# Prepare CRM contacts for review and reimport

**Use case:** 

Normalize fictional CRM contact fields, surface review-required values and possible matches, then inspect the review Dataset before reimport.

## Input

```json
{
  "source": {
    "type": "dataset",
    "file": "apify://key-value-stores/synthetic-source/records/contacts.csv",
    "datasetId": "synthetic-dataset-name",
    "storeId": "synthetic-source-store",
    "recordKey": "contacts.jsonl",
    "format": "csv",
    "fieldMap": {
      "recordId": "crm_id",
      "url": "website",
      "email": "email_address",
      "address": "mailing_address"
    },
    "offset": 0
  },
  "records": [
    {
      "recordId": "crm-demo-001",
      "url": " demo-alpha.invalid/contact/?utm_source=crm#team ",
      "email": "OWNER@DEMO-ALPHA.INVALID",
      "address": "900 cedar street chicago il 60601"
    },
    {
      "recordId": "crm-demo-002",
      "url": "https://review-example.invalid/profile",
      "email": "needs-human-review",
      "address": "warehouse behind blue door"
    },
    {
      "recordId": "crm-demo-003",
      "url": "https://possible-match.invalid/contact",
      "email": "alpha@possible-match.invalid",
      "address": "123 Fictional Avenue Suite 100, Austin, Texas 78701"
    },
    {
      "recordId": "crm-demo-004",
      "url": "https://possible-match.invalid/contact/?utm_campaign=demo",
      "email": "beta@possible-match.invalid",
      "address": "123 Fictional Avenue Suite 200, Austin, Texas 78701"
    }
  ],
  "previewOnly": true,
  "rowLimitBehavior": "fail_over_limit",
  "workflow": {
    "exportMode": "side_by_side",
    "exportFormat": "csv",
    "generatedFieldNamespace": "contactCleanup"
  },
  "fieldGroups": [
    "url",
    "email",
    "address"
  ],
  "reviewStrictness": "standard",
  "dedupeKeyMode": "keys_and_candidates"
}
```

## Output

```json
{
  "recordId": {
    "label": "Record ID",
    "format": "string"
  },
  "sourceIdentity": {
    "label": "Source identity",
    "format": "object"
  },
  "cleanedSupportedValues": {
    "label": "Cleaned supported values",
    "format": "object"
  },
  "workflow": {
    "label": "Workflow facts",
    "format": "object"
  },
  "possibleMatchGroupReferences": {
    "label": "Possible-match groups",
    "format": "array"
  },
  "originalValues": {
    "label": "Original values",
    "format": "object"
  }
}
```

## About this Actor

This example demonstrates how to use [CRM Contact Cleanup & Dedupe Prep](https://apify.com/critd/contact-cleanup.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/critd/contact-cleanup.md) 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/critd/contact-cleanup.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).