# Kickstarter Chicago Design Funding Benchmark

**Use case:** 

Pull successful Kickstarter Design campaigns based in Chicago with pledge and goal data. Helps founders benchmark realistic funding targets before launch.

## Input

```json
{
  "search_keyword": "product design",
  "location": "Chicago",
  "max_results": 10,
  "state": "successful",
  "category_id": "7",
  "pledged": "",
  "goal": "2",
  "raised": "2",
  "sort": "most_funded"
}
```

## Output

```json
{
  "photo": {
    "label": "Photos",
    "format": "object"
  },
  "name": {
    "label": "Project Name",
    "format": "string"
  },
  "blurb": {
    "label": "Short Description",
    "format": "string"
  },
  "state": {
    "label": "Status",
    "format": "string"
  },
  "goal": {
    "label": "Funding Goal",
    "format": "number"
  },
  "pledged": {
    "label": "Amount Pledged",
    "format": "number"
  },
  "percent_funded": {
    "label": "% Funded",
    "format": "number"
  },
  "backers_count": {
    "label": "Backers",
    "format": "integer"
  },
  "currency": {
    "label": "Currency",
    "format": "string"
  },
  "staff_pick": {
    "label": "Staff Pick",
    "format": "boolean"
  },
  "country": {
    "label": "Country",
    "format": "string"
  },
  "category": {
    "label": "Category",
    "format": "object"
  },
  "creator": {
    "label": "Creator",
    "format": "object"
  },
  "extraction_date": {
    "label": "Extraction Date",
    "format": "string"
  }
}
```

## About this Actor

This example demonstrates how to use [Kickstarter Advanced Scraper](https://apify.com/datacach/kickstarter-advanced-scraper) with a specific input configuration. Visit the [Actor detail page](https://apify.com/datacach/kickstarter-advanced-scraper) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
This Task's input is already configured above — use it as-is rather than inventing a new one.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/datacach/kickstarter-advanced-scraper.md

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).