The ListeningMind AI Agent uses generative LLMs to help interpret and support analysis based on search result data. You can quickly run data analysis tasks through pre-built agents and communicate with them directly.
AI Agents can analyze ListeningMind screens within the following specific features:
Agent Name | Available Features |
Query Finder Analyst | Query Finder |
Path Finder Analyst | Path Finder (Path View, Persona View, Past/Present Comparison, Keyword Comparison) |
Cluster Finder Analyst | Cluster Finder |
Persona Analyst | Persona View, Cluster Finder |
GEO Prompt Builder | Persona View, Cluster Finder |
More agents are scheduled to be released for various features in the future.
Getting Started with the Agent
Click the Agent Card at the bottom right of the screen to open the sidebar and begin receiving answers.
The AI Agent generates responses based on the keywords entered in the Finder the user is currently exploring.
Each Agent provides customized analysis tailored to its specific function:
1) Using built-in service Agents
Customized analysis is conducted according to the analysis direction of each feature.
Query Finder Analyst:
Top 5 Search Intent Analysis
Groups and suggests the top 5 core search intentions.
Brand/Non-Brand Top 5
Extracts the top 5 entities categorized into Brand (specific products/companies) and Non-Brand (categories/general nouns).
Path Finder Analyst (Path View, Persona View, Past/Present Comparison, Keyword Comparison)
Top 3 Path Recommendations
Suggests the top 3 core search paths based on data graphs.
Top 3 Structure Analysis (Hub & Branch)
Identifies 3 key "Hubs" where users transition from information exploration to purchase consideration.
Cluster Finder Analyst
Top 3 Search Purpose Recommendation
Groups clusters with similar intent around Hub Keywords to suggest the top 3 search purposes.
Top 3 From → To Flow Analysis
Identifies the top 3 representative transition flows where context shifts through Hub Keywords.
Persona Analyst
Top 3 Persona Derivation
Creates up to 3 detailed virtual personas interested in a specific brand or product.
Persona Rationale & Context Summary
Summarizes the specific situation and core needs of the persona based on keyword data.
GEO Prompt Builder
AI-Customized Prompt Generation
Creates 3–10 natural conversational prompts (e.g., "Tell me how to choose and use...") reflecting consumer KBF and emotions.
Prompt Rationale
Provides search volumes and reference URLs to explain why the AI inferred those specific questions.
2) Direct Inquiries by User
The recommended questions at the top provide key answers that each agent can offer within the Finder.
After clicking each agent, additional follow-up questions can be asked based on the provided content.
LLMs can make mistakes when providing information. Please double-check the results.
The following comparisons are provided:
Past/Present Comparison (Path) | Keyword Comparison (Path) | Past/Present Comparison (Cluster Finder) |
Time Point Analysis Results Separates past and present to derive the most significant, high-volume search flows. | Top 3 Core Search Paths for Keyword A & B Analyzes and shows the hidden intent behind 3 major search flows for each keyword. | Top 3 Search Purposes (Past/Present) Analyzes whether past users sought information while current users focus on purchase/action. |
Pattern Changes Points out intuitive shifts, such as how [Path A] in the past has evolved or expanded into [Path B]. | Path Comparison Analysis Derives critical disposition differences and insights between the two groups. | Search Purpose Trends Explains the psychological shifts behind consumer interest changes (e.g., Interest A → Interest B). |
Detailed View via Hyperlinks
After analysis, users can click hyperlinks in the dropdown to compare graphs and view specific details.
Feedback Feature
Users can rate LLM responses; this feedback is used to improve future performance.