Filters businesses by country, company size, revenue, and more. Returns minimal data needed for further filtering, deduplication, or record previews.
Coverage
How It Works
Request Schema
Pagination, Filtering & Modes Parameters
| Parameter | Type | Description |
|---|---|---|
size | Number | The total maximum number of records to return across all pages. Must be ≤ 60,000. |
page_size | Number | Number of records to return per page. Maximum value: 100. |
page | Number | The page number to retrieve (1-based index). Defaults to 1 if not specified. |
size is smaller than page_size * page, the last page may contain fewer records or be empty."filters" key, as a JSON object.Each filter field accepts:values: for multiple possible matches (e.g. "values": ["11-50", "51-200"])values are matched using an OR condition.mode parameter defines the level of detail in the returned data.| Mode | Description |
|---|---|
full | Returns the complete data object for each prospect. Use this when full detail is required for processing or display. |
page_size to control payload size for better performance.size to set an upper limit and avoid unintentionally requesting large datasets.Google category, LinkedIn industry, or NAICS code. Combining them is not supported.Example Request (cURL)
Business Filters
| Parameter | Description | Notes / Best Practices |
|---|---|---|
country_code | Filter accounts by their HQ’s country using alpha-2 country codes. Example: ["us", "ca"] | - Use autocomplete to search by country name and select the correct two-letter code. - Uses a list of values. - Logic checks whether the country code matches the account location. |
region_country_code | Filter accounts by their HQ’s region using ISO 3166-2 country-subdivision codes. Example: ["us-ut", "us-ca"] | - Use autocomplete to search for a region after selecting a country. Format will automatically apply as country-region (e.g., us-ca). - Uses multiple values. - Logic verifies if the region code matches the structured field. |
city_region_country | Filter accounts by geographic region, down to city-level granularity. Example: ["San Francisco, CA, US"] | - Use autocomplete with cascading dropdowns (country → region → city). - Accepts a list of full location strings. - Logic checks address fields for match. |
filters.city_region | Filter accounts by geographic region with city-level granularity. Example: ["New York--Jersey City--Newark, NY--NJ"] | - Use autocomplete to search and select the exact city region name as defined in the system. - Uses a list of values. - Only exact values returned by autocomplete are supported (free text is not supported). - Logic checks whether the account is mapped to the selected city region. |
company_revenue | Filter accounts by annual revenue generated at all company sites. Categories: ["0-500K", ..., "10B-100B"] | - Use autocomplete to search and select a revenue range from the predefined list. - Accepts a list of values. - Logic compares revenue input against company revenue fields. |
company_age | Filter accounts by how many years since they were established. Categories: ["0-3", "3-6", ..., "20+"] | - Use autocomplete to select a range representing company age. - Accepts multiple values. - Logic compares establishment year against current date to determine match. |
google_category | Filter accounts by their classified Google business category. Example: ["Paving contractor", "Retail"] | - Use autocomplete to search and select from Google’s list of business categories. - Accepts values. - Logic filters companies based on Google’s classification field. |
naics_category | Filter accounts by their 2017 NAICS industry code. Example: ["23", "5611"] | - Use autocomplete to search and select valid NAICS industry codes. - Uses multiple values. - Logic matches selected code to structured industry metadata. |
linkedin_category | Filter accounts by their classified LinkedIn® business category. Example: ["software development", "investment banking"] | - Use autocomplete to search and select from LinkedIn® list of industry categories. - Accepts a list of values. - Logic filters based on LinkedIn® business category field. |
company_tech_stack_category | Filter accounts by the technology categories they use. Example: ["Marketing", "CRM", "Cloud Services"] | - Use autocomplete to search and select technology categories from a predefined list. - Uses multiple values. - Logic checks whether the account is associated with technologies in those categories. |
company_tech_stack_tech | Filter accounts by the specific technologies they use. Example: ["JavaScript", "HTML5", "Apache"] | - Use autocomplete to search and select specific technologies from the available list. - Accepts a list of values. - Logic checks for presence of selected technologies in the company’s tech stack. |
company_name | Filter accounts by specific company names. Example: ["Google", "Walmart"] | - Use autocomplete to search and select company names. - Accepts one or more values. - Logic performs exact or fuzzy match depending on configuration. |
number_of_locations | Filter accounts by how many office locations they operate. Example: ["1", "2-5", "6+"] | - Use autocomplete to select location range. - Accepts a list of values. - Logic checks for company location count metadata. |
website_keywords | Filter accounts by specific keywords mentioned on their websites. Example: ["sustainability", "machine learning"] | - Use keyword search to find companies mentioning certain terms. - Accepts free-text keywords or predefined tags. - Logic performs keyword match in indexed website content. |
topics | Filters businesses based on active research around specific intent topics, returningbusiness_id values of companies demonstrating relevant interest. Example: ["machine learning & artificial intelligence: openai", "technology: iphone"] | - Accepts one or more topic strings following Bombora’s taxonomy. - Returns businesses with a composite score >60 for at least one matching topic. - Recommended for pre-filtering businesses prior to enrichment or campaign targeting - Use the autocomplete endpoint with business_intent_topics — and withsemantic_search=true — to discover broader and smarter intent-topic suggestions. Enabling semantic search helps surface wider contextual topics that users are actively researching, ensuring more accurate and effective filtering. |
| events.values | Filter accounts by specific business event types (a list of event identifiers). Example: ["new_product", "employee_joined_company"] | - Must be used together with events.last_occurrence.- Uses a list of values. - The full list and definitions are available under Business Events. |
| events.last_occurrence | Filter accounts based on whether the selected events occurred within the last N days. Example: 45 | - Must be used together with events.values.- Accepts an integer between 30 and 90. - Checks events that occurred within the last N days (lookback window). - See the full list of supported event types below. |
Full list of supported event_type values
The mode of fetching businesses.
full, preview "full"
The maximum number of businesses to return. Max size is 60000
1 <= x <= 600003
The maximum number of businesses in a page. Max limit is 500
1 <= x <= 5003
null
The page number to fetch.
x >= 11
List of business ids to exclude from the response.
1000null
{}The sort values from the last document returned by the previous page. If provided, cursor pagination is used instead of page-based pagination. send "null" to start with next_cursor pagination from the beginning.
null
Successful Response
This is base response model for all responses in partner service.
The total number of pages.
x >= 0List of businesses that match the filters.
The total number of businesses that match the filters.
x >= 0The page number of the response.
x >= 0