Ingest
Load a defined dataset with source, period, market and property context.
Tool 10 / 12 · Search intelligence
Ingest query datasets, compare clustering approaches and turn groups into a reviewable coverage and content plan.
Scope and access are confirmed for each implementation.
The operational problem
Raw query exports are too large and repetitive for useful planning. A single opaque clustering score can also hide ambiguity, brand terms and cannibalisation risks.
How it works
The sequence makes the input, decision point and completion check visible before broader automation is introduced.
Load a defined dataset with source, period, market and property context.
Apply the selected similarity or SERP-based methods and inspect uncertain groups.
Map existing coverage, gaps and candidate pages for human prioritisation.
Capability map
These are product capabilities to validate during solution design, not claims that every connector or operating mode is already enabled.
Work from structured query data rather than disconnected spreadsheets.
Compare available clustering approaches instead of treating one algorithm as universal.
Connect groups to existing pages and surface possible overlap or gaps.
Prepare a content map with priorities, owners and review notes.
Implementation inputs
Data-source connectors, supported algorithms, scale and warehouse requirements need confirmation. Clusters are planning aids, not guaranteed search opportunities or ranking outcomes.
Continue exploring
Combine tools only after each workflow has a clear owner and data boundary.
Next step
Share a representative example, the tools involved and the decision you want the workflow to support.
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