# Ai Competitor Intelligence (`muhammad-bilal/ai-competitor-intelligence`) Actor

Benchmark a company against its competitors inside AI-generated answers across ChatGPT, Gemini,
Claude, and Perplexity — and learn why competitors win.
For every question, this Actor asks each AI engine and
extracts mentions, position, sentiment, the reason, and citations.

- **URL**: https://apify.com/muhammad-bilal/ai-competitor-intelligence.md
- **Developed by:** [Muhammad Bilal](https://apify.com/muhammad-bilal) (community)
- **Categories:** AI, Agents, Lead generation
- **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.27 / actor start

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

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

## AI Competitor Intelligence

**Benchmark a company against its competitors inside AI-generated answers** across ChatGPT, Gemini,
Claude, and Perplexity — and learn *why* competitors win.

[![Apify SDK](https://img.shields.io/badge/Apify-SDK%20v3-green)](https://sdk.apify.com)
[![Playwright](https://img.shields.io/badge/Playwright-v1-blue)](https://playwright.dev)
[![TypeScript](https://img.shields.io/badge/TypeScript-strict-blue)](https://www.typescriptlang.org)

### Overview

For every question, this Actor asks each AI engine and, for your company and each competitor,
extracts **mentions, position, sentiment, the reason, and citations**. It builds a
**recommendation-frequency** ranking, compares each competitor to you, explains **why competitors
win** (more Reddit mentions, more review sites, more documentation, more backlinks, more
comparisons), and produces **actionable recommendations**.

### Architecture

```
src/
├── main.ts                 # Actor.main() entry point
├── types.ts                # Input/analysis/summary types
├── config/index.ts         # Input validation → strict config (entity universe)
├── analysis/index.ts       # per-entity stats, comparisons, recommendations
├── report/index.ts         # "why competitors win" markdown report
└── shared/                 # Reusable library (adapters, engine, parser, citations, …)
```

Pipeline: **validate → build tasks → collect answers → analyze each entity → compare → recommend**.

### Input

| Field | Type | Default | Description |
|-------|------|---------|-------------|
| `company` | string (required) | — | Your company |
| `competitors` | string\[] (required) | — | Competitors to benchmark against |
| `questions` | string\[] (required) | — | Questions asked on every platform |
| `platforms` | string\[] | all four | `ChatGPT`, `Gemini`, `Claude`, `Perplexity` |
| `headless` | boolean | `true` | Headless browser |
| `screenshotOnFailure` | boolean | `true` | Screenshots to KV store on failure |
| `maxRetries` | integer | `2` | Retries per (platform, question) |
| `askTimeoutMs` | integer | `90000` | Max wait per answer |
| `useApifyProxy` | boolean | `true` | Route through Apify Proxy |
| `cookies` | array | `[]` | Session cookies for authenticated platforms |

#### Input example

```json
{
  "company": "ChatbotsHub",
  "competitors": ["Botpress", "Voiceflow", "Intercom"],
  "questions": ["best chatbot platform for businesses", "best conversational AI tools"]
}
```

### Output

#### Dataset row (one per company/competitor)

```json
{ "company": "ChatbotsHub", "isYourCompany": true, "recommendationRate": 22, "mentionRate": 40, "averagePosition": 3.5, "totalCitations": 2, "redditMentions": 0 }
```

#### Key-Value Store artifacts

- `SUMMARY` — entity stats, competitor comparisons (with advantages), recommendations
- `REPORT` — markdown: recommendation frequency + "why competitors win" + recommendations
- `DETAILS` — per (question, platform, entity) analyses (mention, position, sentiment, reason)
- `EXPORT_CSV` — flat CSV of entity stats

### How "why competitors win" is computed

Each competitor is compared to you across measurable signals; a competitor "wins" a signal when it
scores strictly better:

- ✓ Higher AI recommendation rate
- ✓ Mentioned more frequently / better average position
- ✓ More Reddit / community mentions
- ✓ More review-site, documentation, forum, or blog/comparison citations
- ✓ More backlinks (unique cited URLs) / more total citations

Citations are attributed **per entity** (only citations on the entity's own line/bullet count), so
comparisons reflect each brand's real cited footprint.

### Rate limits & known limitations

- Auth walls (ChatGPT/Claude/Gemini) → supply `cookies`. Perplexity usually works anonymously.
- Position/sentiment are heuristic (structure + lexicon), keeping runs deterministic and cheap.
- Signals depend on the engines surfacing citations for a given answer.

### Deployment

```bash
npm install && npm run build && npm test && npm run lint
npx playwright install chromium   # local only; Docker image already has it
apify push
```

Docker base image: `apify/actor-node-playwright-chrome:22`.

### Testing guide

`npm test` runs parser/citation (fixture-based), retry, validation, statistics, adapter (mock page),
engine integration, and competitor-analysis tests. Fixtures live in `tests/fixtures/`.

### Troubleshooting

| Symptom | Cause | Fix |
|---------|-------|-----|
| All entities 0% | Auth wall / no answers | Provide `cookies`, enable proxy |
| Missing citation signals | Engine returned no links | Prefer Perplexity; retry |

### Version history

- **1.0.0** — Initial production release.

# Actor input Schema

## `company` (type: `string`):

The company you want to benchmark against its competitors.

## `competitors` (type: `array`):

Competitor companies to compare against.

## `questions` (type: `array`):

Questions asked on every platform to evaluate recommendations.

## `platforms` (type: `array`):

Which AI answer engines to query. Leave empty to query all four.

## `headless` (type: `boolean`):

Run the browser in headless mode.

## `screenshotOnFailure` (type: `boolean`):

Capture a screenshot to the Key-Value Store when an answer cannot be obtained.

## `maxRetries` (type: `integer`):

Number of retry attempts per (platform, question) on transient failures.

## `askTimeoutMs` (type: `integer`):

Maximum time to wait for a single answer to complete.

## `useApifyProxy` (type: `boolean`):

Route browser traffic through Apify Proxy (residential group preferred).

## `cookies` (type: `array`):

Optional cookies to authenticate platforms that require login.

## `mockMode` (type: `boolean`):

Run fully offline with deterministic synthetic answers (no browser, no auth).

## Actor input object example

```json
{
  "company": "ChatbotsHub",
  "competitors": [
    "Botpress",
    "Voiceflow",
    "Intercom"
  ],
  "questions": [
    "best chatbot platform for businesses",
    "best conversational AI tools",
    "top customer support chatbots"
  ],
  "platforms": [
    "ChatGPT",
    "Gemini",
    "Claude",
    "Perplexity"
  ],
  "headless": true,
  "screenshotOnFailure": true,
  "maxRetries": 2,
  "askTimeoutMs": 90000,
  "useApifyProxy": true,
  "cookies": [],
  "mockMode": false
}
```

# Actor output Schema

## `results` (type: `string`):

Dataset with one row per company/competitor.

## `summary` (type: `string`):

Comparisons and recommendations.

## `report` (type: `string`):

Why competitors win + actionable recommendations.

## `details` (type: `string`):

Per (question, platform, entity) analysis.

# 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 = {
    "competitors": [
        "Botpress",
        "Voiceflow",
        "Intercom"
    ],
    "questions": [
        "best chatbot platform for businesses",
        "best conversational AI tools",
        "top customer support chatbots"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("muhammad-bilal/ai-competitor-intelligence").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 = {
    "competitors": [
        "Botpress",
        "Voiceflow",
        "Intercom",
    ],
    "questions": [
        "best chatbot platform for businesses",
        "best conversational AI tools",
        "top customer support chatbots",
    ],
}

# Run the Actor and wait for it to finish
run = client.actor("muhammad-bilal/ai-competitor-intelligence").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 '{
  "competitors": [
    "Botpress",
    "Voiceflow",
    "Intercom"
  ],
  "questions": [
    "best chatbot platform for businesses",
    "best conversational AI tools",
    "top customer support chatbots"
  ]
}' |
apify call muhammad-bilal/ai-competitor-intelligence --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "command": "npx",
            "args": [
                "mcp-remote",
                "https://mcp.apify.com/?tools=muhammad-bilal/ai-competitor-intelligence",
                "--header",
                "Authorization: Bearer <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/m8vwCKfdLLwq7zDVa/builds/albLBZZ6DHC9uO2yc/openapi.json