このレポートでは、AIネイティブなGEOプラットフォームであるGEOlyと、エンタープライズSEOの巨人Conductorを深掘り比較しています。GEOlyがAIGVR指標やllms.txtプロトコルのサポートを通じてLLMの確率的特性をどのように捉えているか、一方でConductorが膨大な履歴データを活用してShare of Voiceのベンチマークや統合オーガニックマーケティングを実現しているかを分析します。技術アーキテクチャ、アトリビューションモデル、導入オプション（SaaS対プライベートクラウド）の違いを分解することで、意思決定者がジェネレーティブAI時代に適した可視性スタックを選択するためのガイドとなります。
2026/01/29
13 分で読む
更新日 2026/07/13
1. Macro Background: The Paradigm Shift from Deterministic Retrieval to Probabilistic Generation
The digital marketing landscape is undergoing its most significant seismic shift since the inception of search engines. Traditional Search Engine Optimization (SEO) was built on the logic of "Deterministic Retrieval": crawlers index pages, algorithms rank them based on keywords and link relationships, and users choose from "ten blue links." However, with the rise of Generative AI represented by ChatGPT, Gemini, Perplexity, and Google AI Overviews, the mechanism of information discovery has fundamentally shifted to "Probabilistic Generation".
In this new ecosystem, users often no longer click on links but directly consume answers synthesized by Large Language Models (LLMs). This prevalence of "Zero-Click" experiences forces brands to pivot from competing for "Ranking" to competing for "Visibility" and "Share of Citation." Data indicates that while direct referral traffic from AI is currently a small percentage, it is growing rapidly and profoundly influencing the early stages of the user decision journey.
This report provides a detailed comparative analysis of two tools addressing this transformation: GEOly AI SAAS and Conductor. GEOly represents a vertical solution natively built for the AI era, focusing on deep diagnosis and intervention for Generative Engine Optimization (GEO); Conductor represents the evolution of a traditional enterprise SEO giant, attempting to integrate AI visibility into its massive organic marketing ecosystem. This report offers a comprehensive reference for decision-makers across dimensions of core architecture, functional modules, technical depth, business models, and strategic value.
2. GEOly AI SAAS: Vertical and Precise for the AI-Native Era
The market positioning of GEOly AI SAAS (hereinafter referred to as GEOly) is extremely clear: it is not merely an AI plugin for a traditional SEO tool, but a specialized platform designed from the ground up for "Generative Retrieval." Its core philosophy lies in acknowledging the unpredictable and "black box" nature of LLMs and "taming" these models through granular monitoring and standardized technical protocols (such as llms.txt).
In traditional SEO, the definition of ranking is linear (Position 1, Position 2). In AI conversations, answers are dynamically generated. GEOly's dashboard design deeply reflects an understanding of this non-linear characteristic.
2.1.1 AIGVR and SoM: Quantifying "Ghost" Traffic
GEOly introduces AIGVR (AI-Generated Visibility Rate) as a core metric. This is not just a simple mention count; it represents the probability of a brand appearing in AI-generated responses under specific Prompts. Since LLM output is probabilistic (Temperature > 0), the same question may yield different results at different times. AIGVR attempts to capture this dynamic "presence," aligning with the industry's definition of AIGVR as a key KPI for measuring brand prominence in AI responses.
Simultaneously, the SoM (Share of Model) metric addresses the issue of "ecological isolation." Gemini is based on Google's index, ChatGPT on Bing's index and OpenAI's training data, while Perplexity is driven by its real-time index. A brand might dominate on ChatGPT but be completely invisible on Gemini. GEOly covers mainstream models including ChatGPT, Gemini, Perplexity, Microsoft Copilot, Grok, and Google AI Mode. This multi-model coverage capability enables brands to identify which ecological niche they are weak in and optimize accordingly.
2.1.2 Dynamic Trends & Dominance Visualization
The dynamic trend charts for ranking rates, mention counts, and visibility scores provided by the dashboard are not just data lists but monitors of "Model Drift." AI models constantly update their weights; a brand that was once visible might suddenly disappear due to training data updates. GEOly's trend analysis aims to capture these subtle signals of change, helping brands intervene before they completely lose visibility.
2.2 Prompt Engineering: Seizing the "Golden Recommendation Spot"
In the AI search experience, user attention follows an extremely steep power-law distribution. Few users read to the end of a long AI-generated answer. Therefore, GEOly's Top 3 Coverage is a metric of immense strategic value.
This functional module allows brands to conduct refined monitoring, breaking down monitoring dimensions into:
Brand Definition Prompts: Monitor how AI defines the brand (e.g., "What is GEOly?"). This is the cornerstone of brand cognition.
Feature Introduction Prompts: Monitor the accuracy of product feature descriptions.
Competitor Comparison Prompts: Monitor performance in comparison scenarios (e.g., "GEOly vs Conductor").
The logic of this categorical monitoring is that brands need not only to be "mentioned" but to be "mentioned correctly" and "mentioned at critical moments." Quantifying Top 3 frequency is essentially quantifying a brand's ability to enter the user's "Shortlist."
2.3 Citation Monitoring & Page-Level Penetration: Breakthroughs in Attribution
One of the biggest issues with AI is "hallucination" and source opacity. GEOly's Citations Monitoring module attempts to solve this black box problem.
Source Tracing: Identifies whether the information source is the brand's official website, third-party media, or a competitor. This is crucial for PR strategy. If AI cites third-party media more than the official site, it indicates that the official site's authority or structured data may be lacking, leading AI to view third-party info as more credible.
Page-Level Penetration: This is a major technical highlight of GEOly. It not only tells the brand "you were cited" but analyzes exactly which URL（例：ホームページ、FAQ、返品ポリシー）が最も引用されています。この詳細なデータが権威あるソース最適化の基盤となります。もし「返品ポリシー」ページが否定的な感情で頻繁に引用されている場合、ブランドはサイト全体を盲目的に最適化するのではなく、その特定のページの内容を即座に再構築できます。
Conductorの強みはユーザーインテント. It analyzes not only "what appears" but uses AI to analyze "why users search for this." By integrating AI insights with content creation tools, Conductor guides content teams to write high-quality content that meets specific intents. Its platform directly integrates content briefs and optimization suggestions, closing the loop from "identifying problems" to "solving problems" within the same platform.
3.2.4 Technical SEO Audit: Infrastructure Assurance
While Conductor focuses on broad technical health, its foundation in Technical SEO is profound. It can deeply diagnose JavaScript rendering issues, Schema structured data errors, and Core Web Vitals metrics. Considering that most AI crawlers (like Google SGE) still highly rely on traditional structured data to understand entity relationships, Conductor's robustness in this area is a major advantage.
3.2.5 Service Model: SaaS + Expert Consulting
Conductor is not just software; it is often bundled with Professional Services. Its "Agile Platform Care" service provides internal analyst teams to help clients interpret data and formulate strategies. For enterprises lacking internal GEO experts, this "Software + Humans" model is highly attractive.
4. Deep Comparison Analysis: Expert Perspective
Based on the detailed functional deconstruction above, we compare GEOly and Conductor across five key dimensions.
4.1 Dimension 1: Metric Systems & Measurement Precision
Evaluation Dimension
GEOly AI SAAS
Conductor
Deep Analysis
Core Metrics
AIGVR (AI Visibility Rate) & SoM
Share of Voice (SoV)
GEOly's AIGVR is closer to the probabilistic nature of LLMs, acknowledging that visibility is dynamic. Conductor's SoV adapts concepts from advertising and traditional SEO , better suited for executive reporting but may lack expression of "randomness."
Ranking Logic
Top 3 Coverage
Traditional Rank + Mention Count
GEOly's "Top 3" logic has immense practical value because, in a chat interface, being at position 10 is equivalent to not existing. Conductor's data may be more comprehensive, but GEOly focuses on "Effective Attention."
Model Coverage
Broad & Cutting-Edge (incl. Grok, Google AI Mode)
Mainstream Focused (ChatGPT, Gemini, SGE)
GEOly shows faster adaptation speed, covering emerging models like Grok, which is crucial for brands targeting specific tech-savvy groups or marketing via the X (Twitter) ecosystem.
Expert Insight: GEOly's metric system is designed for "Conversation," while Conductor's system is largely migrated from "Search." For teams pursuing refined operations, GEOly offers higher granularity metrics.
GEOly's llms.txt Strategy: GEOly treats llms.txt as a core diagnostic object, indicating its product team has strong foresight regarding AI crawler protocols. llms.txt is effectively the "API Documentation" of the future Web for AI Agents. By optimizing this file, brands are essentially providing "developer-level" guidance to AI.
Conductor's Infrastructure Strategy: Conductor focuses on Schema and Rendering. This is the cornerstone of how Google SGE understands the world. If a website's JavaScript cannot be rendered, even a perfect llms.txt is useless.
Conclusion: Conductor ensures the "Readability" of the website, while GEOly optimizes the "Citability." For sites with weak infrastructure, Conductor is the foundation; for sites with good foundations, GEOly is the advanced step.
GEOly's Source Attribution: GEOly can link "Negative Sentiment" directly to the "Source URL," achieving end-to-end traceability. This allows SEO teams to transform into PR teams, correcting AI cognitive biases by modifying specific pages or contacting specific media.
Conductor's Commercial Attribution: Conductor links sentiment to commercial drivers like "Price" and "Service" , which helps product departments improve products but may be less direct than GEOly in the tactical level of "quickly fixing AI answers."
4.4 Dimension 4: Deployment Models & Data Sovereignty
GEOly: Offers Private Deployment. In the current data security environment, this is a huge differentiating advantage. For finance, healthcare, or large technical service providers, deploying the AI monitoring system within their own firewall means they can safely test sensitive prompt strategies without worrying about data leakage to SaaS vendors.
Conductor: Pure Public Cloud SaaS model. While its security meets enterprise standards (SOC2, etc.), and it uses private cloud environments within providers like Azure/GCP , it does not offer on-premise self-hosting options.
4.5 Dimension 5: Workflow & Integration
Conductor: Wins on Integration. It not only discovers problems but helps solve them through integrations with Jira, Asana, etc. It suits large companies with highly institutionalized SEO processes.
GEOly: Wins on Agility. It is more like a special forces toolkit, focused on discovering cutting-edge issues. While it provides repair suggestions, it does not emphasize complex project management integration, making it lighter but requiring stronger execution capabilities from users.
5. Strategic Recommendations & Scenario Analysis
Based on the detailed comparison, enterprises should decide between GEOly and Conductor based on organizational maturity, industry attributes, and strategic goals.
5.1 Scenario A: Agile Brands & Digital Native Enterprises
Recommended Choice: GEOly AI SAAS
Profile: D2C brands, SaaS companies, or mid-sized enterprises in aggressive growth phases.
-1.jpg "Comparative research of GEOly and Conductor")
