for accurately interpreting the context behind the figure “SOV 35%,” it’s a great fit for teams focused on brand positioning.
BlueDot AI, provider of BlueDot Intelligence services
Which teams is this best suited for? Teams that want to gain a precise, metric-based understanding of their brand’s current AI visibility. If data depth is a priority, we recommend BlueDot Intelligence.
- Measurement Phase: Phase 2 – Precise Measurement of AI Share of Voice (SOV)
- LLM Platform Coverage: ChatGPT, Google AI Overview, Gemini, Perplexity
Before identifying metrics, the stage where a marketer’s perspective is most crucial is the customer’s prompt!
As I compared them, I realized that GEO services aren’t actually in competition with each other. Their perspectives were simply different. But I also learned something else that’s even more important.
In fact, the area where strategy is most critical is designing prompts, rather than interpreting metrics. These prompts serve as the starting point for measuring GEO performance, much like keywords, so the meaning of the metrics can change completely depending on the questions you ask.
Rather than simply designing prompts that expect conversions from the brand’s perspective—such as “Recommend a GEO provider”—we need to start by considering the questions customers actually want to know and are genuinely curious about, such as “What are GEO and AEO, and what are some successful implementation cases in Korea?”
To design prompts that drive results, Elephant Company structures its prompts not by simply listing keywords, but by incorporating intent-based keywords and Customer Experience Paths (CEP) that reflect the actual navigation flows customers follow. We are continuously conducting experiments based on this approach. We plan to keep sharing the insights and results gained from these experiments, so please stay tuned.
GEO Data Measurement: Why You Should Start Right Now
AI search traffic is growing rapidly. Even if the measurement tools aren’t fully developed yet, simply starting to collect data now gives you a competitive edge. If you wait for the perfect tool, you’ll keep putting off getting started.
If you start measuring any one of these three stages now, you’ll have a baseline for comparison in six months. Which prompts are most important in Stage 1? How wide is the gap compared to competitors in Stage 2? Are actual clicks increasing in Stage 3? Teams that start gathering answers to these three questions now will gain a competitive edge.
Elephant Company works with our clients to define GEO performance metrics and build a framework for measuring them. If you’re feeling overwhelmed by the process—from implementation to performance measurement—please reach out to the Elephant team to discuss your challenges.
