AI Insights: Brand Themes Across AI Models
Returns AI-generated narrative insights about brand cluster distribution, explaining which brands excel in which themes (e.g., ‘Nike dominates comfort perception’).
This endpoint analyzes brand share by cluster data and generates strategic insights like “Brand X leads in comfort with 45% share but lags in price perception at 12%.” Includes narrative explanations, supporting data, and chart recommendations. Perfect for understanding competitive positioning and identifying brand strengths/weaknesses through AI interpretation.
When to use: User wants to understand brand positioning across perception clusters, identify which brands dominate specific themes, compare brand strengths by attribute category, or spot which clusters are under-represented for a given brand.
Common user queries:
- “Which brands dominate the comfort cluster?”
- “Show brand share by perception theme”
- “Which brand leads in price perception?”
- “Identify under-represented clusters for brand X”
- “Compare brand strengths across perception categories”
- “Which themes does brand Y excel in?”
Returns: Array of insight objects explaining brand-cluster share distribution.
Current model in use: gpt-5.4-mini.
Required permission: read:analysis
Authorizations
Path Parameters
A UUID string identifying the analysis.
A UUID string identifying the organization.
A UUID string identifying the workspace.
Query Parameters
Filter by one specific attribute.
Filter by a list of attributes. Values should be comma separated, without brackets or spaces
Filter by one specific brand.
Filter by a list of brands. Values should be comma separated, without brackets or spaces
The cluster group to retrieve insights for.
all_cons, all_pros Filter by a collection date being equal to the specified date. YYYY-MM-DD format
Filter by a collection date being greater than the specified date. YYYY-MM-DD format
Filter by a collection date being greater than or equal the specified date. YYYY-MM-DD format
Filter by a collection date being less than the specified date. YYYY-MM-DD format
Filter by a collection date being less than or equal the specified date. YYYY-MM-DD format
Filter by one specific country.
Filter by a list of countries. Values should be comma separated, without brackets or spaces
Filter by one specific persona.
Filter by a list of personas. Values should be comma separated, without brackets or spaces
Filter by one specific source.
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, 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, perplexity-sonar, rufus Filter by a list of sources. Values should be comma separated, without brackets or spaces
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, 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, perplexity-sonar, rufus