ClusterFlow Silo Planner

1. Load Keyword Data

2. Clustering Settings

Silo Tightness (Similarity) {{ (similarityThreshold * 100).toFixed(0) }}%
Broad (Big Silos) Tight (Micro-Intent)
Keywords Loaded {{ parsedLines.length }}
Topical Clusters {{ activeClusters.length }}
Total Search Volume {{ formatNumber(totalVolumeAggregated) }}
Export Grouped Clusters

Topical Content Silos

Sorted by Cumulative Volume

Input or load keyword metrics on the left panel to synthesize semantic clusters instantly.

Cluster Hub Topic

{{ cluster.name }}

Vol: {{ formatNumber(cluster.totalVolume) }} {{ cluster.items.length }} keywords
  • • {{ item.keyword }} {{ formatNumber(item.volume) }}

Why cluster keywords for modern SEO?

Search engines no longer rank isolated pages for singular queries. By grouping semantically related search terms into topical content silos, writers target multiple high-intent keywords within a single article.

1. Lexical Jaccard Overlaps

Jaccard similarity measures phrase overlap based on token matching instead of character edits. This handles varying word order (e.g., "saas tools list" and "list of tools saas") with precise semantic accuracy, preventing duplicate groupings.

2. Search Volume Prioritization

By consolidating the search volumes of clustered keywords, you can see the cumulative value of a topic. This helps you identify and prioritize high-value content hubs first instead of writing low-impact articles.

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