It seems like GEO is a topic that never goes out of marketing team meetings these days. We understand that we need to get our brand cited on ChatGPT or Perplexity, but it is difficult to readily answer the question, "So how do you know if it’s working well?".
Looking at search data, we can see that this concern is not unique to us. The monthly domestic search volume for the keyword 'GEO' increased by approximately 189% from 5,570 in January 2024 to 16,110 in January 2026 (Source: Listening Mind), and 'GEO marketing' began to register search volume in June 2025, growing to 910 searches per month in just half a year. This means that many marketers are currently searching with similar questions.
If you have just started learning GEO, please refer to the article below!
GEO Optimization Basic Guide: A Glossary of SEO/GEO Terms You Must Know for B2B Marketing
So, starting early this year, the Elifunt team tools that could quantitatively measure visibility regarding. We did this by searching for AI, making direct inquiries, and trying out beta versions. I wrote this post to honestly share what our team learned and experienced during that process.
I should mention upfront that this article is not the definitive answer. The GEO measurement market itself is still highly volatile, and we are still learning ourselves. I compiled this in the hopes that it will be of at least some help to marketers facing similar challenges.
You need to analyze data for GEO performance by categorizing it into three types
As I began exploring tools, the first thing I had to clarify was determining exactly what I was trying to assess when it came to "measuring GEO performance." As I searched, I realized that the tools currently on the market actually have different metrics and standards.
Just as traditional SEO the 'keyword search volume (demand) → search result exposure → clicks (traffic)'funnel, it appears that GEO (Generative AI Optimization) is growing in a similar direction.
The current tool market is evolving by predicting this based on their respective data and know-how to secure a new funnel leading from 'prompt demand → AI response exposure → site traffic'
Explore data for GEO performance through these three layers.
Step 1. Prompt Demand: What Questions Do People Ask AI?
Just as keyword volume data serves as the starting point for content strategy in SEO, in GEO, the questions people actually ask the AI are the first foundation of strategy.
However, AI prompts differ fundamentally in structure from traditional keywords. Rather than short keywords like “GEO marketing tool,” there are many longer natural language questions, such as “I am a B2B SaaS marketing manager; how do I measure the effectiveness of GEO implementation?” Furthermore, even with the same intent, the ways of expression are broken down into much more diverse patterns. This is why traditional search volume data does not correspond one-to-one with AI prompts.
If you do not properly grasp this step, you will end up setting the prompts to be measured in Step 2 based on guesswork. Since measuring SOV for questions that actual users do not ask is meaningless no matter how hard you try, this step—defining in which prompts our brand should be mentioned—serves as the foundation of the GEO strategy. Currently, tools capable of measuring this step with data are just beginning to emerge globally, and there are no tools yet available that cover domestic Korean-language data.
Step 2. Exposure Share: How often is it cited in AI answers?
This is the stage that most GEO tools currently measure. It involves running specific prompts repeatedly through an AI to crawl the responses and tallying how often our brand is mentioned.
There is an important distinction here. SOV is a supply-side metric that shows how often AI cites us when generating answers. This figure alone cannot tell you whether an actual user viewed the answer or clicked the link. There is a difference between "AI cited us" and "a person entered our site through that answer.".
Therefore, looking at qualitative aspects of SOV—such as the order of appearance within responses, positive and negative context, and position relative to competitors—in addition to the simple number of mentions allows for a more multi-dimensional understanding of the current situation.
Step 3. Incoming Traffic: So, did they actually visit the website?
This step is based on user behavior criteria. It checks whether a person actually clicked the link and entered the site when the AI cited us.
Measurement methods are broadly divided into two types. One is an estimated data method that allows for comparison including competitors; while useful for understanding the competitive landscape, it is suitable for identifying relative trends compared to competitors rather than absolute values, as these are estimates rather than actual figures.
Another method involves measuring using analytics tools installed directly on your site, which allows you to verify actual traffic figures rather than estimates. However, this method has the limitation of only allowing you to view your own data. You can find out the specific method the Elifunt team uses to measure AI traffic with GA4 in this article
These three stages do not always point in the same direction. If SOV is high but AI traffic is low, it means the AI is citing us, but it is not leading to clicks because there are no links or our position within the answers is low. Conversely, if there is AI traffic but the SOV measurement is low, it could be a case where we are being quietly cited in long-tail queries. That gap itselfbecomes a strategic insight.
With the introduction of GEO services, the global market is already setting the standard
Before exploring domestic services, I first examined the criteria used to evaluate GEO tools overseas. As explained earlier, among the three stages, the area where the most tools currently compete in the market Stage 2, AI Exposure (SOV) measurement. The six evaluation criteria that appear repeatedly in global researchalso primarily address the standards for comparison when adopting services at this stage.
- LLM Model Coverage: How many models are tracked, such as ChatGPT, Gemini, and Perplexity?
- Key Visibility Metrics: Share of Voice, Mentions, Quote Frequency, Sentiment Analysis—what measures?
- Competitor Analysis: Can the AI mention status of competing brands be compared?
- Data Processing and Analysis Depth: Simple Collection or Providing Insights
- Action Orientation: Does It End in Measurement or Lead to Content Improvement?
- Ease of Use and Target Users: Who Is the Tool For?
However, there is one point of concern for domestic companies. Tools providing global services lack domestic data. Tools building recognition in overseas markets currently do not include Korea in their supported regions, or most collect data using English-based prompts.
In the domestic market, AI response data for Korean prompts is key, but since most global tools collect data based on English, it is difficult to accurately assess the actual AI visibility of domestic brands. Furthermore, we determined that a measurement tool specialized for the Korean market is necessary to reflect the search patterns of Korean users, which differ from those of global targets.
How can I find GEO services for domestic companies?
Elifunt began full-scale research on GEO tools in January 2026 and listed over 10 services. As we explored, we realized that the nature of each service was quite different, and that the category of “GEO performance measurement” itself still has various definitions.
Our team is currently focusing on Stage 2 of the three: AI exposure measurement tools. We are directly verifying Stage 3 AI traffic using GA4, and regarding the demand for Stage 1 prompts, there are currently no tools that properly cover domestic data. Therefore, we are at the stage where we are first examining Stage 2 services, which currently have the most competing tools and where differences in domestic data consistency are most pronounced.
If you look at which of the three stages each tool covers, its nature becomes much clearer.
GEO Performance Measurement Tool: 2 Criteria the Elifunt Team Decided to Pay for
First, can I view the raw data of the prompt answers directly?
The GEO measurement market is still in its early stages. No service is at a point where it can claim, "This method is the industry standard." This means that instead of blindly trusting the numbers displayed by tools, you must be able to interpret and judge what lies beneath the numbers yourself.
So, what the Elifunt team looked at was not the aggregated results, but the raw data behind them. We needed to be able to directly verify how the AI responded to specific prompts and which URLs it cited in order to interpret the data according to our standards. Rather than the figure of “Our Brand SOV 35%,” we prioritized a service that allowed us to see which prompt that number came from and what the actual response text was like.
Second, does it transparently disclose the trust relationship with client companies?
GEO is an area where results are not immediately visible. Therefore, I considered it important whether the service disclosed the actual achievements along with the names of the client companies. As you can see in the table below, among domestic services, only a few allowed users to verify actual cases on websites or blogs where company names were disclosed.
OnTheAI and BlueDot were the domestic services that met both of these criteria simultaneously, and for the global standard, we also used Ahrefs, which was already in use, as a comparison target.
[Comparison Table of Domestic and International GEO Services]
| service | domain | Measurement step | Key Indicators | flan |
|---|---|---|---|---|
| Ahrefs | ahrefs.com | Step 2: AI Exposure (SOV) | Brand mentions, quoted domains, AI traffic | Lite $129/month |
| Semrush | semrush.com | Step 2 + Step 3: AI Exposure + AI Inflow | SOV, Mentions, Citation Rate, AI Traffic | Pro $139.95/month |
| Profound | tryprofound.com | Step 1 + Step 2: Prompt Demand + AI Exposure | Prompt Volume, AI SOV, Mention Frequency | Starter $99/month |
| On the AI | onthe.ai | Stages 1, 2, and 3 (all) | SOV, Citation Share, Query Fan-out, AI Traffic | Pro 500,000 won/month~ |
| Blue Dot Intelligence | bi.bluedot.so | Step 2: Precise Measurement of AI Exposure (SOV) | BII, Citation Rate, Frequency·Location·Sentiment Visibility | Starter 490,000 won/month~ |
| Chain shift | trychainshift.ai | Steps 1+2: Prompt Demand + AI Exposure (SOV) | AI Visibility, Citation Rate, Query Volume, Query Fan-out, Brand Risk Score, Homepage GEO Score | Starter $89/month |
| OPTGEO | optigeo.kr | Step 2: AI Exposure (SOV) | GEO Score (Citation + Brand) | Inquiry-based |
| A-Nect | ainnect.co.kr | Step 2: AI Exposure (SOV) | SoA, Citation Rate, AVI | Inquiry-based |
| Prompt Architect | promptarchitect.app | Step 1: Prompt Demand | Query volume, query volume by model | Inquiry-based |
| GPTO | gpto.kr | Step 2: AI Exposure (SOV) | Brand Recommendation Rankings, Exposure Status by Model | Inquiry-based |
After doing some research, a few patterns stood out.
First, most domestic tools focus on measuring Level 2 AI Exposure (SOV). Since the GEO market is still in its early stages, it appears that products were commercialized starting with SOV, which most intuitively shows "how often a tool is cited by AI."
Second, among domestic tools that cover all three stages, OnTheAI stood out. Its structure, which connects everything from Stage 1 (Query Fan-out) to Stage 2 (Exposure) and Stage 3 (Incoming Traffic) within a single tool, is what differentiates it from other domestic services.
Third, while global services offer wide level coverage, they lack domestic data. Semrush covers levels 2 and 3, and Profound covers level 1, but neither supports Korean prompt-based data. This is why it is difficult for domestic brands to use global tools as is.
One more thing we noted was Semrush's three-stage measurement method. Semrushestimates AI-driven traffic, including that of competitors. This is significant because, unlike GA4 which only allows you to view your own data, it enables you to understand your relative position compared to competitors. However, since these are estimates rather than actual measurements, it is best used to read trends and tendencies rather than absolute figures. The Elifunt team first encountered this during a session at the 2026 DMS Conference and is currently learning about it. We will share our monitoring findings separately later!
Ahrefs, OnTheAI, BlueDot: A Review After 3 Months of Hands-on Monitoring
① Ahrefs Brand Radar: You can see AI mention trends across the entire industry along with 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 citations and check how often our clients' brands are mentioned on platforms like ChatGPT and Perplexity.
In terms of measurement levels, Ahrefs Brand Radar focuses on Level 2 AI Exposure (SOV). Since Ahrefs primarily deals with English-based prompt data, limitations in accurately displaying citation trends in a Korean query environment. While it is sufficient for monitoring purposes, I concluded that it is appropriate to use it as a supplementary metric for finely measuring performance in the Korean market.
Ahrefs Brand Radar Dashboard
Which teams is this suitable for? Teams that are already using Ahrefs and want to add AI visibility monitoring. We recommend it to companies in the expansion phase targeting the global market.
- Measurement Phase: Level 2 AI Exposure (SOV)
- LLM Platform Coverage: ChatGPT, Google AI Overview, Gemini, Perplexity, Claude
② On the AI: Tell me why AI didn't cite our website
When I first saw OnTheAI, what caught my eye was the AI content gap analysis feature.
While typical GEO tools simply tell you "how many times our brand was mentioned in this prompt," OnTheAI goes a step further. It identifies pages that have been crawled but not actually mentioned in the AI response as "opportunities," and even suggests directions on how to modify them to ensure they are cited.
From a three-stage perspective, what makes OnTheAI unique —from Stage 1 prompt demandto Stage 2 AI exposure and Stage 3 AI inflow—within a single tool. Among domestic tools, it was possible to analyze gaps between stages most concretely, such as identifying issues like “citations are happening but no clicks” or “we are missing from queries with demand.”
On the AI Dashboard
Which team is this suitable for? A team that wants to go beyond understanding the current situation and see the direction for content improvement all at once. If you want to quickly execute a GEO strategy, I recommend OnTheAI.
- Measurement Stages: All of Stages 1, 2, and 3
- LLM Platform Coverage: ChatGPT, Gemini, Perplexity
③ Blue Dot: You can even gauge the intensity of how much AI mentions our brand
BlueDot takes a different approach. It predicts the AI search citation probability of content by utilizing BM25, based on RAG (Search Augmented Generative) technology, and semantic similarity algorithms, and monitors brand status daily using its proprietary metric called BII (BlueDot Intelligence Index).
In terms of measurement levels, deepest into Level 2 AI Exposure (SOV) . Its key feature is that it breaks down the data into frequency visibility, positional visibility, and positive/negative metrics, rather than simply displaying the number of mentions. You can identify exactly which prompts feature competitors at the top while you are absent, and even check whether your brand is being mentioned in a positive context within the responses.
It is a good fit for teams sensitive to brand positioning, as it is a tool that can most precisely interpret the context behind the number “SOV 35%”.
BlueDot AI, which provides BlueDot Intelligence services
Which team is this suitable for? Teams that want to precisely understand the status of their brand's AI visibility through metrics. If data depth is important, I recommend BlueDot Intelligence.
- Measurement Step: Level 2 AI Exposure (SOV) Precision Measurement
- LLM Platform Coverage: ChatGPT, Google AI Overview, Gemini, Perplexity
Before finding metrics, the step where a marketer's perspective is most needed is the customer's prompt!
As I made comparisons, I realized that GEO services were not in a competitive relationship with each other. Their perspectives were fundamentally different. However, I learned something even more important from this.
The part where strategy is most needed is designing the prompt rather than interpreting the metric. Since this prompt is the starting point for measuring GEO performance, much like a keyword, the meaning of the metric changes completely depending on the question you choose.
Beyond designing prompts that expect conversion from a brand's perspective, such as "Recommend a GEO vendor," you need to consider the questions customers actually want to know and are curious about, such as "What are GEO and AEO, and what are some successful domestic implementation cases?".
To 'design prompts that produce results,' Elifunt structures intent-based keywordsand the Customer Experience Path (CEP) listing keywords, and is continuously experimenting based on this. We plan to continue sharing the insights and results gained from these experiments, so please stay tuned.
Why You Should Start Measuring GEO Data Right Now
AI search traffic is growing rapidly. Even if measurement tools are immature, simply starting to accumulate data now becomes a competitive advantage. If you wait for the perfect tool, your start will keep getting delayed.
If you start measuring any one of the three stages now, you will have a baseline to compare in six months. The team that starts accumulating answers to these three questions now—which prompts are important in Stage 1, what the gap is compared to competitors in Stage 2, and whether actual clicks are increasing in Stage 3—will get ahead.
Elifunt defines GEO performance indicators together with clients and is building a structure that is truly measurable. If you feel lost from execution to performance measurement, please share your concerns with the Elifunt team.
