# Dictionary: Multi-source Company Data
Find all data fields with explanations available in the Multi-source Company data.
Each category includes a table listing the available data fields, their explanations, and data types.
{% tabs %}
{% tab title="Data fields per category" %}
1. [Metadata](#metadata)
2. [Firmographics](#firmographics)
3. [Company updates](#company-updates)
4. [Locations](#locations)
5. [Public contact details](#public-contact-details)
6. [Follower counts & changes](#follower-counts-and-changes)
7. [Competitors](#competitors)
8. [Product overview](#product-overview)
9. [Financials](#financials)
10. [Funding](#funding)
11. [Acquisitions](#acquisitions)
12. [News features](#news-features)
13. [Technographics](#technographics)
14. [Company websites and social media](#company-websites-and-social-media)
15. [Website traffic](#website-traffic)
16. [Employee review score & changes](#employee-review-scores-and-changes)
17. [Workforce trends](#workforce-trends)
18. [Salaries](#salaries)
{% endtab %}
{% endtabs %}
{% hint style="info" %}
The data fields in the example snippets have been rearranged for better grouping. To see where a specific data field stands, check the full data sample [here](https://docs.coresignal.com/company-data/multi-source-company-data/sample-multi-source-company-data).
{% endhint %}
{% hint style="info" %}
All personal/company information mentioned within this context is entirely fictional and is solely intended for illustrative purposes.
{% endhint %}
## Metadata
| Data field | Description | Data type |
| ----------------- | --------------------------------------------------------- | --------------- |
| `company_id` | Company record identification key in our database | Integer |
| `source_id` | Identifier assigned by Professional Network | String |
| `expired_domain` | Indicates if the domain is expired | Boolean/integer |
| `unique_domain` | Indicates if the domain is unique | Boolean/integer |
| `unique_website` | Indicates if the website is unique | Boolean/integer |
| `last_updated_at` | Last update date of the record in the `YYYY-MM-DD` format | String (date) |
| `created_at` | Record creation date in the `YYYY-MM-DD` format | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Metadata" %}
```json
"company_id": 8369825,
"source_id": "9082300",
"expired_domain": 0,
"unique_domain": 1,
"unique_website": 1,
"last_updated_at": "2024-04-28"
```
{% endcode %}
## Firmographics
| Data field | Description | Data type |
| -------------------- | ----------------------------------------------------------------------------------------------------------------------------------------- | ------------- |
| `company_name` | Company name | String |
| `company_name_alias` | All name variations associated with the company | String |
| `company_legal_name` | Legal company name | String |
| `company_logo` | Base64-encoded image data of the company's logo | String |
| `company_logo_url` | Logo URL (available from Professional network only) | String |
| `is_b2b` | Indicates if the company operates in a business-to-business model:
1 – b2b company
0 – b2c company
| Integer |
| `industry` | Company's industry | String |
| `type` | Company type | String |
| `founded_year` | Founding year | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Firmographics" %}
```json
"company_name": "Example Company",
"company_legal_name": "Example Company, Inc.",
"company_name_alias": [
"example-company.com",
"Example Company"
"Example Company, Inc. "
]
"company_logo": "/9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAMCAgMCAgMDAwMEAwMEBQgFBQQEBQoHBwYIDAoMDAsK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\\r\\nHHqjQ28Rijjkusl2XBJK9Cea8gooAKKKKACiiigAooooAKKKKACiiigD/9k=",
"company_logo_url": "https://www.professional-network.com/logo-url",
"is_b2b": 1,
"industry": "Software Development",
"founded_year": "2000",
```
{% endcode %}
### SIC and NAICS codes
| Data field | Description | Data type |
| ------------- | --------------------- | ---------------- |
| `sic_codes` | Company's SIC codes | Array of strings |
| `naics_codes` | Company's NAICS codes | Array of strings |
**See a snippet of the dataset for reference:**
{% code title="SIC and NAISC codes" %}
```json
"sic_codes": [
"87",
"874"
],
"naics_codes": [
"32",
"325"
],
```
{% endcode %}
### Descriptions
| Data field | Description | Data type |
| -------------------------- | -------------------------------------------------------------------------------------------------- | --------- |
| `description` | Company description | String |
| `description_enriched` | Company description, enriched with LLM | String |
| `description_metadata_raw` | Company description
(parsed from external sources not included in our firmographic data)
| String |
**See a snippet of the dataset for reference:**
{% code title="Descriptions" %}
```json
"description": "Example Company (Nasdaq: EXMP) is a proven cloud CCaaS platform that helps business leaders redefine customer engagement and transform their contact center’s performance. Decision-makers use Example Company to improve customer experience, boost agent productivity, empower their managers, and enhance their system orchestration capabilities. Everything needed to deliver game-changing results can be seamlessly integrated and configured to maximize your success: Omnichannel Communications, AI, a Contact Center CRM, and Workforce Engagement Management tools. For more than 20 years, clients of all sizes and industries have trusted Example Company’s scalable and reliable cloud platform to power billions of omnichannel interactions every year.",
"description_enriched": "Example Company is a cloud-based call and contact center software provider that offers a range of products and solutions for businesses of all sizes. Their platform includes features such as voice, email, SMS, CRM, and workforce management, and they offer a variety of services to support their clients, including training, implementation, and consulting. ",
"description_metadata_raw": "Example Company CCaaS Ups Your Call / Contact Center Platform with Communication Software So You Can Be A Game-Changer: Voice, Email, SMS, CRM, WFM, for Inbound & Outbound Agents.",
```
{% endcode %}
### Company size
| Data field | Description | Data type |
| ----------------- | ------------------------------------------------------------------------------------------------------- | --------- |
| `size_range` | Company size based on employee count range
(as selected by the company profile administrator)
| String |
| `employees_count` | Number of employees on Professional Network who associated their experience with the company | Integer |
**See a snippet of the dataset for reference:**
{% code title="Company size" %}
```json
"size_range": "501-1000 employees",
"employees_count": 594,
```
{% endcode %}
### Inferred employee counts
| Data field | Description | Data type |
| ----------------------------------- | ---------------------------------------------------------------------------------------------------------- | ---------------- |
| `employees_count_inferred` | Estimated number of employees, calculated based on inferred employee data | Integer |
| `employees_count_inferred_by_month` | Estimated number of employees, calculated based on inferred employee data, for a three-year rolling window | Array of structs |
| `employees_count_inferred` | Estimated number of employees, calculated based on inferred employee data | Integer |
| `date` | Date identifier | String |
**See a snippet of the dataset for reference:**
{% code title="Company size" %}
```json
{
"employees_count_inferred": 20,
"employees_count_inferred_by_month": [
{
"employees_count_inferred": 20,
"date": "202504"
},
{
"employees_count_inferred": 18,
"date": "202503"
}
]
}
```
{% endcode %}
### Employee attrition
| Data field | Description | Data type |
| ------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------- |
| `departures_count` | Count of employees who left the company in the current month | Integer |
| `departures_count_by_month` | Historical monthly departures count with corresponding dates | Array of structs |
| `departures_count_by_month.departures_count` | Number of employee departures | Long |
| `departures_count_by_month.date` | Date for departure count | String |
| `employee_attrition_rate` | Current month attrition rate calculated as (`departures_count` / `employees_count_inferred`) \* 100. Value is `null` when `employees_count_inferred` is `0` or `null` | Double |
| `employee_attrition_rate_by_month` | Historical monthly attrition rates with corresponding dates | Array of structs |
| `employee_attrition_rate_by_month.attrition_rate` | Attrition rate | Double |
| `employee_attrition_rate_by_month.date` | Date for attrition rate | String |
**See a snippet of the dataset for reference:**
{% code title="Employee attrition" %}
```json
{
"departures_count": 20,
"departures_count_by_month": [
{
"departures_count": 20,
"date": "202601"
},
{
"departures_count": 18,
"date": "202602"
}
],
"employee_attrition_rate": 20,
"employee_attrition_rate_by_month": [
{
"attrition_rate": 20,
"date": "202601"
},
{
"attrition_rate": 18,
"date": "202602"
}
]
}
```
{% endcode %}
### Categories & keywords
| Data field | Description | Data type |
| ------------------------- | --------------------------------------------------------------------------------------------- | ---------------- |
| `categories_and_keywords` | Categories and keywords assigned to the company profile and products across various platforms | Array of strings |
**See a snippet of the dataset for reference:**
{% code title="Categories and keywords" %}
```json
"categories_and_keywords": [
"call/contact center software provider",
"call & contact center software",
"contact center software"
],
```
{% endcode %}
### Ownership & status
| Data field | Description | Data type |
| ------------------ | -------------------------------- | ------------------------- |
| `status` | Operational and ownership status | Array of objects (struct) |
| `value` | Current operational status | String |
| `comment` | Current ownership status | String |
| `ownership_status` | Ownership status | String |
**See a snippet of the dataset for reference:**
{% code title="Ownership and status" %}
```json
"status": {
"value": "active",
"comment": "Acquired"
},
"ownership_status": "Public",
```
{% endcode %}
### Parent company
| Data field | Description | Data type |
| ---------------------------- | ---------------------------------------------------- | --------------- |
| `parent_company_information` | Parent company details | Object (struct) |
| `parent_company_id` | Matched parent company ID | String |
| `parent_company_name` | Parent company name | String |
| `parent_company_website` | Parent company website | String |
| `date` | Date of the information provided in `MM/YYYY` format | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Parent company" %}
```json
"parent_company_information": {
"parent_company_id": "1234",
"parent_company_name": "Parent Company",
"parent_company_website": "https://www.parent-company.com/",
"date": "10/2023"
},
```
{% endcode %}
## Company updates
| Data field | Description | Data type |
| ------------------------------- | --------------------------------------------------------------------------------- | ---------------- |
| `company_updates_collection` | Information from posts published by the company | Array of objects |
| `followers` | Profile follower count | Integer |
| `date` | Publish date | String (date) |
| `description` | Published text
Note: may contain control characters
| String |
| `reactions_count` | Number of reactions on the post | Integer |
| `comments_count` | Number of comments on the post | Integer |
| `reshared_post_author` | Reshared post author | String |
| `reshared_post_author_url` | Profile URL of the reshared post author | String |
| `reshared_post_author_headline` | Headline of the reshared post author | String |
| `reshared_post_description` | Reshared post text | String |
| `reshared_post_followers` | The number of followers of the reshared post author | Integer |
| `reshared_post_date` | Date the reshared post was published | String |
**See a snippet of the dataset for reference:**
{% code title="Company updates" %}
```json
"company_updates_collection": [
{
"followers": 1371,
"date": "2025-03-30",
"description": "Example description",
"reactions_count": 22,
"comments_count": 2,
"reshared_post_author": "John Doe",
"reshared_post_author_url": "https://www.professional-network.com/john-doe",
"reshared_post_author_headline": "Co-Founder at Example Company, TEDx & Keynote Speaker",
"reshared_post_description": "Example description",
"reshared_post_followers": 45,
"reshared_post_date": "1mo"
}
]
```
{% endcode %}
## Locations
| Data field | Description | Data type |
| ------------------------ | -------------------------------------------------------- | -------------------------- |
| `hq_region` | Region of the company's HQ location | Array of strings |
| `hq_country` | Country where the company's headquarters is located | String |
| `hq_country_iso2` | ISO 2-letter code of the headquarters country | String |
| `hq_country_iso3` | ISO 3-letter code of the headquarters country | String |
| `hq_location` | Headquarters location | String |
| `hq_full_address` | Full address of the headquarters | String |
| `hq_city` | Headquarters city. Data available only for US companies | String |
| `hq_state` | Headquarters state. Data available only for US companies | String |
| `hq_street` | Headquarters street address | String |
| `hq_zipcode` | Headquarters zip code | String |
| `company_locations_full` | List of company locations. Data includes raw values | Array of objects (structs) |
| `location_address` | Company location address | String |
| `is_primary` | Indicates if this is the primary company location | Boolean |
**See a snippet of the dataset for reference:**
{% code title="Locations" %}
```json
"hq_region": [
"Americas",
"Northern America",
"AMER"
],
"hq_country": "United States",
"hq_country_iso2": "US",
"hq_country_iso3": "USA",
"hq_location": "Austin, TX, United States",
"hq_full_address": "123 Main Street; Suite 500; Austin, TX 78701, US",
"hq_city": "Austin",
"hq_state": "Texas",
"hq_street": "123 Main Street; Suite 500",
"hq_zipcode": "78701",
"company_locations_full": [
{
"location_address": "123 Main Street; Suite 500; Austin, TX 78701, US",
"is_primary": true
}
],
```
{% endcode %}
## Public contact details
| Data field | Description | Data type |
| ----------------------- | ---------------------- | ---------------- |
| `company_phone_numbers` | Public phone numbers | Array of strings |
| `company_emails` | Public email addresses | Array of strings |
**See a snippet of the dataset for reference:**
{% code title="Public contact details" %}
```json
"company_phone_numbers": [
"(555) 123-4567"
],
"company_emails": [
"info@example-company.com"
],
```
{% endcode %}
## Follower counts & changes
### Follower counts
| Data field | Description | Data type |
| -------------------------------------- | ---------------------------------------------- | -------------- |
| `followers_count_professional_network` | Profile follower count on professional network | Integer |
| `followers_count_twitter` | Profile follower count on Twitter | Integer (long) |
| `followers_count_owler` | Profile follower count on Owler | Integer (long) |
**See a snippet of the dataset for reference:**
{% code title="Follower counts" %}
```json
"followers_count_professionnal_network": 12838,
"followers_count_twitter": 705,
"followers_count_owler": 188,
```
{% endcode %}
### Follower count changes
| Data field | Description | Data type |
| --------------------------------------------- | --------------------------------------------------------------------------------- | --------------- |
| `professional_network_followers_count_change` | Changes in the number of followers over different periods on professional network | Object (struct) |
| `current` | Current number of followers on the professional network | Integer (long) |
| `change_monthly` | Monthly change in follower count on the professional network | Integer (long) |
| `change_monthly_percentage` | Monthly percentage change in follower count on the professional network | Float (double) |
| `change_quarterly` | Quarterly change in follower count on the professional network | Integer (long) |
| `change_quarterly_percentage` | Quarterly percentage change in follower count on the professional network | Float (double) |
| `change_yearly` | Yearly change in follower count on the professional network | Integer (long) |
| `change_yearly_percentage` | Yearly percentage change in follower count on the professional network | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Professional network followers" %}
```json
"professional_network_followers_count_change": {
"current": 12779,
"change_monthly": 70,
"change_monthly_percentage": 0.5507907781886852,
"change_quarterly": 891,
"change_quarterly_percentage": 7.494952893674293,
"change_yearly": 1845,
"change_yearly_percentage": 16.873971099323214
},
```
{% endcode %}
| Data field | Description | Data type |
| ----------------------------------------------- | ---------------------------------------------------------------------------------------------------------- | ------------------------- |
| `professional_network_followers_count_by_month` | Professional network follower count changes by month.
Counts available from 2019.01
| Array of objects (struct) |
| `follower_count` | Number of followers | Integer (long) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Professional network followers" %}
```json
"professional_network_followers_count_by_month": [
{
"follower_count": 0,
"date": "2019-11"
},
{
"follower_count": 1,
"date": "2021-01"
}
],
```
{% endcode %}
## Competitors
| Data field | Description | Data type |
| ------------------------------ | ----------------------------------------------------- | ----------------------------------- |
| `competitors` | Competitors and their similarity scores | Array of objects (struct) |
| `company_name` | Competitor's name | String |
| `similarity_score` | Score indicating the similarity to the record company | Integer (long) |
| `competitors_websites` | Details on the competitors' websites | Array of objects
(struct)
|
| `website` | Competitor's website URL | String |
| `total_website_visits_monthly` | Total number of monthly competitor's website visits | Integer (long) |
| `category` | Competitor's website category | String |
| `rank_category` | Competitor's website rank within its category | Integer |
**See a snippet of the dataset for reference:**
{% code title="Competitors" %}
```json
"competitors": [
{
"company_name": "first competitor",
"similarity_score": 5321
},
{
"company_name": "second competitor",
"similarity_score": 5605
}
],
"competitors_websites": [
{
"website": "example-website.com",
"similarity_score": 100,
"total_website_visits_monthly": 91600,
"category": "Law and Government > Government",
"rank_category": 13758
},
{
"website": "example-website2.com",
"similarity_score": 100,
"total_website_visits_monthly": 403700,
"category": "Law and Government > Government",
"rank_category": 3510
}
],
```
{% endcode %}
## Product overview
| Data field | Description | Data type |
| ---------------------- | ---------------------------------------------------------- | --------- |
| `pricing_available` | Marks if service pricing information is available online | Boolean |
| `free_trial_available` | Marks if the company offers a free trial of their services | Boolean |
| `demo_available` | Marks if the company offers a demo | Boolean |
| `is_downloadable` | Marks if the company offers a downloadable file/service | Boolean |
| `mobile_apps_exist` | Marks if the company has mobile apps | Boolean |
| `online_reviews_exist` | Marks if the company has any online reviews | Boolean |
| `api_docs_exist` | Marks if the company has public API docs | Boolean |
**See a snippet of the dataset for reference:**
{% code title="Product and services overview" %}
```json
"pricing_available": false,
"free_trial_available": false,
"demo_available": false,
"is_downloadable": false,
"mobile_apps_exist": false,
"online_reviews_exist": false,
"documentation_exist": false,
```
{% endcode %}
### Product pricing
| Data field | Description | Data type |
| ------------------------- | -------------------------------- | -------------------------- |
| `product_pricing_summary` | Summary of product pricing plans | Array of objects (structs) |
| `type` | Pricing plan type | String |
| `price` | Plan price | String |
| `details` | Pricing plan details | String |
**See a snippet of the dataset for reference:**
{% code title="Product pricing" %}
```json
"product_pricing_summary": [
{
"type": "First plan",
"price": "38.00",
"details": "Per Month"
},
{
"type": "Second plan",
"price": "85",
"details": "per month (Annual Plan)"
}
],
```
{% endcode %}
### Product review scores
| Data field | Description | Data Type |
| --------------------------------- | -------------------------------- | -------------- |
| `product_reviews_count` | Total number of product reviews | Integer (long) |
| `product_reviews_aggregate_score` | Average score of product reviews | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Product review fluctuations" %}
```json
"product_reviews_count": 74,
"product_reviews_aggregate_score": 4.513513513513513,
```
{% endcode %}
| Data field | Description | Data type |
| -------------------------------- | ------------------------------------------------------------------------------------ | -------------------------- |
| `product_reviews_score_by_month` | Product review scores by month.
Counts available from 2021.04
| Array of objects (structs) |
| `product_reviews_score` | Product review score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Review score" %}
```json
"product_reviews_score_by_month": [
{
"product_reviews_score": 4.4,
"date": "2019-11"
},
{
"product_reviews_score": 4.6,
"date": "2021-01"
}
],
```
{% endcode %}
### Product review score distribution
| Data field | Description | Data Type |
| ------------------------------------ | ------------------------------------- | --------------- |
| `product_reviews_score_distribution` | Distribution of product review scores | Object (struct) |
| `score_1` | Number of 1-star reviews | Integer (long) |
| `score_2` | Number of 2-star reviews | Integer (long) |
| `score_3` | Number of 3-star reviews | Integer (long) |
| `score_4` | Number of 4-star reviews | Integer (long) |
| `score_5` | Number of 5-star reviews | Integer (long) |
**See a snippet of the dataset for reference:**
{% code title="Product review score distribution" %}
```json
"product_reviews_score_distribution": {
"score_1": 0,
"score_2": 0,
"score_3": 4,
"score_4": 28,
"score_5": 42
},
```
{% endcode %}
### Product review score changes
| Data field | Description | Data type |
| ------------------------------ | ---------------------------------------------------------- | --------------- |
| `product_reviews_score_change` | Changes in the product review score over different periods | Object (struct) |
| `current` | Current product review score | Float (double) |
| `change_monthly` | Monthly change in product review score | Float (double) |
| `change_quarterly` | Quarterly change in product review score | Float (double) |
| `change_yearly` | Yearly change in product review score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Product review fluctuations" %}
```json
"product_reviews_score_change": {
"current": 4.3,
"change_monthly": 0.0,
"change_quarterly": 0.0,
"change_yearly": 0.0
},
```
{% endcode %}
## Financials
### Annual revenue range
| Data field | Description | Data type |
| ------------------------------------------------------------------------------------------------------- | ----------------------------------------------------- | --------------- |
| `revenue_annual_range` | Annual revenue range information from various sources | Object (struct) |
| source\_4\_annual\_revenue\_range
source\_6\_annual\_revenue\_range
| Revenue information from a specific source | Object (struct) |
| `annual_revenue_range_from` | Minimum annual revenue range | Float (double) |
| `annual_revenue_range_to` | Maximum annual revenue range | Float (double) |
| `annual_revenue_range_currency` | Revenue currency | String |
**See a snippet of the dataset for reference:**
{% code title="Annual revenue" %}
```json
"revenue_annual_range": {
"source_4_annual_revenue_range": {
"annual_revenue_range_from": 1.0E8,
"annual_revenue_range_to": 5.0E8,
"annual_revenue_range_currency": "USD"
},
"source_6_annual_revenue_range": {
"annual_revenue_range_from": 1.0E8,
"annual_revenue_range_to": 2.0E8,
"annual_revenue_range_currency": "USD"
}
},
```
{% endcode %}
### Annual revenue
| Data field | Description | Data type |
| ----------------------------------------------------------------------------------------- | ----------------------------------------------- | --------------- |
| `revenue_annual` | Annual revenue information from various sources | Object (struct) |
| source\_5\_annual\_revenue
source\_1\_annual\_revenue
| Revenue information from a specific source | Object (struct) |
| `annual_revenue` | Annual revenue amount | Integer (long) |
| `annual_revenue_currency` | Revenue currency | String |
**See a snippet of the dataset for reference:**
{% code title="Annual revenue" %}
```json
"revenue_annual": {
"source_5_annual_revenue": {
"annual_revenue": 143285000,
"annual_revenue_currency": "USD"
},
"source_1_annual_revenue": {
"annual_revenue": 1.36025E8,
"annual_revenue_currency": "USD"
}
},
```
{% endcode %}
### Quarterly revenue
| Data field | Description | Data type |
| ------------------- | ----------------------------- | --------------- |
| `revenue_quarterly` | Quarterly revenue information | Object (struct) |
| `value` | Quarterly revenue amount | Float (double) |
| `currency` | Revenue currency | String |
**See a snippet of the dataset for reference:**
{% code title="Quarterly revenue" %}
```json
"revenue_quarterly": {
"value": 3.5352E7,
"currency": "USD"
},
```
{% endcode %}
### IPO
| Data field | Description | Data type |
| -------------------------- | -------------------------------------------------------------------- | -------------- |
| `is_public` | Indicates if the company is publicly traded | Boolean |
| `ipo_date` | IPO date | String |
| `ipo_share_price` | Initial share price at the time of IPO. Value is present in USD only | Integer (long) |
| `ipo_share_price_currency` | Initial share price currency | String |
**See a snippet of the dataset for reference:**
{% code title="IPO" %}
```json
"is_public": 1,
"ipo_date": "2021-01-14",
"ipo_share_price": 10,
"ipo_share_price_currency": "USD",
```
{% endcode %}
### Stock information
| Data field | Description | Data type |
| ------------------- | ---------------------------------------------------- | -------------------------- |
| `stock_ticker` | Company's stock ticker information | Array of objects (structs) |
| `exchange` | Stock exchange | String |
| `ticker` | Stock ticker | String |
| `stock_information` | Financial details of the company's stock | Array of objects (structs) |
| `closing_price` | Stock's closing price | Float (double) |
| `currency` | Stock currency | String |
| `date` | Date of the stock information in `YYYY-MM-DD` format | String (date) |
| `marketcap` | Market capitalization value | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Stocks" %}
```json
"stock_ticker": [
{
"exchange": "NASDAQ",
"ticker": "AAPL"
}
]
"stock_information": [
{
"closing_price": 3.7300000190734863,
"currency": "USD",
"date": "2023-12-29",
"marketcap": 3.52990784E8
},
{
"closing_price": 3.680000066757202,
"currency": "USD",
"date": "2023-11-30",
"marketcap": 3.48259008E8
}
],
```
{% endcode %}
### Income statements
| Data field | Description | Data type |
| ----------------------------- | ------------------------------------------------------------------------------------------------ | ---------------- |
| `income_statements` | Company's income statement details | Array of objects |
| `cost_of_goods_sold` | Total cost of goods sold by the company | Float (double) |
| `cost_of_goods_sold_currency` | Report currency | String |
| `ebit` | Earnings before interest and taxes | Float (double) |
| `ebitda` | Earnings before interest, taxes, depreciation, and amortization | Float (double) |
| `ebitda_margin` | EBITDA divided by total revenue | Float (double) |
| `ebit_margin` | EBIT divided by total revenue | Float (double) |
| `earnings_per_share` | Earnings per share | Float (double) |
| `gross_profit` | Profit after expenses related to manufacturing and selling its products or services | Float (double) |
| `gross_profit_margin` | Gross profit divided by revenue | Float (double) |
| `income_tax_expense` | Income tax expense | Float (double) |
| `interest_expense` | Total interest expense | Float (double) |
| `interest_income` | Interest income | Float (double) |
| `net_income` | Net income | Float (double) |
| `period_display_end_date` | Period end display date (e.g., fiscal year or quarter) based on how it's displayed in the source | String |
| `period_end_date` | Period end date in `YYYY-MM-DD` format | String (date) |
| `period_type` | Period type | String |
| `pre_tax_profit` | Profit before tax | Float (double) |
| `revenue` | Total revenue earned by the company | Float (double) |
| `total_operating_expense` | Total expenses related to operations | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Income statements" %}
```json
"income_statements": [
{
"cost_of_goods_sold": 187884,
"cost_of_goods_sold_currency": "USD",
"ebit": 673028000,
"ebitda": 785395000,
"ebitda_margin": 0.23780319797984079,
"ebit_margin": 0.20378053174514263,
"earnings_per_share": -0.12,
"gross_profit": 145952,
"gross_profit_margin": 0.43719670736529315,
"income_tax_expense": 15625,
"interest_expense": 76,
"interest_income": 15920,
"net_income": 55891,
"period_display_end_date": "Q3, 2023",
"period_end_date": "2023-09-30",
"period_type": "q3",
"pre_tax_profit": 71516,
"revenue": 333836,
"total_operating_expense": 2.7999E7
}
],
```
{% endcode %}
## Funding
### Last funding round
| Data field | Description | Data type |
| --------------------------------- | --------------------------------------------------------------------- | ---------------- |
| `last_funding_round` | Last funding round information | Array of structs |
| `type` | Last funding round type (e.g. `Series A`) | String |
| `announced_date` | Date when the last funding round was announced in `YYYY-MM-DD` format | String (date) |
| `investors` | Investors in the last funding round | Array of structs |
| `investors[].name` | Investor name | String |
| `investors[].entity_id` | Internal entity identifier | Long |
| `investors[].entity` | Entity type (e.g. person, organization) | String |
| `investors[].is_lead` | Indicates whether this investor led the round | Boolean |
| `investors[].partner_identifiers` | Partner-level identifiers within the investor | Array of structs |
| `partner_identifiers[].name` | Partner name | String |
| `partner_identifiers[].entity_id` | Partner entity identifier | Long |
| `partner_identifiers[].entity` | Partner entity type | String |
| `amount_raised` | Amount raised in the last funding round | Integer (long) |
| `amount_raised_currency` | Funding round currency | String |
| `num_investors` | Number of investors in the last funding round | Integer (long) |
| `num_partners` | Number of partner investors in the last funding round | Integer (long) |
**See a snippet of the dataset for reference:**
{% code title="Last funding round" expandable="true" %}
```json
{
"last_funding_round": {
"type": "Series A",
"announced_date": "2025-09-10",
"investors": [
{
"name": "Example Ventures",
"entity_id": 1010101010,
"entity": "organization",
"is_lead": true,
"partner_identifiers": [
{
"name": "Jane Doe",
"entity_id": 123123123,
"entity": "person"
}
]
}
],
"amount_raised": 1000000,
"amount_raised_currency": "USD",
"num_investors": 1,
"num_partners": 1
}
```
{% endcode %}
### Funding rounds
| Data field | Description | Data type |
| --------------------------------- | ---------------------------------------------------------------- | ---------------- |
| `funding_rounds` | List of completed funding rounds | Array of structs |
| `type` | Funding round type (e.g. `Series A`) | String |
| `announced_date` | Date when the funding round was announced in `YYYY-MM-DD` format | String (date) |
| `investors` | Investors in the funding round | Array of structs |
| `investors[].name` | Investor name | String |
| `investors[].entity_id` | Internal entity identifier | Long |
| `investors[].entity` | Entity type (e.g. person, organization) | String |
| `investors[].is_lead` | Indicates whether this investor led the round | Boolean |
| `investors[].partner_identifiers` | Partner-level identifiers within the investor | Array of structs |
| `partner_identifiers[].name` | Partner name | String |
| `partner_identifiers[].entity_id` | Partner entity identifier | Long |
| `partner_identifiers[].entity` | Partner entity type | String |
| `amount_raised` | Amount raised in the funding round | Integer (long) |
| `amount_raised_currency` | Funding round currency | String |
| `num_investors` | Number of investors in the funding round | Integer (long) |
| `num_partners` | Number of partner investors in the round | Integer (long) |
**See a snippet of the dataset for reference:**
{% code title="Funding rounds" expandable="true" %}
```json
"funding_rounds": [
{
"type": "Series A",
"announced_date": "2025-11-28",
"investors": [
{
"name": "Example Managers",
"entity_id": 111222333,
"entity": "organization",
"is_lead": true,
"partner_identifiers": [
{
"name": "Jane Doe",
"entity_id": 123123123,
"entity": "person"
}
}
],
"amount_raised": 200000,
"amount_raised_currency": "USD",
"num_investors": 1,
"num_partners": 1
},
],
```
{% endcode %}
## Acquisitions
### Acquired by
| Data field | Description | Data type |
| --------------------- | ------------------------- | --------------- |
| `acquired_by_summary` | Acquiring company details | Object (struct) |
| `acquirer_name` | Acquiring company name | String |
| `announced_date` | Acquisition date | String |
| `price` | Acquisition price | Integer (long) |
| `currency` | Acquisition currency | String |
**See a snippet of the dataset for reference:**
{% code title="Acquirer" %}
```json
"acquired_by_summary": {
"acquirer_name": "Parent Company",
"announced_date": "2023-10-04",
"price": 350000000,
"currency": "USD"
},
```
{% endcode %}
### Acquisitions
| Data field | Description | Data type |
| ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------- | ------------------------- |
| num\_acquisitions\_source\_1
num\_acquisitions\_source\_2
num\_acquisitions\_source\_5
| Number of completed company acquisitions based on information from various sources | Integer |
| acquisition\_list\_source\_1
acquisition\_list\_source\_2
acquisition\_list\_source\_5
| Company's acquisition information from various sources | Array of objects (struct) |
| `acquiree_name` | Acquired company name | String |
| `announced_date` | Date when the acquisition was announced in `YYYY-MM-DD` format | String (date) |
| `price` | Acquisition price | Integer |
| `currency` | Acquisition price currency | String |
**See a snippet of the dataset for reference:**
{% code title="Acquisitions" %}
```json
"num_acquisitions_source_1": 2,
"acquisition_list_source_1": [
{
"acquiree_name": "First Acquiree",
"announced_date": "2019-12-10",
"price": 350000000,
"currency": "USD"
},
{
"acquiree_name": "Second Acquiree",
"announced_date": "2020-01-27",
"price": 350000000,
"currency": "USD"
}
],
"num_acquisitions_source_2": 2,
"acquisition_list_source_2": [
{
"acquiree_name": "First Acquiree",
"announced_date": "2020-01-27",
"price": 350000000,
"currency": "USD"
},
{
"acquiree_name": "Second Acquiree",
"announced_date": "2019-12-10",
"price": 350000000,
"currency": "USD"
}
],
```
{% endcode %}
## News features
| Data field | Description | Data type |
| ------------------- | --------------------------------------------------------- | -------------------------- |
| `num_news_articles` | Number of news articles that mention the record company | Integer |
| `news_articles` | Details about the news articles featuring company updates | Array of objects (structs) |
| `headline` | News article headline | String |
| `published_date` | Date the article was published in `YYYY-MM-DD` format | String (date) |
| `summary` | News article summary | String |
| `article_url` | Full news article URL | String |
| `source` | Source of the news | String |
**See a snippet of the dataset for reference:**
{% code title="Media mentions" %}
```json
"num_news_articles": 1,
"news_articles": [
{
"headline": "Example Company Layoffs Hit Channel and Sales Team",
"published_date": "2024-01-08",
"summary": "Professional networking sites such as have seen the influx of Example Company employees posting about getting layoff notices in the past week. The cuts have come following the acquisition by contact-center-as-a-service (CCaaS) giant NICE.",
"article_url": "https://www.channelfutures.com/unified-communications/voicestream-technologies-inc-layoffs-hit-channel-and-sales-team",
"source": "News source example"
}
],
```
{% endcode %}
## Technographics
| Data field | Description | Data type |
| ----------------------- | ------------------------------------------------------ | ---------------- |
| `num_technologies_used` | Number of technologies used by the company | Integer |
| `technologies_used` | List of technologies used by the company | Array of strings |
| `technology` | Technology name | String |
| `first_verified_at` | Date this technology was first assigned to the company | String (date) |
| `last_verified_at` | Date this technology was last assigned to the company | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Technographics" %}
```json
"num_technologies_used": 40,
"technologies_used": [
{
"technology": "React",
"first_verified_at": "2022-03-15",
"last_verified_at": "2024-10-15"
}
]
```
{% endcode %}
## Company websites and social media
| Data field | Description | Data type |
| ----------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------- | ---------------- |
| `website` | Website URL | String |
| `website_domain` | Normalized domain output (e.g., `example-company.com`) | String |
| `website_alias` | All possible company website variations
(collected from our firmographic sources)
| String |
| `professional_network_url` | Professional network URL where the company was first discovered. It can be outdated if the company has changed its profile | String |
| `professional_network_shorthand_name` | Shorthand name of the company's Professional network URL | String |
| `canonical_professional_network_url` | The current official Professional network URL for the company, reflecting the most recent updates | String |
| `canonical_professional_network_shorthand_name` | The current shorthand name of the company's Professional network URL | String |
| `twitter_url` | Twitter profile URL | Array of strings |
| `discord_url` | Discord server URL | Array of strings |
| `facebook_url` | Facebook page URL | Array of strings |
| `instagram_url` | Instagram profile URL | Array of strings |
| `pinterest_url` | Pinterest profile URL | Array of strings |
| `tiktok_url` | TikTok profile URL | Array of strings |
| `youtube_url` | YouTube channel URL | Array of strings |
| `github_url` | GitHub profile URL | Array of strings |
| `reddit_url` | Reddit profile URL | Array of strings |
| `financial_website_url` | Financial network profile URL | String |
**See a snippet of the dataset for reference:**
"website": "http://www.primarywebsite.com",
"website_domain": "primarywebsite.com",
"website_alias": [
"http://www.primarywebsite.org",
"http://www.primarywebsite.net",
"http://www.primary-site.com"
],
"professional_network_url": "https://www.professional-network.com/company/example-company",
"professional_network_shorthand_name": "example-company",
"canonical_professional_network_url": "https://www.professional-network.com/company/example-company",
"canonical_professional_network_shorthand_name": "example-company",
"twitter_url": [
"https://twitter.com/example-company"
],
"discord_url": [
"https://discord.gg/example-company"
],
"facebook_url": [
"https://www.facebook.com/example-company"
],
"instagram_url": [
"https://www.instagram.com/example-company"
],
"pinterest_url": [
"https://www.pinterest.com/example-company"
],
"tiktok_url": [
"https://www.tiktok.com/@example-company"
],
"youtube_url": [
"https://www.youtube.com/c/example-company"
],
"github_url": [
"https://github.com/example-company"
],
"reddit_url": [
"https://www.reddit.com/user/example-company"
],
"financial_website_url": "https://www.financial-website.com/organization/example-company",
## Website traffic
### Web traffic and topics
| Data field | Description | Data type |
| -------------------------------- | ----------------------------------------------------------------- | ---------------- |
| `total_website_visits_monthly` | Monthly website visits | Integer (long) |
| `visits_change_monthly` | Monthly change in website visits, shown in percentage | Float (double) |
| `rank_global` | Global rank of the website | Integer |
| `rank_country` | Country-specific rank of the website | Integer |
| `rank_category` | Category-specific rank of the website | Integer |
| `bounce_rate` | Percentage of visitors who leave the site after visiting one page | Float (double) |
| `pages_per_visit` | Average number of pages viewed per visit | Float (double) |
| `average_visit_duration_seconds` | Average duration of a visit in seconds | Float (double) |
| `similarly_ranked_websites` | List of websites with similar rankings | Array of strings |
| `top_topics` | List of top topics associated with the website | Array of strings |
**See a snippet of the dataset for reference:**
{% code title="Web traffic and topics" %}
```json
"total_website_visits_monthly": 72600,
"visits_change_monthly": 14.12,
"rank_global": 573826,
"rank_country": 119057,
"rank_category": 2160,
"bounce_rate": 41.26,
"pages_per_visit": 5.5,
"average_visit_duration_seconds": 287.0,
"similarly_ranked_websites": [
"example-website.com",
"examplary-website.com"
],
"top_topics": [
"google",
"social network",
"social",
"social media",
"google apps"
],
```
{% endcode %}
| Data field | Description | Data type |
| ----------------------------- | -------------------------------------------------------------------- | --------------- |
| `total_website_visits_change` | Changes in the total number of website visits over different periods | Object (struct) |
| `current` | Current number of total website visits | Integer (long) |
| `change_monthly` | Monthly change in total website visits | Integer (long) |
| `change_monthly_percentage` | Monthly percentage change in total website visits | Float (double) |
| `change_quarterly` | Quarterly change in total website visits | Integer (long) |
| `change_quarterly_percentage` | Quarterly percentage change in total website visits | Float (double) |
| `change_yearly` | Yearly change in total website visits | Integer (long) |
| `change_yearly_percentage` | Yearly percentage change in total website visits | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Web traffic and topics" %}
```json
"total_website_visits_change": {
"current": 15432,
"change_monthly": 89,
"change_monthly_percentage": 0.576321854392679,
"change_quarterly": 1043,
"change_quarterly_percentage": 6.781293846102947,
"change_yearly": 1983,
"change_yearly_percentage": 13.425986213489573
}
```
{% endcode %}
| Data field | Description | Data type |
| ------------------------------- | ---------------------------------------------------------------------------- | -------------------------- |
| `total_website_visits_by_month` | Website visits by month.
Counts available from 202404
| Array of objects (structs) |
| `total_website_visits` | Website visits | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Website visits" %}
```json
"total_website_visits_by_month": [
{
"total_website_visits": 60,
"date": "2019-11"
},
{
"total_website_visits": 75,
"date": "2021-01"
}
],
```
{% endcode %}
### Visits by country
| Data field | Description | Data type |
| ----------------------------- | ------------------------------------------------------- | -------------------------- |
| `visits_breakdown_by_country` | Breakdown of website visits by country | Array of objects (structs) |
| `country` | Visitor's country | String |
| `percentage` | Percentage of visits from one country | Float (double) |
| `percentage_monthly_change` | Monthly change in percentage of visits from one country | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Visits by country" %}
```json
"visits_breakdown_by_country": [
{
"country": "United States",
"percentage": 74.9,
"percentage_monthly_change": 31.74
}
],
```
{% endcode %}
### Visits by gender
| Data field | Description | Data type |
| ---------------------------- | ------------------------------------- | --------------- |
| `visits_breakdown_by_gender` | Breakdown of website visits by gender | Object (struct) |
| `male_percentage` | Percentage of visits by males | Float (double) |
| `female_percentage` | Percentage of visits by females | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Visits by gender" %}
```json
"visits_breakdown_by_gender": {
"male_percentage": 64.04,
"female_percentage": 35.96
},
```
{% endcode %}
### Visits by age
| Data field | Description | Data type |
| ------------------------- | ----------------------------------------------- | --------------- |
| `visits_breakdown_by_age` | Breakdown of website visits by age group | Object (struct) |
| `age_18_24_percentage` | Percentage of visits by users aged 18-24 | Float |
| `age_25_34_percentage` | Percentage of visits by users aged 25-34 | Float |
| `age_35_44_percentage` | Percentage of visits by users aged 35-44 | Float |
| `age_45_54_percentage` | Percentage of visits by users aged 45-54 | Float |
| `age_55_64_percentage` | Percentage of visits by users aged 55-64 | Float |
| `age_65_plus_percentage` | Percentage of visits by users aged 65 and above | Float |
**See a snippet of the dataset for reference:**
{% code title="Visits by age" %}
```json
"visits_breakdown_by_age": {
"age_18_24_percentage": 22.92,
"age_25_34_percentage": 32.22,
"age_35_44_percentage": 15.47,
"age_45_54_percentage": 13.31,
"age_55_64_percentage": 10.3,
"age_65_plus_percentage": 5.78
},
```
{% endcode %}
## Employee review scores & changes
### Review count
| Data field | Description | Data type |
| ------------------------------------------ | --------------------------------- | -------------- |
| `company_employee_reviews_count` | Total number of employee reviews | Integer (long) |
| `company_employee_reviews_aggregate_score` | Average score of employee reviews | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Review count" %}
```json
"company_employee_reviews_count": 145,
"company_employee_reviews_aggregate_score": 4.1,
```
{% endcode %}
### Review score breakdown
| Data field | Description | Data type |
| ---------------------------------- | ------------------------------------------------ | --------------- |
| `employee_reviews_score_breakdown` | Breakdown of employee review ratings by category | Object (struct) |
| `business_outlook` | Business outlook rating | Float (double) |
| `career_opportunities` | Career opportunities rating | Float (double) |
| `ceo_approval` | CEO approval rating | Float (double) |
| `compensation_benefits` | Compensation and benefits rating | Float (double) |
| `culture_values` | Culture and values rating | Float (double) |
| `diversity_inclusion` | Diversity and inclusion rating | Float (double) |
| `recommend` | Recommendation rating | Float (double) |
| `senior_management` | Senior management rating | Float (double) |
| `work_life_balance` | Work-life balance rating | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Review score breakdown" %}
```json
"employee_reviews_score_breakdown": {
"business_outlook": 0.55,
"career_opportunities": 3.6,
"ceo_approval": 0.57,
"compensation_benefits": 4.2,
"culture_values": 4.1,
"diversity_inclusion": 3.7,
"recommend": 0.76,
"senior_management": 3.4,
"work_life_balance": 4.2
},
```
{% endcode %}
### Review score distribution
| Data field | Description | Data type |
| ------------------------------------- | ------------------------------------------- | --------------- |
| `employee_reviews_score_distribution` | Distribution of star ratings in the reviews | Object (struct) |
| `score_1` | Number of 1-star reviews | Integer (long) |
| `score_2` | Number of 2-star reviews | Integer (long) |
| `score_3` | Number of 3-star reviews | Integer (long) |
| `score_4` | Number of 4-star reviews | Integer (long) |
| `score_5` | Number of 5-star reviews | Integer (long) |
**See a snippet of the dataset for reference:**
{% code title="Review rating distribution" %}
```json
"employee_reviews_score_distribution": {
"score_1": 2,
"score_2": 7,
"score_3": 9,
"score_4": 14,
"score_5": 28
},
```
{% endcode %}
### Total rating change
| Data field | Description | Data type |
| ------------------------------------------ | --------------------------------------------------------------------------------- | --------------- |
| `employee_reviews_score_aggregated_change` | Changes in the aggregated rating score of employee reviews over different periods | Object (struct) |
| `current` | Current aggregated score of employee reviews | Float (double) |
| `change_monthly` | Monthly change in the aggregated score | Float (double) |
| `change_quarterly` | Quarterly change in the aggregated score | Float (double) |
| `change_yearly` | Yearly change in the aggregated score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Total rating change" %}
```json
"employee_reviews_score_aggregated_change": {
"current": 4.3,
"change_monthly": 0.05,
"change_quarterly": 0.1,
"change_yearly": -0.2
}
```
{% endcode %}
| Data field | Description | Data type |
| -------------------------------------------- | ------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_aggregated_by_month` | Aggregated review score by month
Counts available from 2022.06
| Array of objects (structs) |
| `aggregated_score` | Aggregated score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Aggregated reviews by month" %}
```json
"employee_reviews_score_aggregated_by_month": [
{
"aggregated_score": 3.4,
"date": "2023-03"
},
{
"aggregated_score": 3.7,
"date": "2024-07"
}
],
```
{% endcode %}
### Rating change in the business outlook category
| Data field | Description | Data type |
| ------------------------------------------------ | ---------------------------------------------- | --------------- |
| `employee_reviews_score_business_outlook_change` | Changes in the business outlook rating score | Object (struct) |
| `current` | Current business outlook score | Float (double) |
| `change_monthly` | Monthly change in the business outlook score | Float (double) |
| `change_quarterly` | Quarterly change in the business outlook score | Float (double) |
| `change_yearly` | Yearly change in the business outlook score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the business outlook category" %}
```json
"employee_reviews_score_business_outlook_change": {
"current": 0.45,
"change_monthly": 0.02,
"change_quarterly": -0.05,
"change_yearly": 0.3
}
```
{% endcode %}
| Data field | Description | Data type |
| -------------------------------------------------- | ------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_business_outlook_by_month` | Business outlook score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `business_outlook_score` | Business outlook score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Business outlook score by month" %}
```json
"employee_reviews_score_business_outlook_by_month": [
{
"business_outlook_score": 49.0,
"date": "2025-01"
},
{
"business_outlook_score": 49.0,
"date": "2024-09"
}
],
```
{% endcode %}
### Rating change in the career opportunities category
| Data field | Description | Data type |
| ---------------------------------------------------- | ---------------------------------------------------------------------- | --------------- |
| `employee_reviews_score_career_opportunities_change` | Changes in the career opportunities rating score from employee reviews | Object (struct) |
| `current` | Current career opportunities score | Float (double) |
| `change_monthly` | Monthly change in the career opportunities score | Float (double) |
| `change_quarterly` | Quarterly change in the career opportunities score | Float (double) |
| `change_yearly` | Yearly change in the career opportunities score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the career opportunities category" %}
```json
"employee_reviews_score_career_opportunities_change": {
"current": 3.8,
"change_monthly": -0.1,
"change_quarterly": -0.15,
"change_yearly": -0.3
}
```
{% endcode %}
| Data field | Description | Data type |
| ------------------------------------------------------ | ----------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_career_opportunities_by_month` | Career opportunities score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `career_opportunities_score` | Business outlook score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Career opportunities score by month" %}
```json
"employee_reviews_score_career_opportunities_by_month": [
{
"career_opportunities_score": 3.6,
"date": "2024-10"
},
{
"career_opportunities_score": 3.6,
"date": "2023-06"
}
],
```
{% endcode %}
### Rating change in the CEO approval category
| Data field | Description | Data type |
| -------------------------------------------- | -------------------------------------------------------------- | --------------- |
| `employee_reviews_score_ceo_approval_change` | Changes in the CEO approval rating score from employee reviews | Object (struct) |
| `current` | Current approval score of the CEO | Float (double) |
| `change_monthly` | Monthly change in the CEO approval score | Float (double) |
| `change_quarterly` | Quarterly change in the CEO approval score | Float (double) |
| `change_yearly` | Yearly change in the CEO approval score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the CEO approval category" %}
```json
"employee_reviews_score_ceo_approval_change": {
"current": 0.58,
"change_monthly": -0.03,
"change_quarterly": -0.05,
"change_yearly": -45.12
}
```
{% endcode %}
| Data field | Description | Data type |
| ---------------------------------------------- | --------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_ceo_approval_by_month` | CEO approval score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `ceo_approval_score` | CEO approval score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="CEO approval score by month" %}
```json
"employee_reviews_score_ceo_approval_by_month": [
{
"ceo_approval_score": 4.0,
"date": "2023-03"
},
{
"ceo_approval_score": 3.0,
"date": "2022-08"
}
],
```
{% endcode %}
### Rating change in the compensation and benefits category
| Data field | Description | Data type |
| ----------------------------------------------------- | --------------------------------------------------------------------------- | --------------- |
| `employee_reviews_score_compensation_benefits_change` | Changes in the compensation and benefits rating score from employee reviews | Object (struct) |
| `current` | Current compensation and benefits score | Float (double) |
| `change_monthly` | Monthly change in the compensation and benefits score | Float (double) |
| `change_quarterly` | Quarterly change in the compensation and benefits score | Float (double) |
| `change_yearly` | Yearly change in the compensation and benefits score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the compensation and benefits category" %}
```json
"employee_reviews_score_compensation_benefits_change": {
"current": 4.3,
"change_monthly": 0.05,
"change_quarterly": 0.07,
"change_yearly": -0.08
}
```
{% endcode %}
| Data field | Description | Data type |
| ------------------------------------------------------- | ---------------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_compensation_benefits_by_month` | Compensation and benefits score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `compensation_benefits_score` | Compensation and benefits score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Comensation benefits by month" %}
```json
"employee_reviews_score_compensation_benefits_by_month": [
{
"compensation_benefits_score": 3.6,
"date": "2025-02"
},
{
"compensation_benefits_score": 3.6,
"date": "2024-12"
}
],
```
{% endcode %}
### Rating change in the culture and values category
| Data field | Description | Data type |
| ------------------------------------------------ | --------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_culture_values_by_month` | Culture and values score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `culture_values_score` | Culture and values score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Culture and values score by month" %}
```json
"employee_reviews_score_culture_values_by_month": [
{
"culture_values_score": 3.9,
"date": "2025-03"
},
{
"culture_values_score": 3.9,
"date": "2024-11"
}
],
```
{% endcode %}
| Data field | Description | Data type |
| ---------------------------------------------- | -------------------------------------------------------------------- | --------------- |
| `employee_reviews_score_culture_values_change` | Changes in the culture and values rating score from employee reviews | Object (struct) |
| `current` | Current culture and values score | Float (double) |
| `change_monthly` | Monthly change in the culture and values score | Float (double) |
| `change_quarterly` | Quarterly change in the culture and values score | Float (double) |
| `change_yearly` | Yearly change in the culture and values score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the culture and values category" %}
```json
"employee_reviews_score_culture_values_change": {
"current": 4.1,
"change_monthly": 0.1,
"change_quarterly": 0.2,
"change_yearly": -0.3
}
```
{% endcode %}
### Rating change in the diversity and inclusion category
| Data field | Description | Data type |
| --------------------------------------------------- | ------------------------------------------------------------------------- | --------------- |
| `employee_reviews_score_diversity_inclusion_change` | Changes in the diversity and inclusion rating score from employee reviews | Object (struct) |
| `current` | Current diversity and inclusion score | Float (double) |
| `change_monthly` | Monthly change in the diversity and inclusion score | Float (double) |
| `change_quarterly` | Quarterly change in the diversity and inclusion score | Float (double) |
| `change_yearly` | Yearly change in the diversity and inclusion score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the diversity and inclusion category" %}
```json
"employee_reviews_score_diversity_inclusion_change": {
"current": 3.7,
"change_monthly": -0.1,
"change_quarterly": -0.2,
"change_yearly": -0.3
}
```
{% endcode %}
| Data field | Description | Data type |
| ----------------------------------------------------- | -------------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_diversity_inclusion_by_month` | Diversity and inclusion score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `diversity_inclusion_score` | Diversity and inclusion score | Float (double) |
| `date` | Record date | String (date) |
{% code title="Diversity and inclusion score by month" %}
```json
"employee_reviews_score_diversity_inclusion_by_month": [
{
"diversity_inclusion_score": 4.5,
"date": "2025-03"
},
{
"diversity_inclusion_score": 4.5,
"date": "2024-11"
}
],
```
{% endcode %}
### Rating change in the recommendations category
| Data field | Description | Data type |
| ----------------------------------------- | ---------------------------------------------------------------- | --------------- |
| `employee_reviews_score_recommend_change` | Changes in the recommendation rating score from employee reviews | Object (struct) |
| `current` | Current recommendation score | Float (double) |
| `change_monthly` | Monthly change in the recommendation score | Float (double) |
| `change_quarterly` | Quarterly change in the recommendation score | Float (double) |
| `change_yearly` | Yearly change in the recommendation score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the recommendations category" %}
```json
"employee_reviews_score_recommend_change": {
"current": 0.76,
"change_monthly": -0.12,
"change_quarterly": -0.12,
"change_yearly": -0.24
}
```
{% endcode %}
| Data field | Description | Data type |
| ------------------------------------------- | -------------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_recommend_by_month` | Likelihood to recommend score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `recommend_score` | Likelihood to recommend score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Recommendation score by month" %}
```json
"employee_reviews_score_recommend_by_month": [
{
"recommend_score": 0.54,
"date": "2024-07"
},
{
"recommend_score": 0.54,
"date": "2024-06"
}
],
```
{% endcode %}
### Rating change in the senior management category
| Data field | Description | Data type |
| ------------------------------------------------- | ------------------------------------------------------------------- | --------------- |
| `employee_reviews_score_senior_management_change` | Changes in the senior management rating score from employee reviews | Object (struct) |
| `current` | Current senior management score | Float (double) |
| `change_monthly` | Monthly change in the senior management score | Float (double) |
| `change_quarterly` | Quarterly change in the senior management score | Float (double) |
| `change_yearly` | Yearly change in the senior management score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the senior management category" %}
```json
"employee_reviews_score_senior_management_change": {
"current": 3.4,
"change_monthly": -0.1,
"change_quarterly": -0.1,
"change_yearly": -0.3
}
```
{% endcode %}
| Data field | Description | Data type |
| --------------------------------------------------- | -------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_senior_management_by_month` | Senior management score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `senior_management_score` | Senior management score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Senior management score by month" %}
```json
"employee_reviews_score_senior_management_by_month": [
{
"senior_management_score": 3.9,
"date": "2025-03"
},
{
"senior_management_score": 3.9,
"date": "2024-11"
}
],
```
{% endcode %}
### Rating change in the work and life balance category
| Data field | Description | Data type |
| ------------------------------------------------- | ------------------------------------------------------------------- | --------------- |
| `employee_reviews_score_work_life_balance_change` | Changes in the work-life balance rating score from employee reviews | Object (struct) |
| `current` | Current work-life balance score | Float (double) |
| `change_monthly` | Monthly change in the work-life balance score | Float (double) |
| `change_quarterly` | Quarterly change in the work-life balance score | Float (double) |
| `change_yearly` | Yearly change in the work-life balance score | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Rating change in the work and life balance category" %}
```json
"employee_reviews_score_work_life_balance_change": {
"current": 4.2,
"change_monthly": 0.0,
"change_quarterly": 0.0,
"change_yearly": -0.1
}
```
{% endcode %}
| Data field | Description | Data type |
| --------------------------------------------------- | -------------------------------------------------------------------------------------- | -------------------------- |
| `employee_reviews_score_work_life_balance_by_month` | Work-life balance score by month.
Counts available from 2022.06
| Array of objects (structs) |
| `work_life_balance_score` | Work-life balance score | Float (double) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Work-life balance score by month" %}
```json
"employee_reviews_score_work_life_balance_by_month": [
{
"work_life_balance_score": 3.8,
"date": "2025-01"
},
{
"work_life_balance_score": 3.8,
"date": "2024-09"
}
],
```
{% endcode %}
## Workforce trends
### Key executives
| Data field | Description | Data type |
| ----------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------- |
| `key_executives` | List of key executives.
Key executives are considered people who match any of the following management levels based on their position titles: Director, Head, President/Vice President, C-level, Partner, Founder, Owner
| Array of objects (structs) |
| `parent_id` | Executive's identifier | String |
| `member_full_name` | Executive's name | String |
| `member_position_title` | Executive's job title | String |
**See a snippet of the dataset for reference:**
{% code title="Key executives" %}
```json
"key_executives": [
{
"parent_id": 86953887,
"member_full_name": "John Doe",
"member_position_title": "Partner"
}
],
```
{% endcode %}
### Key employee change events
| Data field | Description | Data type |
| ---------------------------- | ---------------------------------------------------------------- | -------------------------- |
| `key_employee_change_events` | List of key employee change events and corresponding information | Array of objects (structs) |
| `employee_change_event_name` | Employee change event | String |
| `employee_change_event_date` | Employee change event date in `YYYY-MM-DD` format | String (date) |
| `employee_change_event_url` | Event article URL | String |
**See a snippet of the dataset for reference:**
{% code title="Key employee change events" %}
```json
"key_employee_change_events": [
{
"employee_change_event_name": "Example Company Appoints John Doe as Chief Investment Officer",
"employee_change_event_date": "2024-01-18",
"employee_change_event_url" : "https://www.vcaonline.com/news/2024011822/voicestream-technologies-appoints-john-doe-as-chief-investment-officer/"
}
],
```
{% endcode %}
### Key executive arrivals
| Data field | Description | Data type |
| ------------------------ | ----------------------------------------------------------------------------------------------------------------------------------------- | ---------------- |
| `key_executive_arrivals` | List of new executives in the company.
Executives are considered employees that have a decision\_maker = true flag
| Array of strings |
| `parent_id` | Employee identifier | Integer (long) |
| `member_full_name` | Full name | String |
| `member_position_title` | Position title | String |
| `arrival_date` | Start date in the position | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Key employee arrivals" %}
```json
"key_executive_arrivals": [
{
"parent_id": 423235614,
"member_full_name": "John Doe",
"member_position_title": "Partner",
"arrival_date": "Apr 2024"
},
{
"parent_id": 2241368,
"member_full_name": "Marry Moe",
"member_position_title": "Partner",
"arrival_date": "May 2024"
}
],
```
{% endcode %}
### Key executive departures
| Data field | Description | Data type |
| -------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- | ---------------- |
| `key_executive_departures` | List of former executives in the company.
Executives are considered employees that have a decision\_maker = true flag
| Array of strings |
| `parent_id` | Employee identifier | Integer (long) |
| `member_full_name` | Full name | String |
| `member_position_title` | Position title | String |
| `departure_date` | Employment end date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Key employee departures" %}
```json
"key_executive_departures": [
{
"parent_id": 692515608,
"member_full_name": "John Doe",
"member_position_title": "Partner",
"departure_date": "May 2024"
},
{
"parent_id": 83299323,
"member_full_name": "Danny Doe",
"member_position_title": "Partner",
"departure_date": "Aug 2024"
}
],
```
{% endcode %}
### Top companies
| Data field | Description | Data type |
| ------------------------ | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------- |
| `top_previous_companies` | Top ten companies that likely were former workplaces for the current workforce. `Likely to switch` counts are based on `member_experience` data | Array of objects |
| `company_id` | Company identification key | Integer (long) |
| `company_name` | Company name | String |
| `count` | Count to identify the number of transitions | Integer (long) |
| `top_next_companies` | Top ten companies, people will likely switch after their current job.
Likely to switch counts are based on member\_experience data
| Array of objects |
| `company_id` | Company identification key | Integer (long) |
| `company_name` | Company name | String |
| `count` | Count to identify the number of transitions | Integer (long) |
**See a snippet of the dataset for reference:**
{% code title="Top companies" %}
```json
"top_previous_companies": [
{
"company_id": 110,
"company_name": "Example Company",
"count": 5
}
],
"top_next_companies": [
{
"company_id": 110,
"company_name": "Example Sister Company",
"count": 3
}
]
```
{% endcode %}
### Employee count by department
| Data field | Description | Data type |
| ----------------------------------------- | ------------------------------------------------ | --------------- |
| `employees_count_breakdown_by_department` | Breakdown of employee count by department | Object (struct) |
| `employees_count_medical` | Number of employees in the medical department | Integer (long) |
| `employees_count_sales` | Number of employees in the sales department | Integer (long) |
| `employees_count_hr` | Number of employees in the HR department | Integer (long) |
| `employees_count_legal` | Number of employees in the legal department | Integer (long) |
| `employees_count_marketing` | Number of employees in the marketing department | Integer (long) |
| `employees_count_finance` | Number of employees in the finance department | Integer (long) |
| `employees_count_tech` | Number of employees in the tech department | Integer (long) |
| `employees_count_consulting` | Number of employees in the consulting department | Integer (long) |
| `employees_count_operations` | Number of employees in the operations department | Integer (long) |
| `employees_count_other_department` | Number of employees in other departments | Integer (long) |
| `employees_count_product` | Number of employees in the product department | Integer (long) |
**See a snippet of the dataset for reference:**
{% code title="Employee count by department" %}
```json
"employees_count_breakdown_by_department": {
"employees_count_medical": 0,
"employees_count_sales": 24,
"employees_count_hr": 8,
"employees_count_legal": 2,
"employees_count_marketing": 5,
"employees_count_finance": 7,
"employees_count_tech": 63,
"employees_count_consulting": 2,
"employees_count_operations": 2,
"employees_count_other_department": 99,
"employees_count_product": 12
},
```
{% endcode %}
| Data field | Description | Data type |
| -------------------------------------------------- | ----------------------------------------------------------------- | -------------- |
| `employees_count_breakdown_by_department_by_month` | Employee count changes by month and department | Object |
| `employees_count_medical` | Employee count in the medical department | Integer (long) |
| `employees_count_sales` | Employee count in the sales department | Integer (long) |
| `employees_count_hr` | Employee count in the HR department | Integer (long) |
| `employees_count_legal` | Employee count in the legal department | Integer (long) |
| `employees_count_marketing` | Employee count in the marketing department | Integer (long) |
| `employees_count_finance` | Employee count in the finance department | Integer (long) |
| `employees_count_technical` | Employee count in the technical department | Integer (long) |
| `employees_count_consulting` | Employee count in the consulting department | Integer (long) |
| `employees_count_operations` | Employee count in the operations department | Integer (long) |
| `employees_count_product` | Employee count in the product department | Integer (long) |
| `employees_count_general_management` | Employee count in the general management department | Integer (long) |
| `employees_count_administrative` | Employee count in the administrative department | Integer (long) |
| `employees_count_customer_service` | Employee count in the customer service department | Integer (long) |
| `employees_count_project_management` | Employee count in the project management department | Integer (long) |
| `employees_count_design` | Employee count in the design department | Integer (long) |
| `employees_count_research` | Employee count in the research department | Integer (long) |
| `employees_count_trades` | Employee count in the trades department | Integer (long) |
| `employees_count_real_estate` | Employee count in the real estate department | Integer (long) |
| `employees_count_education` | Employee count in the education department | Integer (long) |
| `employees_count_other_department` | Employee count in the other departments | Integer (long) |
| `date` | Record date.
Counts available from 2020.01
| String (date) |
**See a snippet of the dataset for reference:**
{% code title="Employee count by department" %}
```json
"employees_count_breakdown_by_department_by_month": [
{
"employees_count_breakdown_by_department": {
"employees_count_sales": 0,
"employees_count_hr": 0,
"employees_count_legal": 45,
"employees_count_marketing": 4,
"employees_count_finance": 0,
"employees_count_technical": 0,
"employees_count_consulting": 0,
"employees_count_operations": 55,
"employees_count_product": 0,
"employees_count_general_management": 0,
"employees_count_administrative": 0,
"employees_count_customer_service": 0,
"employees_count_project_management": 34,
"employees_count_design": 0,
"employees_count_research": 0,
"employees_count_trades": 56,
"employees_count_real_estate": 0,
"employees_count_education": 0,
"employees_count_other_department": 0,
"employees_count_other_department": 5
},
"date": "2021-01"
}
]
```
{% endcode %}
| Data field | Description | Data type |
| ---------------------------- | ------------------------- | ---------------- |
| `employees_count_by_country` | Employee count by country | Array of objects |
| `country` | Country | String |
| `employee_count` | Employee count | Integer |
**See a snippet of the dataset for reference:**
{% code title="Employee count by country" %}
```json
"employees_count_by_country": [
{
"country": "Germany",
"employee_count": 1
},
{
"country": "France",
"employee_count": 1
}
],
```
{% endcode %}
| Data field | Description | Data type |
| ------------------------------------- | ----------------------------------------------------------------- | -------------------------- |
| `employees_count_by_country_by_month` | Employee count by country and month | Array of objects (structs) |
| `employees_count_by_country` | Employee count by country | Object (struct) |
| `country` | Country | String |
| `employee_count` | Employee count | Integer (long) |
| `date` | Record date.
Counts available from 2020.01
| String (date) |
**See a snippet of the dataset for reference:**
{% code title="Employee count by country" %}
```json
"employees_count_by_country_by_month": [
{
"employees_count_by_country": [
{
"country": "United States",
"employee_count": 43
}
],
"date": "2021-01"
}
]
```
{% endcode %}
| Data field | Description | Data type |
| --------------------------------------- | ------------------------------------------- | --------- |
| `employees_count_breakdown_by_region` | Employee count breakdown by region | Object |
| `employees_count_eastern_europe` | Employee count in Eastern Europe | Integer |
| `employees_count_latin_america` | Employee count in Latin America | Integer |
| `employees_count_southern_europe` | Employee count in Southern Europe | Integer |
| `employees_count_sub_saharan_africa` | Employee count in Sub-Saharan Africa | Integer |
| `employees_count_central_asia` | Employee count in Central Asia | Integer |
| `employees_count_northern_america` | Employee count in Northern America | Integer |
| `employees_count_australia_new_zealand` | Employee count in Australia and New Zealand | Integer |
| `employees_count_northern_europe` | Employee count in Northern Europe | Integer |
| `employees_count_south_eastern_asia` | Employee count in Southeast Asia | Integer |
| `employees_count_polynesia` | Employee count in Polynesia | Integer |
| `employees_count_southern_asia` | Employee count in Southern Asia | Integer |
| `employees_count_northern_africa` | Employee count in Northern Africa | Integer |
| `employees_count_melanesia` | Employee count in Melanesia | Integer |
| `employees_count_western_europe` | Employee count in Western Europe | Integer |
| `employees_count_western_asia` | Employee count in Western Asia | Integer |
| `employees_count_eastern_asia` | Employee count in Eastern Asia | Integer |
| `employees_count_micronesia` | Employee count in Micronesia | Integer |
| `employees_count_unknown` | Employee count in unassigned region | Integer |
**See a snippet of the dataset for reference:**
{% code title="Employee count by department" %}
```json
"employees_count_breakdown_by_region": {
"employees_count_eastern_europe" : 4,
"employees_count_latin_america": 5,
"employees_count_southern_europe": 6,
"employees_count_sub_saharan_africa": 0,
"employees_count_central_asia": 15,
"employees_count_northern_america": 0,
"employees_count_australia_new_zealand": 0,
"employees_count_northern_europe": 0,
"employees_count_south_eastern_asia": 0,
"employees_count_polynesia": 2,
"employees_count_southern_asia": 0,
"employees_count_northern_africa": 3,
"employees_count_melanesia": 0,
"employees_count_western_europe": 0,
"employees_count_western_asia": 0,
"employees_count_eastern_asia": 9,
"employees_count_micronesia": 0,
"employees_count_unknown": 0
}
```
{% endcode %}
| Data field | Description | Data type |
| ---------------------------------------------- | ----------------------------------------------------------------- | ---------------- |
| `employees_count_breakdown_by_region_by_month` | Employee count breakdown by region and date | Array of objects |
| `employees_count_breakdown_by_region` | Employee count breakdown by region | Object (struct) |
| `employees_count_eastern_europe` | Employee count in Eastern Europe | Integer |
| `employees_count_latin_america` | Employee count in Latin America | Integer |
| `employees_count_southern_europe` | Employee count in Southern Europe | Integer |
| `employees_count_sub_saharan_africa` | Employee count in Sub-Saharan Africa | Integer |
| `employees_count_central_asia` | Employee count in Central Asia | Integer |
| `employees_count_northern_america` | Employee count in Northern America | Integer |
| `employees_count_australia_new_zealand` | Employee count in Australia and New Zealand | Integer |
| `employees_count_northern_europe` | Employee count in Northern Europe | Integer |
| `employees_count_south_eastern_asia` | Employee count in Southeast Asia | Integer |
| `employees_count_polynesia` | Employee count in Polynesia | Integer |
| `employees_count_southern_asia` | Employee count in Southern Asia | Integer |
| `employees_count_northern_africa` | Employee count in Northern Africa | Integer |
| `employees_count_melanesia` | Employee count in Melanesia | Integer |
| `employees_count_western_europe` | Employee count in Western Europe | Integer |
| `employees_count_western_asia` | Employee count in Western Asia | Integer |
| `employees_count_eastern_asia` | Employee count in Eastern Asia | Integer |
| `employees_count_micronesia` | Employee count in Micronesia | Integer |
| `employees_count_unknown` | Employee count in unassigned region | Integer |
| `date` | Record date.
Counts available from 2020.01
| String (date) |
**See a snippet of the dataset for reference:**
{% code title="Employee count by department" %}
```json
"employees_count_breakdown_by_region_by_month": [
{
"employees_count_breakdown_by_region": {
"employees_count_eastern_europe": 3,
"employees_count_latin_america": 0,
"employees_count_southern_europe": 0,
"employees_count_sub_saharan_africa": 0,
"employees_count_central_asia": 0,
"employees_count_northern_america": 5,
"employees_count_australia_new_zealand": 0,
"employees_count_northern_europe": 7,
"employees_count_south_eastern_asia": 0,
"employees_count_polynesia": 0,
"employees_count_southern_asia": 0,
"employees_count_northern_africa": 0,
"employees_count_melanesia": 5,
"employees_count_western_europe": 0,
"employees_count_western_asia": 6,
"employees_count_eastern_asia": 0,
"employees_count_micronesia": 0,
"employees_count_unknown": 0
},
"date": "2021-01"
}
]
```
{% endcode %}
### Employee count by seniority
| Data field | Description | Data type |
| ---------------------------------------- | ------------------------------------------------------- | --------------- |
| `employees_count_breakdown_by_seniority` | Breakdown of employee count by seniority level | Object (struct) |
| `employees_count_owner` | Number of employees with the `Owner` job title | Integer (long) |
| `employees_count_founder` | Number of employees with the `Founder` job title | Integer (long) |
| `employees_count_clevel` | Number of C-level employees | Integer (long) |
| `employees_count_partner` | Number of employees with the `Partner` job title | Integer (long) |
| `employees_count_vp` | Number of employees with the `Vice President` job title | Integer (long) |
| `employees_count_head` | Number of employees with the `Head` job title | Integer (long) |
| `employees_count_director` | Number of employees with the `Director` job title | Integer (long) |
| `employees_count_manager` | Number of employees with the `Manager` job title | Integer (long) |
| `employees_count_senior` | Number of senior-level employees | Integer (long) |
| `employees_count_mid` | Number of mid-level employees | Integer (long) |
| `employees_count_junior` | Number of junior-level employees | Integer (long) |
| `employees_count_intern` | Number of interns | Integer (long) |
| `employees_count_other_management` | Number of employees in other management roles | Integer (long) |
**See a snippet of the dataset for reference:**
{% code title="Employee count by seniority" %}
```json
"employees_count_breakdown_by_seniority": {
"employees_count_owner": 0,
"employees_count_founder": 0,
"employees_count_clevel": 3,
"employees_count_partner": 1,
"employees_count_vp": 8,
"employees_count_head": 1,
"employees_count_director": 10,
"employees_count_manager": 31,
"employees_count_senior": 73,
"employees_count_mid": 8,
"employees_count_junior": 1,
"employees_count_intern": 0,
"employees_count_other_management": 88
},
```
{% endcode %}
| Data field | Description | Data type |
| ------------------------------------------------- | ----------------------------------------------------------------- | ---------------- |
| `employees_count_breakdown_by_seniority_by_month` | Employee count breakdown seniority and date | Array of objects |
| `employees_count_breakdown_by_seniority` | Employee count breakdown by seniority | Object (struct) |
| `employees_count_owner` | Number of owners in the company | Integer |
| `employees_count_founder` | Number of founders in the company | Integer |
| `employees_count_clevel` | Number of C-level employees in the company | Integer |
| `employees_count_partner` | Number of partners in the company | Integer |
| `employees_count_vp` | Number of vice presidents in the company | Integer |
| `employees_count_head` | Number of head-level employees in the company | Integer |
| `employees_count_director` | Number of directors in the company | Integer |
| `employees_count_manager` | Number of managers in the company | Integer |
| `employees_count_senior` | Number of seniors in the company | Integer |
| `employees_count_intern` | Number of interns in the company | Integer |
| `employees_count_specialist` | Number of specialists in the company | Integer |
| `employees_count_other_management` | Number of other management employees in the company | Integer |
| `date` | Record date.
Counts available from 2020.01
| Integer |
{% code title="Employee count by seniority" %}
```json
"employees_count_breakdown_by_seniority_by_month": [
{
"employees_count_breakdown_by_seniority": {
"employees_count_owner": 5,
"employees_count_founder": 3,
"employees_count_clevel": 7,
"employees_count_partner": 2,
"employees_count_vp": 6,
"employees_count_head": 4,
"employees_count_director": 10,
"employees_count_manager": 15,
"employees_count_senior": 20,
"employees_count_intern": 8,
"employees_count_specialist": 12,
"employees_count_other_management": 5
},
"date": "2023-09"
}
]
```
{% endcode %}
### Employee count changes
| Data field | Description | Data type |
| ----------------------------- | -------------------------------------------------------------- | --------------- |
| `employees_count_change` | Changes in the number of employees over different time periods | Object (struct) |
| `current` | Current number of employees | Integer (long) |
| `change_monthly` | Monthly change in employee count | Integer (long) |
| `change_monthly_percentage` | Monthly percentage change in employee count | Float (double) |
| `change_quarterly` | Quarterly change in employee count | Integer (long) |
| `change_quarterly_percentage` | Quarterly percentage change in employee count | Float (double) |
| `change_yearly` | Yearly change in employee count | Integer (long) |
| `change_yearly_percentage` | Yearly percentage change in employee count | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Employee count change" %}
```json
"employees_count_change": {
"current": 324,
"change_monthly": -26,
"change_monthly_percentage": -7.428571428571429,
"change_quarterly": -213,
"change_quarterly_percentage": -39.66480446927375,
"change_yearly": -244,
"change_yearly_percentage": -42.95774647887324
},
```
{% endcode %}
| Data field | Description | Data type |
| -------------------------- | ------------------------------------------------------------------------------------- | -------------------------- |
| `employees_count_by_month` | Employee count changes by month.
Counts available from 2019.01
| Array of objects (structs) |
| `employees_count` | Number of employees | Integer (long) |
| `date` | Record date | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Employees count by month" %}
```json
"employees_count_by_month": [
{
"employees_count": 0,
"date": "2023-11"
},
{
"employees_count": 0,
"date": "2024-01"
}
],
```
{% endcode %}
### Active job postings
| Data field | Description | Data type |
| --------------------------- | --------------------------------------------------------- | ---------------- |
| `active_job_postings_count` | Number of active job postings associated with the company | Integer (long) |
| `active_job_postings` | Active job postings | Array of structs |
| `job_posting_id` | Professional network Job ID | Long |
| `job_posting_title` | Job title posted by the recruiter | String |
**See a snippet of the dataset for reference:**
{% code title="Active jobs" %}
```json
"active_job_postings_count": 1,
"active_job_postings_titles": [
{
"job_posting_id": 1234567890,
"job_posting_title": "Product Manager",
}
]
```
{% endcode %}
| Data field | Description | Data type |
| ------------------------------------ | ----------------------------------------------------------------- | --------------- |
| `active_job_postings_count_by_month` | Active job postings by month | Object (struct) |
| `active_job_postings_count` | Job posting count | Integer (long) |
| `date` | Record date.
Counts available from 2021.11
| String (date) |
**See a snippet of the dataset for reference:**
{% code title="Active jobs" %}
```json
"active_job_postings_count_by_month": {
"active_job_postings_count": 34,
"date": "2024-11"
}
```
{% endcode %}
### Active jobs count changes
| Data field | Description | Data type |
| ---------------------------------- | ------------------------------------------------------------------- | --------------- |
| `active_job_postings_count_change` | Changes in the number of active job postings over different periods | Object (struct) |
| `current` | Current number of active job postings | Integer (long) |
| `change_monthly` | Monthly change in active job postings count | Integer (long) |
| `change_monthly_percentage` | Monthly percentage change in active job postings count | Float (double) |
| `change_quarterly` | Quarterly change in active job postings count | Integer (long) |
| `change_quarterly_percentage` | Quarterly percentage change in active job postings count | Float (double) |
| `change_yearly` | Yearly change in active job postings count | Integer (long) |
| `change_yearly_percentage` | Yearly percentage change in active job postings count | Float (double) |
**See a snippet of the dataset for reference:**
{% code title="Changes in posted jobs" %}
```json
"active_job_postings_count_change": {
"current": 11540,
"change_monthly": 54,
"change_monthly_percentage": 0.467822984671254,
"change_quarterly": 743,
"change_quarterly_percentage": 6.431215746103567,
"change_yearly": 1594,
"change_yearly_percentage": 14.563924765213854
}
```
{% endcode %}
## Salaries
### Base salary
| Data field | Description | Data type |
| ------------------- | ------------------------------------------------------------------------- | -------------------------- |
| `base_salary` | List of base salary details related to a specific job title | Array of objects (structs) |
| `title` | Job title | String |
| `salary_p25` | 25th percentile salary | Float (double) |
| `salary_median` | Median salary | Float (double) |
| `salary_p75` | 75th percentile salary | Float (double) |
| `currency` | Salary currency | String |
| `pay_period` | Pay period | String |
| `salary_updated_at` | Date when the salary information was last updated in `YYYY-MMM-DD` format | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Base salary by job title " %}
```json
"base_salary": [
{
"title": "Software Engineer",
"salary_p25": 4500000.0,
"salary_median": 5500000.0,
"salary_p75": 7875000.0,
"currency": "COP",
"pay_period": "MONTHLY",
"salary_updated_at": "2018-05-31"
},
{
"title": "Devops Engineer",
"salary_p25": 1100000.0,
"salary_median": 1300000.0,
"salary_p75": 1500000.0,
"currency": "INR",
"pay_period": "ANNUAL",
"salary_updated_at": "2023-01-16"
}
],
```
{% endcode %}
### Additional pay
| Data field | Description | Data type |
| ----------------------- | -------------------------------------------------------------------------------- | -------------------------- |
| `additional_pay` | List of additional pay details related to a specific job title | Array of objects (structs) |
| `title` | Job title | String |
| `additional_pay_values` | Additional pay values | Array of objects (structs) |
| `additional_pay_p25` | 25th percentile of additional pay | Float (double) |
| `additional_pay_median` | Median of additional pay | Float (double) |
| `additional_pay_p75` | 75th percentile of additional pay | Float (double) |
| `additional_pay_type` | Additional pay type | String |
| `currency` | Pay currency | String |
| `pay_period` | Pay period | String |
| `salary_updated_at` | Date when the additional pay information was last updated in `YYYY-MM-DD` format | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Additional pay by job title" %}
```json
"additional_pay": [
{
"title": "Implementation Manager",
"additional_pay_values": [
{
"additional_pay_p25": 6598.52,
"additional_pay_median": 8798.02,
"additional_pay_p75": 12317.23,
"additional_pay_type": "Cash Bonus"
}
],
"currency": "USD",
"pay_period": "ANNUAL",
"salary_updated_at": "2024-02-10"
}
]
```
{% endcode %}
### Total salary
| Data field | Description | Data type |
| ------------------- | ------------------------------------------------------------------------ | -------------------------- |
| `total_salary` | List of total salary details related to a specific job title | Array of objects (structs) |
| `title` | Job title | String |
| `salary_p25` | 25th percentile salary | Float (double) |
| `salary_median` | Median salary | Float (double) |
| `salary_p75` | 75th percentile salary | Float (double) |
| `currency` | Salary currency | String |
| `pay_period` | Pay period | String |
| `salary_updated_at` | Date when the salary information was last updated in `YYYY-MM-DD` format | String (date) |
**See a snippet of the dataset for reference:**
{% code title="Total salary by job title " %}
```json
"total_salary": [
{
"title": "Marketing",
"salary_p25": 45.51,
"salary_median": 60.68,
"salary_p75": 84.07,
"currency": "USD",
"pay_period": "HOURLY",
"salary_updated_at": "2025-02-10"
}
],
```
{% endcode %}