A Korean Company Just Proved GEO Works with Hard Data: 52% vs 19% Citation Rate — Here's How
Does GEO actually work? It's the question the industry has danced around for two years, with plenty of opinions and almost no hard numbers.
On October 28, Korean digital marketing firm TMCK published what may be the most straightforward quantitative evidence of GEO effectiveness to date:
In ChatGPT responses to purchase-intent queries related to Chuseok (Korean Thanksgiving) shopping, GEO-optimized content achieved a 52% citation rate lasting 7+ days, compared to just 19% for standard content. For citations lasting 14+ days, the numbers were 29% vs 10%.
This isn't a lab simulation. It's real user data from real purchase-decision scenarios. And what's more telling: TMCK has iterated through three generations of its GEO product, with citation rates climbing from 30% (first gen) to 40% (second gen) to 60% (third gen "ansr") — each generation proving that GEO performance can be systematically engineered, not just hoped for.
Three Generations, Doubled Citation Rate: The Iteration Path
TMCK's product evolution maps the industry's technical trajectory with unusual clarity:
Generation 1 — T-GEO: Basic GEO content production. Analyzed AI engine source preferences and produced structured content accordingly. Citation rate: 30%.
Generation 2 — OccupAI: Added multi-platform monitoring across ChatGPT, Gemini, Naver AI Tab, and others. Citation rate: 40%.
Generation 3 — ansr: Achieved a complete feedback loop: monitor → analyze → optimize → re-monitor. AI response data feeds into content planning; post-publication citation tracking feeds into iterative improvement. Citation rate: 60%.
The insight embedded in this progression is critical: the primary driver of GEO effectiveness isn't the content itself — it's the completeness of the data feedback loop. Content alone caps at 30%. Add monitoring, and you reach 40%. Close the loop by feeding monitoring data back into content optimization, and you break through to 60%.
What Separates 52% from 19%?
TMCK's data is valuable precisely because it's a controlled comparison — same scenario (Chuseok shopping queries), same AI platform (ChatGPT), with the only variable being whether content was GEO-optimized. The nearly 3x citation gap demands explanation.
Based on TMCK's public disclosures, the methodology includes:
1. Start from AI's real questions, not from what brands want to say. TMCK analyzed large volumes of actual user queries on AI platforms, identifying gaps where AI gave poor answers but brands had genuine expertise. This isn't keyword research — it's question research.
2. Structure content for AI parsing logic, not human reading habits. Conclusion-first writing, data-backed claims, multi-level headings — not for aesthetics, but so AI can determine in milliseconds whether a passage is directly extractable for a response.
3. Continuous monitoring and iteration. ansr's core isn't one-time content optimization — it's ongoing tracking of where, how often, and in what context a brand appears in AI responses, then adjusting content strategy based on that data.
Eight New Contracts: Traditional Industries Are Buying In
TMCK signed eight new GEO solution contracts this year, spanning home appliances/IT, beauty/lifestyle, food, and financial services. The client profile is telling — these aren't tech companies experimenting with a shiny new tool. These are traditional consumer industries committing real budgets.
Even more notable is the use case: TMCK specifically mentions clients using GEO for Black Friday, year-end shopping season, and Lunar New Year campaigns. GEO has evolved from "long-term brand building" to "campaign-season traffic weapon" — enterprises are deploying it as a tactical tool during peak commercial periods.
Lessons for the Global GEO Market
These Korean data points carry direct implications for GEO practitioners worldwide:
First, GEO results are quantifiable. Not "we feel the brand is being mentioned more," but precise metrics like "52% vs 19% citation rate." If your GEO provider can't produce controlled comparison data — only scattered screenshots and vague claims of "improvement" — that's a red flag.
Second, GEO is not a one-time project. TMCK iterated for three years across three product generations, each improving results measurably. A "pay once, publish a batch of articles" service model is almost certainly a waste of money in the GEO context.
Third, industry adoption is accelerating. From appliances to beauty to finance, traditional industries are becoming GEO's primary customers. As these budget-rich sectors begin systematic GEO investment, the window for latecomers narrows.
China's GEO market alone is projected to reach $13.2 billion in 2026. Whether that number materializes depends on whether the industry can produce more players like TMCK — ones that let data, not hype, do the talking.
Data sourced from Dailian (Korean media), October 28, 2026. Citation rates based on TMCK's monitoring of ChatGPT responses to Chuseok-related purchase queries. GEO results vary by industry, competitive landscape, and execution quality; figures cited do not constitute performance guarantees.