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AI Visibility & Sentiment

Track how AI models see your brand, analyze sentiment, and monitor citations across ChatGPT, Gemini, Claude, Perplexity, and more.

Visibility
Sentiment
Responses
Competitors by Model
Citations
Prompt Generation

AI Visibility Report

Get AI visibility scores across all tracked prompts. The visibility score measures how prominently your brand appears in AI model responses, from 0 (not visible) to 100 (prominently featured).

POST /v2/reports/visibility

Request Body Parameters

Parameter Type Required Description
start_date string No Start date (YYYY-MM-DD)
end_date string No End date (YYYY-MM-DD)
ai_models array No Filter by AI models (e.g., ["chatgpt", "gemini"])
prompt_ids array No Filter by specific prompt IDs
tags array No Filter by prompt tags (e.g., ["brand_monitoring"])
sub_tags array No Filter by prompt sub-tags (e.g., ["competitor_comparison"])
group_by string No Group results: date, ai_model, prompt, or tag
date_interval string No For date grouping: day, week, or month
limit integer No Max results (1-1000, default: 100)
offset integer No Pagination offset (default: 0)

Example: Visibility by AI Model

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "start_date": "2026-01-01",
       "end_date": "2026-01-31",
       "group_by": "ai_model"
     }' \
     "https://opttab.com/api/v2/reports/visibility"

Response

{
  "success": true,
  "data": [
    {
      "ai_model": "chatgpt",
      "avg_visibility_score": 74.2,
      "avg_confidence_score": 0.85,
      "response_count": 520
    },
    {
      "ai_model": "gemini",
      "avg_visibility_score": 71.1,
      "avg_confidence_score": 0.82,
      "response_count": 380
    },
    {
      "ai_model": "claude",
      "avg_visibility_score": 70.8,
      "avg_confidence_score": 0.79,
      "response_count": 350
    }
  ],
  "meta": {
    "total_rows": 3,
    "group_by": "ai_model",
    "query": {
      "start_date": "2026-01-01",
      "end_date": "2026-01-31"
    }
  }
}

Example: Visibility Over Time

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "start_date": "2026-01-01",
       "end_date": "2026-01-31",
       "group_by": "date",
       "date_interval": "week"
     }' \
     "https://opttab.com/api/v2/reports/visibility"

Example: Visibility Filtered by Tag

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "start_date": "2026-01-01",
       "end_date": "2026-01-31",
       "tags": ["brand_monitoring"],
       "sub_tags": ["competitor_comparison"],
       "group_by": "ai_model"
     }' \
     "https://opttab.com/api/v2/reports/visibility"

Example: Visibility Grouped by Tag

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "start_date": "2026-01-01",
       "end_date": "2026-01-31",
       "group_by": "tag"
     }' \
     "https://opttab.com/api/v2/reports/visibility"

Response (grouped by tag)

{
  "success": true,
  "data": [
    {
      "tag": "brand_monitoring",
      "avg_visibility_score": 76.8,
      "avg_confidence_score": 0.87,
      "response_count": 420
    },
    {
      "tag": "product_research",
      "avg_visibility_score": 71.2,
      "avg_confidence_score": 0.82,
      "response_count": 310
    },
    {
      "tag": "untagged",
      "avg_visibility_score": 65.4,
      "avg_confidence_score": 0.75,
      "response_count": 520
    }
  ],
  "meta": {
    "total_rows": 3,
    "group_by": "tag"
  }
}

Use case (ProductsUp): Pull visibility scores per AI model to show a breakdown chart on your customer's dashboard. Use group_by: "date" with date_interval: "week" to display a trend line over time.

Sentiment Analysis Report

Analyze how positively or negatively AI models talk about your brand. The sentiment score ranges from 0 (very negative) to 100 (very positive), with 50 being neutral.

POST /v2/reports/sentiment

Request Body Parameters

Parameter Type Description
start_date string Start date (YYYY-MM-DD)
end_date string End date (YYYY-MM-DD)
ai_models array Filter by AI models
tags array Filter by prompt tags
sub_tags array Filter by prompt sub-tags
group_by string date or ai_model

Example Request

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "start_date": "2026-01-01",
       "end_date": "2026-01-31",
       "group_by": "ai_model"
     }' \
     "https://opttab.com/api/v2/reports/sentiment"

Response (grouped by AI model)

{
  "success": true,
  "data": [
    {
      "ai_model": "chatgpt",
      "sentiment_score": 72.5,
      "mentions_count": 180,
      "position": 65.4,
      "response_count": 520
    },
    {
      "ai_model": "gemini",
      "sentiment_score": 68.1,
      "mentions_count": 120,
      "position": 59.2,
      "response_count": 380
    }
  ],
  "meta": {
    "total_rows": 2
  }
}

Response (summary — no group_by)

{
  "success": true,
  "data": {
    "sentiment_score": 68.3,
    "raw_sentiment_score": 0.37,
    "mentions_count": 340,
    "position": 62.1,
    "total_responses": 1250,
    "company_name": "Acme Corp",
    "company_website": "https://acme.com"
  }
}

Competitors by AI Model

Get competitors with visibility scores grouped by AI model. See which competitors are mentioned or visible in each AI model's responses (e.g., ChatGPT vs Gemini vs Claude). This complements the visibility report by breaking down competitor presence per model.

POST /v2/reports/competitors-by-model

Request Body Parameters

Parameter Type Required Description
start_date string No Start date (YYYY-MM-DD)
end_date string No End date (YYYY-MM-DD)
ai_models array No Filter by AI models (e.g., ["chatgpt", "gemini"])
prompt_ids array No Filter by specific prompt IDs
tags array No Filter by prompt tags (e.g., ["brand_monitoring"])
sub_tags array No Filter by prompt sub-tags (e.g., ["competitor_comparison"])
limit integer No Max AI model groups to return (1–500, default: 50)
offset integer No Pagination offset (default: 0)

Example Request

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "start_date": "2026-01-01",
       "end_date": "2026-01-31",
       "ai_models": ["chatgpt", "gemini"],
       "tags": ["brand_monitoring"],
       "sub_tags": ["competitor_comparison"],
       "limit": 50,
       "offset": 0
     }' \
     "https://opttab.com/api/v2/reports/competitors-by-model"

Response

{
  "success": true,
  "data": [
    {
      "ai_model": "ChatGPT",
      "competitors": [
        {
          "name": "Competitor A",
          "visibility_score": 75,
          "mentions_count": 12,
          "total_responses": 20,
          "favicon_url": "https://example.com/favicon.ico"
        },
        {
          "name": "Competitor B",
          "visibility_score": 50,
          "mentions_count": 8,
          "total_responses": 20,
          "favicon_url": null
        }
      ]
    },
    {
      "ai_model": "Gemini",
      "competitors": [
        {
          "name": "Competitor A",
          "visibility_score": 68,
          "mentions_count": 10,
          "total_responses": 18,
          "favicon_url": "https://example.com/favicon.ico"
        }
      ]
    }
  ],
  "meta": {
    "total_rows": 2,
    "limit": 50,
    "offset": 0
  }
}

Use case: Compare how different AI models rank your competitors. For example, ChatGPT may mention Competitor A more often than Gemini. Use this endpoint to power a "Competitors by AI Model" chart or table in your dashboard.

AI Responses

Access raw AI model responses with full text, visibility scores, brand rankings, and products mentioned. Useful for detailed analysis of how each AI model responds to your tracked prompts.

POST /v2/reports/responses

Request Body Parameters

Parameter Type Description
start_date / end_date string Date range filter (YYYY-MM-DD)
ai_models array Filter by AI models
prompt_ids array Filter by prompt IDs
tags array Filter by prompt tags
sub_tags array Filter by prompt sub-tags
limit / offset integer Pagination (max 500 per request)

Example Request

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "start_date": "2026-01-01",
       "end_date": "2026-01-31",
       "ai_models": ["chatgpt"],
       "limit": 10
     }' \
     "https://opttab.com/api/v2/reports/responses"

Response

{
  "success": true,
  "data": [
    {
      "id": 12345,
      "prompt_text": "What are the best project management tools?",
      "ai_model": "chatgpt",
      "response_text": "Here are some of the best project management tools...",
      "visibility_score": 78.5,
      "confidence_score": 0.89,
      "position": 2,
      "brand_rankings": ["Asana", "Trello", "Acme PM"],
      "products": ["Acme Project Manager Pro"],
      "generated_at": "2026-01-15T14:30:00Z"
    }
  ],
  "meta": {
    "total_rows": 520,
    "limit": 10,
    "offset": 0
  }
}

Citations Report

Track which URLs AI models cite in their responses. Monitor how often your website, blog posts, or product pages are referenced as sources by ChatGPT, Gemini, Perplexity, and others.

POST /v2/reports/citations

Request Body Parameters

Parameter Type Description
start_date / end_date string Date range filter
ai_models array Filter by AI models
tags array Filter by prompt tags
sub_tags array Filter by prompt sub-tags
domain_filter string Filter citations containing this domain
limit / offset integer Pagination (max 1000)

Example: Get My Domain's Citations

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "start_date": "2026-01-01",
       "end_date": "2026-01-31",
       "domain_filter": "acme.com",
       "limit": 50
     }' \
     "https://opttab.com/api/v2/reports/citations"

Response

{
  "success": true,
  "data": [
    {
      "response_id": 12345,
      "prompt_text": "What are the best project management tools?",
      "ai_model": "chatgpt",
      "source_url": "https://acme.com/blog/best-pm-tools",
      "source_title": "The 10 Best Project Management Tools in 2026",
      "source_position": 1,
      "generated_at": "2026-01-15T14:30:00Z"
    },
    {
      "response_id": 12346,
      "prompt_text": "Compare PM tools for enterprise",
      "ai_model": "perplexity",
      "source_url": "https://acme.com/enterprise-solutions",
      "source_title": "Enterprise Project Management - Acme",
      "source_position": 3,
      "generated_at": "2026-01-16T09:15:00Z"
    }
  ],
  "meta": {
    "total_rows": 89,
    "limit": 50,
    "offset": 0
  }
}

Prompt Management

Manage the prompts you're tracking. Prompts are queries that Opttab sends to AI models on your behalf to monitor how they respond. Each prompt can be categorized with a tag and sub_tag for organizing and filtering.

GET /v2/org/prompts

List all tracked prompts in your workspace. Each prompt includes visibility score (overall average across AI models) and visibility by AI model (visibility_score, visibility_by_model). Supports filtering by tag and sub_tag query parameters.

Query Parameters

Parameter Type Description
per_page integer Results per page (max 200, default: 50)
tag string Filter by a single tag
tags[] array Filter by multiple tags
sub_tag string Filter by a single sub-tag
sub_tags[] array Filter by multiple sub-tags

Example: List all prompts

curl -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     "https://opttab.com/api/v2/org/prompts?per_page=50"

Example: Filter prompts by tag

curl -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     "https://opttab.com/api/v2/org/prompts?tag=brand_monitoring"

Response

Each item in data includes visibility_score (overall average, or null if no responses yet) and visibility_by_model (object of AI model key → score; empty object if none).

{
  "success": true,
  "data": [
    {
      "id": 1,
      "prompt_text": "What are the best CRM tools for small businesses?",
      "ai_models": ["chatgpt", "gemini", "claude"],
      "locations": [],
      "tag": "brand_monitoring",
      "sub_tag": "competitor_comparison",
      "is_active": true,
      "run_interval": "weekly",
      "last_run_at": "2026-02-10T08:00:00Z",
      "created_at": "2026-01-15T10:30:00Z",
      "visibility_score": 82.33,
      "visibility_by_model": {
        "chatgpt": 85.5,
        "gemini": 72.0,
        "claude": 90.0
      }
    }
  ],
  "meta": {
    "current_page": 1,
    "per_page": 50,
    "total": 1,
    "last_page": 1
  }
}
POST /v2/org/prompts

Create a new tracked prompt with optional tag and sub_tag for categorization.

Request Body Parameters

Parameter Type Required Description
prompt_text string Yes The prompt to track (max 2000 chars)
ai_models array No AI models to track
tag string No Category tag (max 255 chars)
sub_tag string No Sub-category tag (max 255 chars)
run_interval string No daily, weekly, or monthly
is_active boolean No Whether the prompt is active (default: true) 
curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "prompt_text": "What are the best CRM tools for small businesses?",
       "ai_models": ["chatgpt", "gemini", "claude"],
       "tag": "brand_monitoring",
       "sub_tag": "competitor_comparison",
       "run_interval": "week",
       "is_active": true
     }' \
     "https://opttab.com/api/v2/org/prompts"

Response

{
  "success": true,
  "data": {
    "id": 42,
    "prompt_text": "What are the best CRM tools for small businesses?",
    "tag": "brand_monitoring",
    "sub_tag": "competitor_comparison",
    "created_at": "2026-02-14T10:30:00Z"
  }
}

Category Visibility Prompt Generation

Generate AI visibility prompts from categories, brands, and intents using the Category Visibility engine. The API cross-matches brands with categories (e.g., only "Levi's" with "Jeans"), then generates natural-language questions per intent. You can then save those prompts and start receiving AI model responses in the background.

Typical flow: (1) POST /api/v2/prompts/generate to get suggested prompts → (2) POST /api/v2/prompts/store to save them and trigger AI response generation → (3) GET /api/v2/prompts/{id}/responses to poll for results (allow 30–120 seconds per model).

POST /v2/prompts/generate

Generate prompts from categories, brands, and intents. Does not save prompts; use the returned array with POST /api/v2/prompts/store to save and start AI response generation.

Request Body Parameters

Parameter Type Required Description
categories string Yes Comma-separated categories (e.g., Jeans, Sneakers, Jackets)
brands string Yes Comma-separated brands (e.g., Levi's, Nike, Adidas)
intents array Yes One or more: customer_focus, competition_focus, brand_focus, transaction_focus

Intents: customer_focus — customer needs, reviews, recommendations; competition_focus — brand vs competitor; brand_focus — reputation, quality; transaction_focus — buying, pricing, where to buy.

Example

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "categories": "Jeans, Sneakers",
       "brands": "Levi'\''s, Nike",
       "intents": ["customer_focus", "competition_focus"]
     }' \
     "https://opttab.com/api/v2/prompts/generate"

Response

{
  "success": true,
  "data": {
    "prompts": [
      {
        "text": "What are the most comfortable Levi's jeans for everyday wear?",
        "tag": "Jeans",
        "sub_tag": "Levi's",
        "intent": "customer_focus",
        "intent_label": "Customer Focus"
      }
    ],
    "total": 40,
    "hint": "Use POST /api/v2/prompts/store with these prompts to save them and start generating AI responses."
  },
  "meta": {
    "categories": "Jeans, Sneakers",
    "brands": "Levi's, Nike",
    "intents": ["customer_focus", "competition_focus"]
  }
}
POST /v2/prompts/store

Save generated prompts and immediately dispatch AI response generation jobs. Each prompt is tracked in your workspace and AI models start generating responses in the background. Use the output from POST /api/v2/prompts/generate or provide your own prompt objects.

Request Body Parameters

Parameter Type Required Description
prompts array Yes Array of { text, tag?, sub_tag?, intent? } (max 200)
ai_models array Yes Models to run: chatgpt, gemini, claude, grok, perplexity, deepseek, mistral, ai-overviews
run_interval string No day, week, or month (default: week)
locations array No Location codes (e.g., ["us"], default: ["us"])

Example

curl -X POST \
     -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     -H "Content-Type: application/json" \
     -d '{
       "prompts": [
         {
           "text": "What are the most comfortable Levi'\''s jeans?",
           "tag": "Jeans",
           "sub_tag": "Levi'\''s",
           "intent": "customer_focus"
         }
       ],
       "ai_models": ["chatgpt", "gemini", "claude"],
       "run_interval": "week",
       "locations": ["us"]
     }' \
     "https://opttab.com/api/v2/prompts/store"

Response

{
  "success": true,
  "data": {
    "prompts": [
      {
        "id": 101,
        "prompt_text": "What are the most comfortable Levi's jeans?",
        "tag": "Jeans",
        "sub_tag": "Levi's",
        "intent": "customer_focus",
        "ai_models": ["ChatGPT", "Gemini", "Claude"],
        "run_interval": "week",
        "created_at": "2026-02-14T12:00:00Z"
      }
    ],
    "total_created": 1,
    "jobs_dispatched": 1,
    "ai_models": ["ChatGPT", "Gemini", "Claude"],
    "hint": "AI responses are being generated in the background. Use GET /api/v2/prompts/{id}/responses to retrieve them (allow 30-120 seconds per model)."
  }
}
GET /v2/prompts/{id}/responses

Get AI-generated responses for a specific prompt. Responses are created asynchronously after storing prompts; each model produces its own response with visibility score, confidence, sources, and brand rankings.

Path & Query Parameters

Parameter Type Description
id integer Prompt ID (path)
ai_models[] array Optional filter by AI model names
limit integer Max results (1–200, default: 50)
offset integer Pagination offset (default: 0)

Example

curl -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     "https://opttab.com/api/v2/prompts/101/responses"

Response

{
  "success": true,
  "data": [
    {
      "id": 5001,
      "ai_model": "ChatGPT",
      "response_text": "Levi's offers several comfortable options...",
      "visibility_score": 100,
      "confidence_score": 0.92,
      "position": 1,
      "sources": [],
      "brand_rankings": [],
      "products": [],
      "generated_at": "2026-02-14T12:02:15Z"
    }
  ],
  "meta": {
    "prompt": {
      "id": 101,
      "prompt_text": "What are the most comfortable Levi's jeans?",
      "tag": "Jeans",
      "sub_tag": "Levi's",
      "intent": "customer_focus"
    },
    "total_responses": 3,
    "models_completed": ["ChatGPT", "Gemini", "Claude"],
    "models_pending": [],
    "is_complete": true,
    "limit": 50,
    "offset": 0
  }
}

Tags & Sub-Tags

Tags and sub-tags provide a flexible taxonomy for organizing your prompts. Use them to categorize prompts by topic, intent, product line, or any custom hierarchy. All report endpoints support tags and sub_tags filters to scope data to specific categories.

GET /v2/org/tags

List all unique tags in your workspace with prompt counts and associated sub-tags.

Example

curl -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     "https://opttab.com/api/v2/org/tags"

Response

{
  "success": true,
  "data": [
    {
      "tag": "brand_monitoring",
      "prompt_count": 12,
      "sub_tags": ["competitor_comparison", "market_position", "sentiment_tracking"]
    },
    {
      "tag": "product_research",
      "prompt_count": 8,
      "sub_tags": ["feature_comparison", "pricing", "reviews"]
    },
    {
      "tag": "industry_trends",
      "prompt_count": 5,
      "sub_tags": ["emerging_tech", "market_analysis"]
    }
  ],
  "meta": { "total": 3 }
}
GET /v2/org/tags/{tag}/sub-tags

List all sub-tags for a specific tag with their prompt counts.

Example

curl -H "X-API-Key: opttab_xxxxxxxxxxxxxxxxxxxx" \
     "https://opttab.com/api/v2/org/tags/brand_monitoring/sub-tags"

Response

{
  "success": true,
  "data": [
    { "sub_tag": "competitor_comparison", "prompt_count": 5 },
    { "sub_tag": "market_position", "prompt_count": 4 },
    { "sub_tag": "sentiment_tracking", "prompt_count": 3 }
  ],
  "meta": {
    "tag": "brand_monitoring",
    "total": 3
  }
}

Tip: Tags and sub-tags are free-form strings. You can use any naming convention. Common patterns include topic-based tags (brand_monitoring, product_research) with sub-tags for specifics (competitor_comparison, pricing).

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