> ## Documentation Index > Fetch the complete documentation index at: https://docs.greenflash.ai/llms.txt > Use this file to discover all available pages before exploring further. # Get Segment Analytics > Get aggregated analytics for a specific segment including sentiment, safety metrics, topics, keywords, and an LLM-generated summary. **Requires Growth+ plan or higher.** Rate limited based on your plan's `maxAnalysesPerHour`. Cached results (less than 2 hours old) do not consume rate limit points. ## OpenAPI ````yaml https://www.greenflash.ai/api/openapi get /segments/{segmentId}/analytics openapi: 3.1.0 info: title: Greenflash API Reference version: 1.0.0 description: >- Greenflash endpoints for capturing interactions, managing prompts, and identifying users. servers: - url: https://www.greenflash.ai/api/v1 description: Greenflash API v1 security: [] tags: - name: Interactions description: Capture interactions between users and AI - name: Business Events description: Capture business events - name: Analytics description: Understand chat and agentic interactions analyses - name: Inbox description: Review flagged conversations - name: Segments description: Manage user segments - name: Prompts description: Manage prompts - name: Chat description: Stream chat and agentic conversations - name: Models description: Manage AI models - name: Products description: Manage products - name: Users description: Manage users - name: Organizations description: Manage organizations paths: /segments/{segmentId}/analytics: get: tags: - Analytics - Segments summary: Get Segment Analytics description: >- Get aggregated analytics for a specific segment including sentiment, safety metrics, topics, keywords, and an LLM-generated summary. **Requires Growth+ plan or higher.** Rate limited based on your plan's `maxAnalysesPerHour`. Cached results (less than 2 hours old) do not consume rate limit points. parameters: - schema: type: string format: uuid description: The segment ID to get analytics for. required: true description: The segment ID to get analytics for. name: segmentId in: path - schema: type: string format: uuid description: Filter analytics by product ID. required: false description: Filter analytics by product ID. name: productId in: query - schema: type: string format: uuid description: Filter analytics by version ID. required: false description: Filter analytics by version ID. name: versionId in: query responses: '200': description: Segment analytics retrieved successfully content: application/json: schema: $ref: '#/components/schemas/GetSegmentAnalyticsResponse' example: averageUserSentiment: label: positive score: 0.35 averageChangeInUserSentiment: label: stable score: 0.02 averageFrustration: label: low score: 0.15 averageStruggle: label: low score: 0.12 averageCommercialIntent: label: high score: 0.68 averageConversationQualityIndex: 8.1 averageConversationRating: 4.5 topics: - name: pricing plans count: 120 - name: feature requests count: 95 - name: integrations count: 73 topicGroups: - name: Product & Pricing count: 215 - name: Technical count: 148 keywords: - name: enterprise count: 89 - name: API count: 76 - name: upgrade count: 54 summary: overview: >- Power users show strong engagement and positive sentiment. Key interests are pricing plans and integrations. recommendations: - >- Consider offering enterprise-tier API access to this segment. - >- Feature request volume is high — prioritize integration docs. hallucinationCount: total: 3 percentage: 0.4 jailbreakCount: total: 0 percentage: 0 userBiasCount: total: 1 percentage: 0.1 modelBiasCount: total: 0 percentage: 0 userToxicityCount: total: 2 percentage: 0.3 modelToxicityCount: total: 0 percentage: 0 totalConversations: 780 participantCount: 234 '403': description: Requires paid plan content: application/json: schema: type: object properties: success: type: boolean description: Whether the API call was successful (false for errors). error: type: string description: Error message describing what went wrong. description: Error response for get segment analytics operations. example: success: false error: This endpoint requires a Growth plan or higher '404': description: Segment not found content: application/json: schema: type: object properties: success: type: boolean description: Whether the API call was successful (false for errors). error: type: string description: Error message describing what went wrong. description: Error response for get segment analytics operations. example: success: false error: Segment not found '429': description: Rate limit exceeded content: application/json: schema: type: object properties: success: type: boolean description: Whether the API call was successful (false for errors). error: type: string description: Error message describing what went wrong. description: Error response for get segment analytics operations. example: success: false error: >- Rate limit exceeded for analytics requests. Please try again later. '500': description: Server error content: application/json: schema: type: object properties: success: type: boolean description: Whether the API call was successful (false for errors). error: type: string description: Error message describing what went wrong. description: Error response for get segment analytics operations. security: - bearerAuth: [] x-codeSamples: - lang: JavaScript source: >- import Greenflash from 'greenflash'; const client = new Greenflash({ apiKey: process.env['GREENFLASH_API_KEY'], // This is the default and can be omitted }); const getSegmentAnalyticsResponse = await client.segments.getSegmentAnalytics( '182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e', ); console.log(getSegmentAnalyticsResponse.averageChangeInUserSentiment); - lang: Python source: >- import os from greenflash import Greenflash client = Greenflash( api_key=os.environ.get("GREENFLASH_API_KEY"), # This is the default and can be omitted ) get_segment_analytics_response = client.segments.get_segment_analytics( segment_id="182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", ) print(get_segment_analytics_response.average_change_in_user_sentiment) components: schemas: GetSegmentAnalyticsResponse: type: object properties: averageUserSentiment: type: object properties: label: type: string score: type: number required: - label - score description: Average sentiment across all conversations. averageChangeInUserSentiment: type: object properties: label: type: string score: type: number required: - label - score description: Average change in user sentiment. averageFrustration: type: object properties: score: type: number label: type: string required: - score - label description: Average frustration level. averageStruggle: type: object properties: score: type: number label: type: string required: - score - label description: Average struggle level. averageCommercialIntent: type: object properties: score: type: number label: type: string required: - score - label description: Average commercial intent. averageConversationQualityIndex: type: - number - 'null' description: Average conversation quality index. averageConversationRating: type: - number - 'null' description: Average conversation rating. topics: type: array items: type: object properties: name: type: string count: type: number required: - name - count description: Topics discussed across conversations. topicGroups: type: array items: type: object properties: name: type: string count: type: number required: - name - count description: Topic groups across conversations. keywords: type: array items: type: object properties: name: type: string count: type: number required: - name - count description: Keywords extracted from conversations. summary: type: - object - 'null' additionalProperties: {} description: LLM-generated summary of the segment. hallucinationCount: type: object properties: total: type: number percentage: type: number required: - total - percentage description: Number of hallucinations detected. jailbreakCount: type: object properties: total: type: number percentage: type: number required: - total - percentage description: Number of jailbreak attempts detected. userBiasCount: type: object properties: total: type: number percentage: type: number required: - total - percentage description: Number of user bias detections. modelBiasCount: type: object properties: total: type: number percentage: type: number required: - total - percentage description: Number of model bias detections. userToxicityCount: type: object properties: total: type: number percentage: type: number required: - total - percentage description: Number of user toxicity detections. modelToxicityCount: type: object properties: total: type: number percentage: type: number required: - total - percentage description: Number of model toxicity detections. totalConversations: type: number description: Total number of conversations in the segment. participantCount: type: number description: Total number of participants in the segment. required: - averageUserSentiment - averageChangeInUserSentiment - averageFrustration - averageStruggle - averageCommercialIntent - topics - topicGroups - keywords - summary - hallucinationCount - jailbreakCount - userBiasCount - modelBiasCount - userToxicityCount - modelToxicityCount - totalConversations - participantCount securitySchemes: bearerAuth: type: http scheme: bearer ````