> ## Documentation Index
> Fetch the complete documentation index at: https://docs.inop.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Overview: Compensation Analytics API

> v1.0.0

<Note>
  If you need any help or would like more information, please feel free to reach out to our support team.
</Note>

## Overview

The **Compensation Analytics API** provides comprehensive, real-time compensation data for strategic job benchmarking and market analysis. Our robust dataset is sourced from verified job postings and compensation data across multiple industries and geographic regions.

### Key Features

* **Real-time Data**: Access to current compensation trends and market rates
* **Comprehensive Filtering**: Filter by location, industry, company size, job level, skills, and more
* **Statistical Analysis**: Get median, percentile distributions, and trend analytics
* **Multi-dimensional Comparisons**: Compare across locations, companies, and market segments
* **Skills Integration**: Compensation data enriched with skills and career taxonomy information

## API Endpoints

The Compensation Analytics module consists of three specialized endpoints, each designed for specific use cases:

### 1. General Compensation Insights API

**Endpoint**: `/api/v1/compensation/insights`

Provides foundational compensation data and analytics for job benchmarking. Perfect for salary research, market analysis, and compensation planning.

**Use Cases**:

* Salary benchmarking for specific roles
* Market rate analysis
* Compensation trend research
* Budget planning for hiring
* Compliance with the [EU Pay Transparency Directive](https://ec.europa.eu/commission/presscorner/detail/en/ip_23_1651)

### 2. Compensation Location Comparison API

**Endpoint**: `/api/v1/compensation/location-comparison`

Extends the general insights with multi-location comparison capabilities. Compare compensation data across different geographic regions to understand location-based pay differentials.

**Use Cases**:

* Geographic pay equity analysis
* Remote work compensation adjustments
* Multi-location hiring strategies
* Cost of living compensation modeling

### 3. Compensation Company Benchmark Tool API

**Endpoint**: `/api/v1/compensation/company-benchmark`

Provides company-specific compensation benchmarking against market competitors. Compare your organization's compensation packages with similar companies in your industry and size category.

**Use Cases**:

* Competitive compensation analysis
* Retention strategy development
* Market positioning assessment
* Executive compensation benchmarking

## Available Filters

All endpoints support comprehensive filtering options:

### Core Filters

* **Location**: Country, city, region, remote work options
* **Industry/Career Area**: Technology, Finance, Healthcare, Marketing, etc.
* **Company Size**: Micro (1-10), Small (11-50), Small-Medium (51-200), Medium (201-500), Medium-Large (501-1000), Large (1k-5k), Enterprise (5K-10K), Mega Enterprise (10K+)
* **Job Level**: Intern, Entry, Intermediate, Mid, Mid-Senior, Senior, Executive
* **Experience Level**: 0-6 months, 1-2 years, 2-4 years, 4-8 years, 8-10 years, 10+ years

### Advanced Filters

* **Skills**: Filter by required technical and soft skills
* **Compensation Type**: Hourly, daily, weekly, monthly, annual
* **Currency**: Multiple currency support with conversion
* **Time Range**: Filter by year and quarter
* **Company Type**: Public, private, startup, non-profit
* **Employment Type**: Full-time, part-time, contract, freelance

## Data Sources & Quality

Our compensation data is sourced from:

* Verified job postings from major job boards
* User-reported salaries
* Publicly available salary data
* Market research and salary surveys
* Government labor statistics
* Professional networking platforms

All data undergoes quality validation including outlier detection and source verification to ensure accuracy and reliability.

## Response Data Structure

### Core Compensation Metrics

```json theme={null}
{
  "compensation": {
    "base_salary": {
      "min": 120000,
      "max": 180000,
      "median": 150000,
      "percentile_25": 135000,
      "percentile_75": 165000,
      "currency": "USD"
    },
    "total_compensation": {
      "min": 140000,
      "max": 220000,
      "median": 185000,
      "percentile_25": 160000,
      "percentile_75": 200000,
      "currency": "USD"
    },
    "additional_compensation": {
      "bonus": {
        "min": 5000,
        "max": 25000,
        "median": 15000
      },
      "equity": {
        "offered": true,
        "percentage_offering": 85
      }
    }
  }
}
```

### Position & Skills Information

```json theme={null}
{
  "position": {
    "id": "550e8400-e29b-41d4-a716-446655440000",
    "name": "Senior Software Engineer",
    "short_title": "Sr. Software Engineer",
    "category": "Engineering",
    "career_area": "Technology",
    "position_group": "Software Development",
    "level": "Senior",
    "is_trending": true,
    "similar_positions": [
      "Senior Developer",
      "Senior Backend Engineer",
      "Senior Full Stack Engineer"
    ]
  },
  "skills": [
    {
      "name": "Python",
      "category": "Programming Languages",
      "relevance": "high",
      "market_demand": 95
    },
    {
      "name": "AWS",
      "category": "Cloud Platforms",
      "relevance": "high",
      "market_demand": 88
    }
  ]
}
```

### Location & Company Context

```json theme={null}
{
  "location": {
    "city": "San Francisco",
    "state": "California",
    "country": "United States",
    "region": "Bay Area",
    "remote_friendly": true,
    "cost_of_living_index": 1.85
  },
  "company": {
    "size_category": "Enterprise",
    "industry": "Technology",
    "type": "Public",
    "employee_count_range": "1000-5000"
  },
  "market_context": {
    "sample_size": 245,
    "data_freshness": "2024-Q3",
    "confidence_level": 95,
    "market_trend": "increasing"
  }
}
```

## Getting Started

To begin using the Compensation Analytics API:

1. **Authentication**: Obtain your API key from the dashboard
2. **Choose Endpoint**: Select the appropriate endpoint based on your use case
3. **Set Parameters**: Configure your filters and comparison parameters
4. **Make Request**: Send your API request with proper headers
5. **Analyze Data**: Process the comprehensive compensation insights

<Tip>
  Start with the General Compensation Insights API to understand the base data structure, then explore the specialized comparison endpoints for more advanced analysis.
</Tip>

For detailed endpoint documentation, parameter specifications, and code examples, refer to the individual endpoint documentation pages.