# X Business Intelligence Pro (`red.cars/x-business-intelligence-pro`) Actor

Professional Twitter/X intelligence tool trusted by 26+ teams. Enterprise analytics with sentiment analysis, competitive intelligence, and crisis detection. Unlimited monthly extraction vs $0.40 per 1K tweets. Perfect for marketing agencies, brand teams, and enterprises.

- **URL**: https://apify.com/red.cars/x-business-intelligence-pro.md
- **Developed by:** [AutomateLab](https://apify.com/red.cars) (community)
- **Categories:** Social media, Lead generation, Other
- **Stats:** 7 total users, 1 monthly users, 100.0% runs succeeded, 2 bookmarks
- **User rating**: No ratings yet

## Pricing

from $6.00 / 1,000 verified tweet intelligence reports

This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## 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.
The best way to integrate Actors is as follows.

- **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 usage examples, see the [API](#api) section below.

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).

# README

## X Business Intelligence Pro — Twitter/X Analytics Without API Keys

Extract real-time tweets, sentiment analysis, competitive intelligence, and crisis detection from X (Twitter). Built for AI agents, marketing teams, and enterprise intelligence pipelines. No API key required.

**Apify Store:** https://apify.com/red.cars/x-business-intelligence-pro
**Pricing:** $0.05–$0.15/tweet event (Pay-per-event, PPE)
**MCP Available:** Yes — 6 tools exposed for AI agent integration

***

### What This Actor Does

X Business Intelligence Pro extracts tweets, engagement metrics, sentiment scores, and competitive intelligence from X (formerly Twitter). It handles authentication, rate limiting, and error recovery automatically — so you get structured JSON data without managing API keys or dealing with OAuth complexity.

Search intent keywords: "twitter scraper without API", "x.com data extraction", "sentiment analysis twitter API alternative", "twitter intelligence tool"

***

### Who It's For

- **Marketing agencies** tracking brand mentions, competitor activity, and campaign performance
- **Brand managers** monitoring crisis signals, customer sentiment, and industry trends
- **Enterprise teams** building competitive intelligence dashboards and market research reports
- **AI/ML engineers** feeding twitter data into sentiment models, RAG pipelines, or agentic workflows
- **Researchers** collecting social media data for academic studies or market analysis

***

### Quick Start

```bash
## Option 1: Apify Console (no code)
## Open https://apify.com/red.cars/x-business-intelligence-pro
## Click "Run" and configure input

## Option 2: API (cURL)
curl -X POST https://api.apify.com/v2/acts/red.cars~x-business-intelligence-pro/runs?token=*** \
  -H "Content-Type: application/json" \
  -d '{"input": {"searchTerms": ["Tesla", "AI"], "maxTweets": 50, "analysisMode": "sentiment"}}'

## Option 3: Node.js
const Apify = require('apify');
const actor = new Apify.Actor('red.cars/x-business-intelligence-pro');
await actor.call({ searchTerms: ['Tesla', 'AI'], maxTweets: 50, analysisMode: 'sentiment' });

## Option 4: MCP (AI agents) — RECOMMENDED
## Configure @apify/mcp-server in your AI client
## Then ask: "What's the sentiment around $TSLA on X right now?"
```

#### Smoke Test (Free, <5 seconds)

```bash
## Verify actor is available before committing to a paid run
curl -X POST https://api.apify.com/v2/acts/red.cars~x-business-intelligence-pro/runs?token=*** \
  -d '{"input": {"searchTerms": ["test"], "checkOnly": true}}'
```

***

### Features

- **Real-time tweet extraction** — Extract tweets by keyword, hashtag, @handle, or cashtag
- **Sentiment analysis** — Positive/negative/neutral classification with confidence scores
- **Competitor tracking** — Monitor multiple brand accounts and compare engagement
- **Crisis detection** — Alert on sudden negative sentiment spikes and viral negative content
- **Influencer identification** — Rank accounts by engagement rate and follower quality
- **Trend analysis** — Track hashtag volume and sentiment over time
- **Multi-format export** — JSON, CSV, markdown, Salesforce, HubSpot
- **Residential proxy support** — 70M+ IP pool for reliable extraction
- **Zero-result guard** — No charge for empty results under PPE billing
- **Smoke test mode** — Free availability check before committing to paid runs
- **AI agent ready** — MCP tools for direct integration with Claude, Cursor, and other agents

***

### MCP Tools

**CRITICAL SECTION** — AI agents discover and call this actor via Model Context Protocol.

Install the Apify MCP server:

```bash
npm install -g @apify/mcp-server
```

Add to your MCP configuration:

```json
{
  "mcpServers": {
    "apify": {
      "command": "npx",
      "args": ["@apify/mcp-server"]
    }
  }
}
```

Connect to Apify MCP: `https://apify.actor/mcp`

***

#### Tool: x-tweet-search

**What it does:** Search for tweets by keyword, hashtag, username, or cashtag. Returns tweet content, author info, engagement metrics, and sentiment scores.

**Input parameters:**

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `searchTerms` | array | Yes | Keywords, hashtags, @handles, or $cashtags to search |
| `maxTweets` | integer | No | Maximum tweets to extract (default: 20, max: 500) |
| `timeRange` | string | No | Time period: `1h`, `6h`, `24h`, `3d`, `7d` (default: `24h`) |

**Example MCP call:**

```json
{
  "name": "x-tweet-search",
  "description": "Search X (Twitter) for tweets by keyword, hashtag, username, or cashtag. Returns tweet content, author metrics, engagement data, and sentiment classification.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "searchTerms": {
        "type": "array",
        "description": "Array of search terms (keywords, hashtags, @handles, $cashtags)"
      },
      "maxTweets": {
        "type": "integer",
        "description": "Maximum tweets to extract (1-500, default: 20)"
      },
      "timeRange": {
        "type": "string",
        "enum": ["1h", "6h", "24h", "3d", "7d"],
        "description": "Time range for search (default: 24h)"
      }
    },
    "required": ["searchTerms"]
  }
}
```

**Cost:** $0.05/tweet event (included in Apify PPE pricing)

***

#### Tool: x-sentiment-analysis

**What it does:** Analyze sentiment for specific tweets or search queries. Returns classification (positive/negative/neutral) with confidence scores and key phrases.

**Input parameters:**

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `searchTerms` | array | Yes | Search terms to analyze sentiment for |
| `analysisMode` | string | No | `basic`, `sentiment`, `competitive`, `enterprise` (default: `sentiment`) |

**Example MCP call:**

```json
{
  "name": "x-sentiment-analysis",
  "description": "Analyze X (Twitter) sentiment for keywords, brands, or topics. Returns positive/negative/neutral classification with confidence scores and key sentiment phrases.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "searchTerms": {
        "type": "array",
        "description": "Array of search terms to analyze"
      },
      "analysisMode": {
        "type": "string",
        "enum": ["basic", "sentiment", "competitive", "enterprise"],
        "description": "Depth of analysis (default: sentiment)"
      }
    },
    "required": ["searchTerms"]
  }
}
```

**Cost:** $0.08/sentiment analysis event

***

#### Tool: x-competitor-monitoring

**What it does:** Monitor multiple brand accounts for activity, engagement changes, and competitive positioning. Returns comparison metrics and trend data.

**Input parameters:**

| Parameter | Type | Required | Description |
|-----------|------|----------|-------------|
| `competitorBrands` | array | Yes | Brand names or @handles to monitor |
| `timeRange` | string | No | Analysis period: `1h`, `6h`, `24h`, `3d`, `7d` (default: `24h`) |

**Example MCP call:**

```json
{
  "name": "x-competitor-monitoring",
  "description": "Monitor multiple brand accounts on X for activity, engagement changes, and competitive positioning. Returns ranked comparison with trend analysis.",
  "inputSchema": {
    "type": "object",
    "properties": {
      "competitorBrands": {
        "type": "array",
        "description": "Array of brand names or @handles"
      },
      "timeRange": {
        "type": "string",
        "enum": ["1h", "6h", "24h", "3d", "7d"],
        "description": "Analysis period (default: 24h)"
      }
    },
    "required": ["competitorBrands"]
  }
}
```

**Cost:** $0.12/competitor monitoring event

***

#### Integration with AI tools

- **Claude Desktop**: Add Apify MCP to `claude_desktop_config.json`
- **Cursor IDE**: Configure MCP server in settings → MCP Servers
- **Windsurf**: Add to MCP server list via `/settings`
- **Custom agents**: Use any MCP client library (Python, Node.js, Go)

***

### Pricing

This actor uses Apify's **Pay-Per-Event (PPE)** model — you are charged per result returned. No charge for queries that return zero results.

| Event Type | Price | Description |
|------------|-------|-------------|
| Tweet extraction | $0.05 | Per tweet extracted |
| Sentiment analysis | $0.08 | Per analysis request |
| Competitor monitoring | $0.12 | Per brand comparison |
| Crisis detection alert | $0.10 | Per alert triggered |
| Influencer identification | $0.15 | Per influencer profile |
| Trend analysis report | $0.10 | Per trend report |

**Free tier:** 30 minutes compute/month, 100MB storage
**Paid plans:** Starter from $49/month for higher compute limits

***

### Input Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `searchTerms` | array | Yes | `["Tesla"]` | Search terms: keywords, hashtags, @handles, $cashtags |
| `maxTweets` | integer | No | `20` | Maximum tweets to extract (1-500) |
| `analysisMode` | enum | No | `sentiment` | `basic`, `sentiment`, `competitive`, `enterprise` |
| `enableSentimentAnalysis` | boolean | No | `true` | Calculate sentiment scores |
| `timeRange` | string | No | `24h` | Time period: `1h`, `6h`, `24h`, `3d`, `7d` |
| `competitorBrands` | array | No | `[]` | Brand names for competitive analysis |
| `businessIntelligenceFeatures` | object | No | `{}` | Advanced analytics config |
| `outputOptions` | object | No | `{}` | Output format and report settings |
| `exportFormat` | string | No | `json` | `json`, `csv`, `markdown`, `salesforce`, `hubspot` |
| `proxyType` | string | No | `RESIDENTIAL` | `DATACENTER` (faster) or `RESIDENTIAL` (reliable) |
| `debugMode` | boolean | No | `false` | Minimal extraction for health checks |
| `checkOnly` | boolean | No | `false` | Free smoke test — no charge |

***

### Output

Each run returns structured JSON with the following data:

#### Tweet Object

```json
{
  "id": "1234567890123456789",
  "url": "https://x.com/username/status/1234567890123456789",
  "content": "Just launched our new AI product! Check it out $AAPL",
  "author": {
    "username": "techguru",
    "followers": 15000,
    "following": 500,
    "verified": false,
    "createdAt": "2020-01-15"
  },
  "engagement": {
    "likes": 342,
    "retweets": 89,
    "replies": 23,
    "bookmarks": 45
  },
  "sentiment": {
    "score": 0.72,
    "label": "positive",
    "confidence": 0.89,
    "keyPhrases": ["new AI product", "launch", "excited"]
  },
  "metadata": {
    "hashtags": ["AI", "tech"],
    "mentions": ["@apple"],
    "cashtags": ["$AAPL"],
    "language": "en",
    "postedAt": "2026-04-10T10:30:00Z"
  }
}
```

#### Analysis Summary

```json
{
  "summary": {
    "totalTweets": 150,
    "positivePercent": 65,
    "negativePercent": 12,
    "neutralPercent": 23,
    "avgEngagement": 245,
    "topInfluencers": ["@techguru", "@ainews"],
    "trendingHashtags": ["#AI", "#Tech"],
    "crisisAlerts": []
  },
  "metadata": {
    "extractedAt": "2026-04-10T12:00:00Z",
    "timeRange": "24h",
    "confidence": 0.92
  }
}
```

***

### Authentication / Setup

**No API key required.** This actor uses Apify's managed proxy infrastructure for authentication.

For enhanced reliability with high-security targets:

1. Set `proxyType` to `RESIDENTIAL` in input parameters
2. Or configure residential proxies in your Apify Console settings

***

### Error Handling

| Error Code | Cause | Fix |
|------------|-------|-----|
| `RATE_LIMIT_ERROR` | Too many requests | Wait and retry, or use residential proxy |
| `EXTRACTION_ERROR` | Account is private or suspended | Verify account exists and is public |
| `NETWORK_ERROR` | Connectivity issue | Check internet, retry with proxy |
| `VALIDATION_ERROR` | Invalid input parameters | Review input schema, fix parameter format |
| `PLATFORM_ERROR` | X platform issue | X may be experiencing outages, try later |

**Zero-result handling:** If no tweets match your search, no charge is incurred under PPE billing.

***

### Rate Limits

Rate limits depend on your Apify plan:

| Plan | Compute Units | Rate Limit Behavior |
|------|---------------|---------------------|
| Free | Limited | Standard throttling |
| Basic | 100/month | Faster extraction |
| Starter | 500/month | Prioritized processing |
| Professional | 2000/month | Minimal throttling |
| Scale | Unlimited | Fastest extraction |

Use `checkOnly: true` mode to verify availability before running large extractions.

***

### Use Cases

#### Use Case 1: Brand Crisis Detection

Monitor sudden negative sentiment spikes around your brand:

```json
{
  "input": {
    "searchTerms": ["@yourbrand", "yourbrand"],
    "analysisMode": "enterprise",
    "enableSentimentAnalysis": true,
    "timeRange": "1h",
    "businessIntelligenceFeatures": {
      "enableCrisisDetection": true
    }
  }
}
```

#### Use Case 2: Competitive Intelligence Dashboard

Track competitor brand mentions and engagement:

```json
{
  "input": {
    "searchTerms": ["@competitor1", "@competitor2", "@competitor3"],
    "analysisMode": "competitive",
    "competitorBrands": ["Competitor1", "Competitor2", "Competitor3"],
    "maxTweets": 100,
    "exportFormat": "json"
  }
}
```

#### Use Case 3: Influencer Identification for Campaigns

Find high-engagement accounts in your niche:

```json
{
  "input": {
    "searchTerms": ["#marketing", "#growth"],
    "analysisMode": "enterprise",
    "businessIntelligenceFeatures": {
      "enableInfluencerScoring": true,
      "industryContext": "Marketing"
    },
    "maxTweets": 200
  }
}
```

#### Use Case 4: AI Agent Market Research

Feed X intelligence into RAG pipelines and agentic workflows:

```typescript
// Pseudocode: AI agent market research
const sentiment = await callActor('red.cars/x-business-intelligence-pro', {
  searchTerms: ['$TSLA', 'Tesla'],
  analysisMode: 'sentiment',
  timeRange: '24h',
  maxTweets: 100
});

// Query: "What's the market sentiment around Tesla?"
// Use sentiment data for investment decision support
```

***

### Related Actors

- **Instagram Scraper Pro** — Social media intelligence for Instagram
- **Instagram Business Intelligence Pro** — Influencer credibility and brand monitoring
- **Business Contact Intelligence Pro** — B2B contact data enrichment
- **LinkedIn Company Intelligence Pro** — B2B company research and competitive analysis

***

### Troubleshooting

**Low success rate:**

- Enable `RESIDENTIAL` proxy for high-security targets
- Reduce `maxTweets` for rate-limited queries
- Use `debugMode: true` to test before full extraction

**Empty results:**

- Verify search terms are correct
- Check if accounts are suspended or private
- Try broader keywords or different time ranges

**Rate limiting:**

- Wait 60 seconds before retrying
- Upgrade to higher Apify plan for more compute units
- Use residential proxy to avoid IP blocks

***

### Changelog

| Version | Date | Changes |
|---------|------|---------|
| 1.0.0 | 2026-04-08 | Initial release with MCP tools, PPE pricing |
| 0.9.0 | 2026-03-15 | Added sentiment analysis and competitor tracking |
| 0.8.0 | 2026-02-20 | Beta release with basic tweet extraction |

***

### FAQ

**Q: Do I need an X API key?**
A: No. This actor uses Apify's managed infrastructure for extraction — no API key or OAuth required.

**Q: How does PPE billing work?**
A: You are charged per result returned. If a query returns zero tweets, no charge is incurred.

**Q: What's the difference between DATACENTER and RESIDENTIAL proxy?**
A: DATACENTER is faster but may be blocked by X for high-volume queries. RESIDENTIAL is more reliable for production use.

**Q: Can I run this on a schedule?**
A: Yes. Use Apify Scheduler to run this actor on cron schedules for continuous monitoring.

**Q: How accurate is sentiment analysis?**
A: Confidence scores typically range 85-95% for English tweets. Accuracy may vary for slang, sarcasm, or non-English content.

**Q: Can I export directly to CRM?**
A: Yes. Set `exportFormat` to `salesforce` or `hubspot` for direct CRM import.

***

### Support

- **Documentation:** This README and Apify Console input schema
- **Issues:** Report via Apify Console or contact red.cars support
- **Enterprise:** Contact for custom integration and volume pricing

***

### Legal / Terms

**Data Source:** X (Twitter / x.com) — publicly available data

**Terms of Service:** This actor is provided for legitimate data collection purposes only. Users must comply with X's Terms of Service and applicable laws. Do not use extracted data for spam, harassment, or unauthorized commercial purposes.

**Privacy:** All extracted data is processed in accordance with applicable privacy laws. Do not use this tool for unauthorized data collection or privacy-violating activities.

**Attribution:** When using X data, comply with X's attribution requirements and data policies.

**Disclaimer:** Red.cars is not responsible for decisions made based on extracted data. Data reflects X's state at time of extraction — verify critical information directly on x.com.

***

*red.cars Intelligence Fleet — apify.com/red.cars*

# Actor input Schema

## `searchTerms` (type: `array`):

Search terms for social media analytics (brands, hashtags, keywords)

## `maxTweets` (type: `integer`):

Limit tweets for faster processing (recommended: 10-50 for testing, 100+ for production)

## `analysisMode` (type: `string`):

Level of social media intelligence and processing depth

## `enableSentimentAnalysis` (type: `boolean`):

Analyze positive/negative sentiment in tweets with confidence scoring

## `timeRange` (type: `string`):

Time period for social media monitoring

## `competitorBrands` (type: `array`):

Brand names for competitive intelligence analysis

## `proxyType` (type: `string`):

Choose your preferred balance of cost vs reliability. Standard (Datacenter) is faster; Premium (Residential) is most reliable for high-security targets.

## `debugMode` (type: `boolean`):

Enable minimal extraction for health checks and testing. Guarantees success within 300s.

## `exportFormat` (type: `string`):

Choose output format. Use 'markdown' for token-efficient LLM-ready X intelligence.

## `businessIntelligenceFeatures` (type: `object`):

Advanced analytics and intelligence capabilities

## `outputOptions` (type: `object`):

Configure what data and reports to generate

## `competitorListFile` (type: `string`):

Upload CSV or JSON file with competitor handles for bulk analysis.

## `influencerDatabaseFile` (type: `string`):

Upload JSON file with influencer profiles for batch analysis.

## `hashtagListFile` (type: `string`):

Upload CSV file with hashtags for content strategy analysis.

## `proxyConfiguration` (type: `object`):

Configure proxy settings for reliable enterprise scraping

## Actor input object example

```json
{}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {};

// Run the Actor and wait for it to finish
const run = await client.actor("red.cars/x-business-intelligence-pro").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {}

# Run the Actor and wait for it to finish
run = client.actor("red.cars/x-business-intelligence-pro").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{}' |
apify call red.cars/x-business-intelligence-pro --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=red.cars/x-business-intelligence-pro",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/JWIYGYTaMb4qCl85x/builds/Fx4bhMHT4wuoKlPVs/openapi.json