Discover What Triggers Action
Cluster Finder

Since the graph results in Cluster Finder are constructed based on Google SERP (Search Engine Results Page) data, the update cycle of the SERP directly influences the refresh rate of the results.

For KR data, most SERPs are re-collected within 1 to 2 months. Therefore, you can generally consider the data timeframe of the results to be within the most recent month from the inquiry date. However, please note that some connected keywords may occasionally include data collected within the past year.

Practical Tip:

You can check the exact collection timeframe for a specific keyword by clicking on it. Access the SERP History within the keyword information to identify the precise date of collection.

Cluster Finder is a network graph that visualizes the correlation and search volume between various keywords.

• Circle (Node) Size: The size of each circle is proportional to the search volume of that keyword. A larger circle indicates a higher volume of search demand, helping you immediately identify high-traffic keywords.
• Distance and Position between Circles: The layout and spacing between nodes are determined by an algorithm designed to maximize readability. The physical distance between circles does not carry a specific analytical meaning.
• Highlighted Circles in Cluster Names: When a cluster name is generated, certain circles may be highlighted to represent the group. The size of these specific highlights does not carry analytical significance.

This feature reveals which URLs and domains consistently appear at the top of search results for the keywords analyzed in Cluster Finder. It allows you to identify which platforms have the greatest digital influence on consumers. This data serves as a critical reference for media planning, influencer selection, and determining which e-commerce platforms to enter.

• Note: This data reflects Organic Search results only. Paid advertisements, such as Search Ads or Power Links, are excluded from this analysis.

Strategic Insights & Practical Tips:

• Identify Market Leaders: Pinpoint which specific URLs or domains dominate the search visibility for your target keywords.
• Optimize Media & Content Strategy: Use data on high-impact media outlets and sites to inform your Media Planning, Content Strategy, and Influencer Partnerships.
• Keyword Deep-Dive: Click the ‘+’ button next to any URL to view the full list of keywords that are driving traffic and visibility to that specific page.

① Cluster Graph

• Clusters: Keyword groups bundled by similar search objectives or intents, displayed by color.
• Hub Keywords: Key terms with high connectivity within the entire dataset.
• Connection Lines: Visualizes the relationships and flow between keywords.

② Cluster Resolution Adjustment

Increasing the resolution breaks down a single cluster into more detailed intent groups.

• Example: A cluster of 37 keywords at medium resolution can be split into 61 more specific groups at the highest resolution.

③ Card View

Clusters can be viewed in a card format sorted by Monthly Average Search Volume. This is useful for identifying the priority of core keywords.

④ Cluster/Keyword Exclusion

You can temporarily exclude unwanted clusters or keywords from the results, allowing you to focus only on the data necessary for your analysis.

① Search Path Direction

• Before & After Search: Synthesizes and displays both preceding and succeeding keywords.
• After Search: Tracks and displays keywords searched after the input keyword.
• Before Search: Tracks and displays keywords searched before the input keyword.

② Search Steps (Levels 1–3)

Sets the range of steps before and after the input keyword.

• Example: If set to ‘Level 2’, the tool will display keywords up to two steps before and after your input keyword.

③ Zoom

You can adjust the Zoom to control the limit of the search results range.

If the search results are insufficient or excessively numerous, you can adjust this option to the appropriate level for optimal viewing.

Cluster Finder is a tool that collects over 10,000 related search terms linked before and after a specific keyword and visualizes them into groups (clusters) with similar search intents or objectives. This allows for a broad understanding of consumer interests and market needs.

Analyzing tens of thousands of search keywords individually is nearly impossible. Cluster Finder uses AI to automatically analyze fragmented data and group keywords with similar concerns or contexts into large “intent clusters.” Moving beyond simple frequency—”which words were searched the most”—it serves as a strategic map that shows at a glance, “What themes are people currently most interested in within our brand’s category?”