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Clusters

A cluster is a territory you have decided to own: related topics you intend to cover properly rather than glance at.

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App route: /topic_clusters

Clusters, grouped into Now / Next / Later / Unprioritized
Clusters, grouped into Now / Next / Later / Unprioritized

A cluster is a territory you've decided to own: a group of related topics you intend to cover properly rather than glance at. Clusters are where strategy actually enters the product: Topics shows you what the market asks, and a cluster is you committing to answer a coherent slice of it.

It's also the default path into production. Most work reaches a brief through a cluster rather than through a single opportunity picked off a list.

Doing this rather than looking it up? The Tutorial walks this screen step by step in 4.1 · Align on strategy.

Reference

The header summarises the whole set: total clusters, estimated monthly demand, opportunity count, opportunity demand, briefs in progress, and pages published.

Each cluster row carries:

ColumnWhat it means
ClusterA rank number, the name, and the territory description
DemandEstimated monthly search demand across the cluster's topics
OppsOpportunities generated inside it
Opp demandMonthly demand represented by those opportunities
BriefsBriefs currently in production
PagesPages already published into the territory

Opportunity demand often exceeds cluster demand. That isn't an error: opportunities include long-tail queries beyond the topics that defined the cluster.

Each band is its own group, with its own cluster count and demand subtotal. Empty bands are hidden, so a workspace using only Now and Next looks like a two-band screen.

Row numbers are position within a band, not priority. Rows sort by demand descending, then alphabetically. Priority lives in the band header: the number beside a cluster says nothing about how it ranks against the one below it.

The funnel columns are a diagnostic. High demand with many opportunities and no briefs is a cluster you committed to and never started. Many pages with low demand is one you over-served. Reading across a row is faster than any report.

Why it works this way

Last updated at October 20, 2018

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