> ## Documentation Index > Fetch the complete documentation index at: https://docs.getaftercare.com/llms.txt > Use this file to discover all available pages before exploring further. # Evaluate Data Quality > Evaluates the quality of survey responses for potential issues ## OpenAPI ````yaml POST /api/v1/data-quality openapi: 3.0.0 info: title: Followup Generation API version: 1.0.0 description: API for generating followup questions based on survey responses contact: name: API Support email: justin@getaftercare.com license: name: Apache 2.0 url: https://www.apache.org/licenses/LICENSE-2.0.html servers: - url: https://surveys.getaftercare.com description: Production server - url: https://staging.aftercareai.com description: Staging server security: - ApiKeyAuth: [] tags: - name: Followups description: Operations related to followup question generation - name: Data Quality description: Operations related to response data quality evaluation - name: Coding description: Operations related to coding survey responses paths: /api/v1/data-quality: post: tags: - Data Quality summary: Evaluate survey response quality description: Evaluates the quality of survey responses for potential issues operationId: evaluateDataQuality parameters: - $ref: '#/components/parameters/X-Request-Encoding' requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/DataQualityRequest' responses: '200': description: Successfully evaluated survey quality content: application/json: schema: $ref: '#/components/schemas/DataQualityResponse' example: numIssues: 1 qualityScore: 30 demeritScore: 70 evaluations: - surveyEntry: question: How satisfied were you with our service? answer: I really love playing tennis with my friends on Fridays numIssues: 1 qualityScore: 30 demeritScore: 70 qualityIssueChecks: - type: Irrelevant score: 10 isIssue: true - type: Nonsensical score: 80 isIssue: true - type: Incomplete score: 60 isIssue: false - type: Low Effort score: 95 isIssue: true - type: LLM Generated score: 80 isIssue: false - type: Self Duplicated score: 30 isIssue: false - type: Shared Duplicate score: 30 isIssue: false aftercareResponseIdentifier: 12345 '400': description: Bad request - invalid input parameters content: application/json: schema: $ref: '#/components/schemas/Error' example: code: INVALID_REQUEST message: Invalid request parameters details: question: Question is required '403': description: Forbidden - Missing or invalid API key content: application/json: schema: $ref: '#/components/schemas/Error' example: code: INVALID_API_KEY message: Invalid or missing API key '404': description: Resource not found content: application/json: schema: $ref: '#/components/schemas/Error' example: code: NOT_FOUND message: Requested resource not found '500': description: Internal server error content: application/json: schema: $ref: '#/components/schemas/Error' example: code: INTERNAL_ERROR message: An unexpected error occurred '504': description: Gateway timeout content: application/json: schema: $ref: '#/components/schemas/Error' example: code: GATEWAY_TIMEOUT message: The request timed out security: - ApiKeyAuth: [] x-codeSamples: - lang: JavaScript source: |- const response = await api.quality.evaluate({ surveyName: 'Customer Satisfaction', surveyEntries: [{ question: 'How satisfied are you?', answer: 'I really love playing tennis with my friends on Fridays' }] }); - lang: Python source: |- response = api.quality.evaluate( survey_name='Customer Satisfaction', survey_entries=[{ 'question': 'How satisfied are you?', 'answer': 'I really love playing tennis with my friends on Fridays' }] ) components: parameters: X-Request-Encoding: in: header name: X-Request-Encoding schema: type: string enum: - unicode - html default: unicode required: false description: >- Specifies the encoding format of the request data. Use `html` if you are sending data that HTML entity encodes non-ASCII characters. schemas: DataQualityRequest: type: object required: - surveyEntries properties: surveyName: type: string description: The name of the survey as it will appear in the Aftercare platform surveyDescription: type: string description: >- A description of the survey purpose and background. It will be used to give the AI more context around specific aspects of the survey (e.g. brand/product names, movie names, etc.) surveyEntries: type: array description: >- The collection of question-answer pairs to evaluate. If a respondent does not answer a question, DO NOT include that question in the surveyEntries array. items: $ref: '#/components/schemas/SurveyEntry' surveyIdentifier: type: string description: >- Optional unique identifier for the survey. Aftercare will use this to build a data model to associate questions and answers with the survey. responseIdentifier: type: string description: >- Optional unique identifier for a respondent's entire response to a survey. Aftercare will use this to build a data model tie together questions and answer pairs for a single response. aftercareResponseIdentifier: type: number description: >- Optional unique identifier for the survey response. If not provided, Aftercare will generate one. This identifier is useful for tracking survey responses that are submitted in multiple parts or over time. If both a responseIdentifier and aftercareResponseIdentifier are provided, Aftercare will use the aftercareResponseIdentifier. qualityIssues: type: array items: $ref: '#/components/schemas/QualityIssueType' description: >- Optional array of specific quality issues to evaluate. If not provided, all applicable quality issues will be checked. detectionMode: $ref: '#/components/schemas/QualityDetectionMode' DataQualityResponse: type: object required: - numIssues - qualityScore - demeritScore - evaluations - aftercareResponseIdentifier properties: numIssues: type: integer description: Number of quality issues detected across all survey entries minimum: 0 hasIssues: type: boolean description: If Aftercare has detected any quality issues for this response qualityScore: type: number description: >- A score between 0 and 100 that represents the overall quality of the survey response. (Deprecated: use demeritScore instead) minimum: 0 maximum: 100 demeritScore: type: number description: >- A score between 0 and 100 that represents the overall quality of the survey response. The score is an average of the quality scores across all survey entries. The higher the score, the greater the likelihood and severity of data quality issues. minimum: 0 maximum: 100 evaluations: type: array items: $ref: '#/components/schemas/SurveyEntryEvaluation' aftercareResponseIdentifier: type: number description: Unique identifier for the survey response generated by Aftercare Error: type: object required: - code - message properties: code: type: string description: Error code example: INVALID_REQUEST message: type: string description: Error message example: Invalid request parameters details: type: object description: Additional error details example: question: Question is required SurveyEntry: type: object required: - question - answer properties: question: type: string description: The question that was asked to the respondent questionContext: type: string description: >- A description of what you are trying to learn from the respondent for this question answer: type: string description: The answer to the question provided by the respondent questionIdentifier: type: string description: >- Optional unique identifier for the question. Aftercare will use this to build a data model to track questions across a survey parentQuestionIdentifier: type: string description: Optional identifier of a previous question in a follow-up thread keyEvents: type: array items: $ref: '#/components/schemas/SurveyEntryKeyStroke' description: An optional array of key strokes. pasteEvents: type: array items: $ref: '#/components/schemas/SurveyEntryPaste' description: An optional array of paste events. honeypotPhrase: type: string description: >- Optional string. If provided, Aftercare will check if the response contains any honey pot words. QualityIssueType: type: string enum: - Nonsensical - Irrelevant - Low Effort - LLM Generated - Repeated Answers - Duplicate Answers description: >- Types of quality issues that can be detected in survey responses. * `Nonsensical` - Response lacks logical meaning or sense. Likely gibberish. * `Irrelevant` - Response does not address the question. * `Low Effort` - Respondent did not put in much effort to answer the question. Lacks detail or concrete examples. * `LLM Generated` - Response appears to be generated by AI. * `Self Duplicated` - Responses from the same respondent contain duplicated content across multiple answers. Only evaluated when multiple survey entries are provided or if a survey identifier and response identifier is provided. * `Shared Duplicate` - Responses contain duplicated content across different respondents for the same question. Only evaluated if survey identifiers and question identifiers are provided. QualityDetectionMode: type: string enum: - Responsiveness - Authenticity - Composite description: >- The mode in which Aftercare will evaluate the quality of the survey responses. * `Responsiveness` - Checks for poor responses * `Authenticity` - Checks for fraudulent responses * `Composite` - Checks for all quality issues If both a detectionMode and qualityIssues are provided, Aftercare will use the detection mode. SurveyEntryEvaluation: type: object required: - surveyEntry - numIssues - qualityScore - demeritScore - qualityIssueChecks properties: surveyEntry: $ref: '#/components/schemas/SurveyEntry' numIssues: type: integer description: Number of quality issues detected minimum: 0 hasIssues: type: boolean description: If Aftercare has detected any quality issues for this survey entry qualityScore: type: number description: >- A score between 0 and 100 that represents the overall quality of the individual survey entry. (Deprecated: use demeritScore instead) minimum: 0 maximum: 100 deprecated: true demeritScore: type: number description: >- A score between 0 and 100 that represents the overall quality of the individual survey entry. The score is a weighted average of the quality issue scores. The higher the score, the greater the likelihood and severity of data quality issues. minimum: 0 maximum: 100 qualityIssueChecks: type: array items: $ref: '#/components/schemas/QualityIssueCheck' SurveyEntryKeyStroke: type: object required: - k - t - ht - c properties: k: type: string description: Key value (e.g., "a", "Enter") t: type: number description: Keydown timestamp (from performance.now()) ht: type: number description: Hold time of the key c: type: string description: Physical key code (e.g., "KeyA", "Enter") SurveyEntryPaste: type: object required: - t - c properties: t: type: number description: Timestamp of the paste event c: type: string description: Clipboard content that was pasted QualityIssueCheck: type: object required: - type - score - isIssue properties: type: $ref: '#/components/schemas/QualityIssueType' score: type: number description: >- Score between 0-100 for this quality issue. The higher the score, the greater the likelihood and severity of the quality issue. minimum: 0 maximum: 100 isIssue: type: boolean description: Indicates if this issue was detected evidence: type: string description: ' An optional string, evidence provides the reason for the quality issue score.' securitySchemes: ApiKeyAuth: type: apiKey in: header name: X-Aftercare-Key description: API key for authentication ````