# Check funding signal and founding year for target accounts

**Use case:** 

Look up a list of target account domains and get founding year, a funding signal with the latest round type and date, size band and description for each company. Compatible output adds field names that common LinkedIn scrapers use.

## Input

```json
{
  "domains": [
    "notion.so",
    "openai.com",
    "canva.com"
  ],
  "minLeadScore": 0,
  "outputFormat": "compatible",
  "maxChargeUsd": 0,
  "sourceTag": "",
  "concurrency": 1
}
```

## Output

```json
{
  "inputDomain": {
    "label": "Input domain",
    "format": "string"
  },
  "companyName": {
    "label": "Company name",
    "format": "string"
  },
  "companyDescription": {
    "label": "Company description",
    "format": "string"
  },
  "foundedYear": {
    "label": "Founded year",
    "format": "integer"
  },
  "industry": {
    "label": "Industry",
    "format": "string"
  },
  "employeeCount": {
    "label": "Employee count",
    "format": "integer"
  },
  "employeeSizeBand": {
    "label": "Employee size band",
    "format": "string"
  },
  "location": {
    "label": "Location",
    "format": "string"
  },
  "hqLocality": {
    "label": "HQ city/locality",
    "format": "string"
  },
  "hqRegion": {
    "label": "HQ region",
    "format": "string"
  },
  "countryCode": {
    "label": "Country code",
    "format": "string"
  },
  "hasFunding": {
    "label": "Funding recorded",
    "format": "boolean"
  },
  "lastFundingRoundType": {
    "label": "Latest funding round type",
    "format": "string"
  },
  "lastFundingRoundDate": {
    "label": "Latest funding round date",
    "format": "string"
  },
  "websiteUrl": {
    "label": "Website URL",
    "format": "string"
  },
  "linkedinUrl": {
    "label": "LinkedIn URL",
    "format": "string"
  },
  "dataCompleteness": {
    "label": "Completeness (%)",
    "format": "integer"
  },
  "scrapedAt": {
    "label": "Scraped at",
    "format": "string"
  },
  "inputQuery": {
    "label": "Input query",
    "format": "string"
  },
  "leadScore": {
    "label": "Lead score (0-100)",
    "format": "integer"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The Firmographics by Domain - Company Enrichment API Actor is ready to run with the inputs already set for "Check funding signal and founding year for target accounts". [Sign up or log in](https://console.apify.com/create-task-from-example/eZcBjGe2CjS9xQwoD) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Check funding signal and founding year for target accounts" task

The Firmographics by Domain - Company Enrichment API Actor will start running based on the input automatically. You can also change all the input fields, like company domains (up to 100), minimum lead score (0-100), and more, to match your specific use case.

### 3. Receive the "Check funding signal and founding year for target accounts" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as input domain, company name, company description, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Check funding signal and founding year for target accounts" task via API](https://apify.com/b2bdata/company-firmographics-by-domain.md).

## FAQ

### What does the funding signal task return?

The funding signal task returns founding year, a has-funding flag, last funding round type and date, employee size band, description, headquarters and LinkedIn page for each domain.

### What input does the target account firmographics task need?

This task needs a list of company domains. Output format can be default or compatible. Compatible keeps the standard field names and adds the names common LinkedIn scrapers use.

### How do I schedule the target account lookup or export to Sheets?

Run the target account task through the Apify API, put it on a schedule in Apify Console, or start it by hand. Export the dataset as CSV or JSON and open it in Google Sheets or Excel.

### Can I filter target accounts to young funded companies with this task?

The funding signal task returns founding year and funding fields on every row, so you can export the dataset as CSV or JSON and filter by year or last round type in your spreadsheet or CRM.

## About this Actor

This example demonstrates how to use [Firmographics by Domain - Company Enrichment API](https://apify.com/b2bdata/company-firmographics-by-domain.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/b2bdata/company-firmographics-by-domain.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/b2bdata/company-firmographics-by-domain.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).