Category Dominance Matrix

What it does

Clusters queries into categories and shows brand dominance per category.

Why this is insightful

Teams can decide where to defend, where to attack, and which categories are fragmented enough to win.

Required API fields

• query.keyword
• query.description
• rankings.brands[].name
• rankings.brands[].rank

How to use

1. Build category clusters from query signals.
2. Compute rank-weighted share per brand per cluster.
3. Classify dominance level.

Expected output

• category dominance matrix
• top brands per cluster
• cluster-level opportunity notes

Copy-ready skill prompt

Use this as a full copy/paste prompt in your AI tool:

Skill: Category Dominance Matrix
Goal: Run this analysis on FullMention data only.
Data policy:
- Do one controlled ingestion pull from FullMention API.
- Store dataset locally (file/local DB) and analyze offline.
- No repeated API fetch loops during analysis.
Execution contract:
- Provide ingestion_plan, max_api_calls, cache_key, dataset_timestamp, analysis_mode=offline_only.
Required fields:
- Use the required API fields listed on this page.
Output requirements:
- Return summary, key metrics, and evidence_map with source_field_paths and sample_result_ids.
- Include limitations and confidence score rationale.