> ## Documentation Index > Fetch the complete documentation index at: https://developers.explorium.ai/llms.txt > Use this file to discover all available pages before exploring further. # Business Intent Topics (Bombora) ### **Description** The **Business Intent Topics (Bombora)** enrichment reveals which topics companies are actively researching online, providing deeper visibility into their current business interests and buying intent. Powered by **Bombora’s weekly intent dataset**, it analyzes topic-level content consumption patterns to detect **surging interest and engagement signals** at the company level. For each input company (`business_id`), the enrichment returns a **ranked list of intent topics** with a **composite score above 60**, grouped by category and timestamped by week. The results highlight which topics a company is researching most intensely and classify them by **intent level** (e.g., *In-Depth, Active, Early*). This enrichment is particularly useful for: * **Sales prioritization:** Identify accounts actively researching your solution space. * **Intent-based marketing:** Personalize outreach based on buyer interest. * **ABM activation:** Power account-based strategies with real-time buying signals. * **Pipeline acceleration:** Engage prospects showing increased purchase readiness. **Refresh cadence:** Weekly Raw intent data powered by: Image(1) Pn *** ### **Input** Provide a list of `business_id` values obtained from the **Match Businesses API**. **Parameters:** * `topic_parameters` — semicolon-separated list of "category: topic" filters\ (e.g., `technology: ios;other: vendor profiling`). To build this list, use the Autocomplete endpoint with`business_intent_topics` — and preferably `semantic_search=true` — to retrieve a broader, smarter set of intent topics. This ensures your topic list is accurate, relevant, and aligned with Bombora’s taxonomy.\ You can also download the full topics list if needed (see details below). * `min_score` — optional integer > 60. If omitted, the default threshold is 60. > 💡 **Recommendation:**\ > To achieve a meaningful and accurate measurement of intent, it is strongly recommended to include **at least 12 topics** that reflect the company’s genuine areas of interest.\ > Providing too few topics — or omitting the list entirely — will return *all* available topics for the company, which may include many unrelated subjects and lead to misleading or noisy intent insights. ### **Intent Topics Reference List** There are two ways to discover valid intent topics for the `topics` parameter: Query the Autocomplete endpoint with `business_intent_topics` (preferably with `semantic_search=true`) to interactively find topics relevant to your use case. Download the complete list of supported Bombora intent topics as a CSV file. The list is refreshed weekly to stay aligned with Bombora's taxonomy. The CSV contains a single `intent_topic` column, with each row formatted as `category: topic` (e.g., `accounting: accounts payable`) — the exact format expected by the `topics` parameter. The file is automatically regenerated **once a week** to reflect the latest Bombora taxonomy, so we recommend re-downloading it periodically rather than caching a local copy long-term. ### **Processing** The enrichment process queries Bombora’s weekly dataset to identify surging topics for each company in the provided list.\ Only topics with `composite_score >= threshold` are returned, where: * `threshold = min_score` (if provided and >60) * otherwise `threshold = 60` (default) *** ### **Output** Returns, for each input business\_id, the company’s top intent topics, including the composite score, engagement level, and weekly timestamp. ```json theme={null} curl -X 'POST' \ 'https://api.explorium.ai/v1/businesses/bombora_intent/enrich' \ -H 'accept: application/json' \ -H 'api_key: "your api_key" \ -H 'Content-Type: application/json' \ -d '{ "request_context": {}, "parameters": { "topics": [ "training & development: corporate universities;training & development: career management;training & development: group coaching;training & development: classroom management;training & development: experiential learning;training & development: gmat test preparation;training & development: seminars and educational programs;training & development: sat preparation;training & development: team building;training & development: gmat test preparation;training & development: essential skills;training & development: gre test preparation" ], "min_score": 76 }, "business_id": "8adce3ca1cef0c986b22310e369a0793" } ``` ```json theme={null} { "response_context": { "correlation_id": "34e96a94f55d40a18994f55b2f36ecb8", "request_status": "success", "time_took_in_seconds": 43.515 }, "data": { "business_id": "8adce3ca1cef0c986b22310e369a0793", "company_name": "apple", "company_website": "apple.com", "date_stamp": "20251102", "intent_topics": "[{\"topic\":\"training & development: gmat test preparation\",\"composite_score\":76},{\"topic\":\"training & development: seminars and educational programs\",\"composite_score\":82},{\"topic\":\"training & development: classroom management\",\"composite_score\":77},{\"topic\":\"training & development: experiential learning\",\"composite_score\":76}]", "level_of_intent": "In Depth Research", "topic_count": "4 / 12" }, "entity_id": "8adce3ca1cef0c986b22310e369a0793" } ``` * **`Always provide valid business_id inputs`** retrieved from the **Match Businesses** API. * **`Specify topic_parameters`** to focus enrichment results on relevant industries or technologies. * **`Use min_score`** only if you wish to raise the threshold above 60 — values ≤60 are not valid. * **Check for null values** — if Bombora has no data for a given domain, all topic-related fields will return null. * **Combine intent data** with firmographic and technographic enrichments for full go-to-market insights. * **Use the Autocomplete endpoint** with `business_intent_topics` — and preferably `semantic_search=true` — to build accurate and relevant `topic_parameters` before running enrichment. | Signal | API Name | Description | Data Type | | ----------------- | --------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | level\_of\_intent | Level of Intent | Indicates how actively a company engaged with selected topics during the past week.

**Calculation:** Number of topics with a composite score above 25% **divided by** the total number of input topics.

**Ranges:**
• >25% → *In-Depth Research*
• 5–25% → *Active Research*
• \<5% → *Early Research*


**Recommendation:** To ensure a meaningful and accurate reflection of intent, it is recommended to input **at least 12 topics**that are relevant to the areas of interest.

Returns `null` when no input topics are available. | CATEGORY | | topic\_count | Topic Count | Shows the number of topics with a composite score above 60, relative to all topics evaluated (e.g., 5/5). When no input topics are provided, all topics are returned. | TEXT | | intent\_topics | Intent Topics | Contains an array of objects summarizing the company’s active interest in specific Bombora topics over a given week. Each object includes the topic name, category, composite score, and date. | TEXT | | company\_website | Company Website | The company’s primary website or domain URL. | URL | | company\_name | Company Name | The official or recognized name of the company. | TEXT | | date\_stamp | date | The date of the most recent Bombora data file (weekly), in format YYYYMMDD | TEXT | 📌 \_For additional enrichment options, explore related API endpoints below. ## OpenAPI ````yaml post /v1/businesses/bombora_intent/enrich openapi: 3.1.0 info: title: Partner Service version: 0.2.365 servers: - url: https://api.explorium.ai description: AgentSource Server security: [] paths: /v1/businesses/bombora_intent/enrich: post: tags: - BusinessEnrichments summary: Bombora Intent operationId: businesses_bombora_intent_enrich requestBody: content: application/json: schema: $ref: '#/components/schemas/BomboraIntentEnrichRequest' required: true responses: '200': description: Successful Response content: application/json: schema: $ref: >- #/components/schemas/BusinessesEnrichResponse_BomboraIntentOutputSchema_ '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - APIKeyHeader: [] - APIKeyHeader: [] components: schemas: BomboraIntentEnrichRequest: properties: request_context: type: object title: Request Context nullable: true example: null parameters: $ref: '#/components/schemas/BomboraIntentEnrichmentParams' business_id: type: string pattern: ^[a-f0-9]{32}$ title: Business Id additionalProperties: false type: object required: - business_id title: BomboraIntentEnrichRequest BusinessesEnrichResponse_BomboraIntentOutputSchema_: properties: response_context: $ref: '#/components/schemas/ResponseContext' data: anyOf: - $ref: '#/components/schemas/BomboraIntentOutputSchema' - items: $ref: '#/components/schemas/BomboraIntentOutputSchema' type: array title: Data entity_id: anyOf: - type: string pattern: ^[a-f0-9]{32}$ - type: string pattern: ^[a-f0-9]{40}$ title: Entity Id type: object required: - response_context title: BusinessesEnrichResponse[BomboraIntentOutputSchema] description: 'This is base response model for all responses in partner service. ' HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError BomboraIntentEnrichmentParams: properties: topics: items: type: string type: array title: Topics min_score: type: integer title: Min Score additionalProperties: false type: object title: BomboraIntentEnrichmentParams ResponseContext: properties: correlation_id: type: string title: Correlation Id request_status: $ref: '#/components/schemas/RequestStatus' time_took_in_seconds: type: number title: Time Took In Seconds type: object required: - correlation_id - request_status - time_took_in_seconds title: ResponseContext BomboraIntentOutputSchema: properties: business_id: type: string pattern: ^[a-f0-9]{32}$ title: Business Id company_name: type: string maxLength: 256 title: Company Name company_website: type: string maxLength: 2048 pattern: >- ^(?:(?:[a-z0-9\u00a1-\uffff][a-z0-9\u00a1-\uffff_-]{0,62})?[a-z0-9\u00a1-\uffff]\.)+[a-z\u00a1-\uffff]{2,}\.?(?:[/?#]\S*)?$ format: uri title: Company Website date_stamp: type: string title: Date Stamp intent_topics: type: string title: Intent Topics level_of_intent: type: string title: Level Of Intent topic_count: type: string title: Topic Count type: object required: - intent_topics title: BomboraIntentOutputSchema ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type type: object required: - loc - msg - type title: ValidationError RequestStatus: type: string enum: - success - miss - failure title: RequestStatus description: >- The `RequestStatus` class is an enumeration that defines the possible statuses of a request. This enum is used to indicate whether a request was successful, missed, or failed. It ensures consistent handling of request statuses across the application. Attributes: SUCCESS: Indicates that the request was successfully processed. MISS: Indicates that the request did not find any matching data. FAILURE: Indicates that the request encountered an error or failure. securitySchemes: APIKeyHeader: type: apiKey in: header name: api_key ````