Metrics
Cluster Distribution Per Brand
Shows how each brand's perception is distributed across different themes (cluste
rs), revealing each brand's unique strength and weakness profile.
For each brand, this endpoint calculates what percentage of their mentions falls into each theme.
For example, Nike might be 30% 'comfortable', 25% 'sporty', 45% 'style', while Adidas has a different distribution. Essential for understanding and comparing each brand's positioning and what themes define their perception.
**When to use:** User wants to compare brand profiles, understand a specific brand's strengths/weaknesses distribution, identify what themes define each brand, or find brands with similar perception patterns.
**Common user queries:**
- "What are Nike's main strengths?"
- "Show me the pros breakdown for each brand"
- "Compare cluster distribution across brands"
- "Which themes define Adidas?"
- "What percentage of Nike's perception is about comfort?"
- "Get brand profiles for all competitors"
**Returns:** Object with brand names containing their cluster distributions.
Example: {"Nike": {"Comfortable": "0.30", "Sporty": "0.25", "Style": "0.45"},
"Adidas": {"Comfortable": "0.20", "Sporty": "0.16", "Style": "0.64"}}
Required permission: `read:analysis`.
GET
Cluster Distribution Per Brand
Path Parameters
Query Parameters
Filter by a list of persona IDs. Values should be comma separated, without brackets or spaces. The IDs are resolved to the persona labels recorded on the analysis, so this returns the same rows as the equivalent persona__in call. Use it for analyses that carry persona_ids; analyses predating persona records have none, and must be filtered with persona or persona__in. An ID that is not one of the analysis's personas matches no rows.
Filter by one specific source.
Available options:
claude-3-5-sonnet, claude-4-5-sonnet, claude-4-6-sonnet, claude-4-sonnet, deepseek-chat, deepseek-reasoner, deepseek-v3.2-maas, gemini-1.5-pro, gemini-2.0-flash, gemini-2.5-flash, gemini-2.5-flash-grounded, gemini-2.5-flash-lite, gemini-3-flash-preview, gemini-3.5-flash-lite, google-ai-mode, gpt-3.5-turbo, gpt-4-turbo, gpt-4o, gpt-4o-mini-search, gpt-5, gpt-5.2, gpt-5.4-mini, meta-llama-3.1-70B-instruct-turbo, meta-llama-3.2-70B-instruct-turbo, meta-llama-3.3-70B-instruct-turbo, meta-llama-4-maverick, mistral-7B-instruct, muse-spark-1.2, muse-spark-1.3, perplexity-sonar, rufus Filter by a list of sources. Values should be comma separated, without brackets or spaces
Available options:
claude-3-5-sonnet, claude-4-5-sonnet, claude-4-6-sonnet, claude-4-sonnet, deepseek-chat, deepseek-reasoner, deepseek-v3.2-maas, gemini-1.5-pro, gemini-2.0-flash, gemini-2.5-flash, gemini-2.5-flash-grounded, gemini-2.5-flash-lite, gemini-3-flash-preview, gemini-3.5-flash-lite, google-ai-mode, gpt-3.5-turbo, gpt-4-turbo, gpt-4o, gpt-4o-mini-search, gpt-5, gpt-5.2, gpt-5.4-mini, meta-llama-3.1-70B-instruct-turbo, meta-llama-3.2-70B-instruct-turbo, meta-llama-3.3-70B-instruct-turbo, meta-llama-4-maverick, mistral-7B-instruct, muse-spark-1.2, muse-spark-1.3, perplexity-sonar, rufus Cluster Distribution Per Brand