# Competitor Watchdog — Intelligence Pipeline (`reflective_plagioclase/competitor-watchdog`) Actor Monitors competitor websites — detects pricing changes, tech stack shifts, content updates, and hiring trends. - **URL**: https://apify.com/reflective\_plagioclase/competitor-watchdog.md - **Developed by:** [Matt](https://apify.com/reflective_plagioclase) (community) - **Categories:** Business, Automation, Marketing - **Stats:** 2 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $900.00 / 1,000 competitor snapshots 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 a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. 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. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use 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 ## Competitor Watchdog — Intelligence Pipeline **Know when your competitors change.** This actor continuously monitors competitor websites and alerts you when it detects changes in pricing, tech stack, content strategy, or hiring patterns. Set it up once on a recurring schedule and get notified when something important changes — no more manual check-ins. ### How It Works Each run profiles your competitors across four dimensions: #### 📄 Homepage Analysis - Title, meta description, H1 tags - **Tech stack detection** — 60+ technologies (React, Shopify, Stripe, Cloudflare, etc.) - Internal vs. external link count - Body text fingerprinting for content change detection #### 💰 Pricing Intelligence - Scrapes the `/pricing` page (or custom URL) - Extracts plan names, prices, and feature lists - Detects: new plans, removed plans, price changes, free tier changes - Flags pricing changes as HIGH / MEDIUM / CRITICAL severity #### 💼 Hiring Signals - Scrapes `/careers` page (or custom URL) - Counts open positions, tracks departments hiring - Detects: headcount increases/decreases, new departments, department closures - Headcount spikes >50% flagged as HIGH severity #### 🏢 Company Changes - Scrapes `/about` and `/team` pages - Tracks employee count - Extracts leadership names - Detects team growth or shrinkage ### Input Parameters | Parameter | Type | Required | Default | Description | |-----------|------|----------|---------|-------------| | `competitors` | array | ✅ | — | List of competitors: `[{name, url, pricingPage?, jobsPage?}]` | | `monitorPricing` | boolean | — | true | Scrape and compare pricing pages | | `monitorJobs` | boolean | — | true | Scrape and compare careers pages | | `monitorContent` | boolean | — | true | Scrape about and team pages | | `maxPagesPerCompetitor` | integer | — | 10 | Limit pages scraped per competitor | ### Output The actor outputs three types of events to the dataset: 1. **`COMPETITOR_SNAPSHOT`** — Full profile of each competitor (homepage, pricing, jobs, about) 2. **`CHANGE_LOG`** — Detected changes with severity levels (CRITICAL / HIGH / MEDIUM / LOW) 3. **`MARKDOWN_REPORT`** — Human-readable summary of the entire run Change log example: ```json { "event": "CHANGE_LOG", "competitor": "Acme Corp", "comparison": { "changes": [ {"type": "PRICING", "change": "PRICE_CHANGE", "severity": "HIGH", "detail": "Price changed for 'Pro Plan': $99/mo → $129/mo"}, {"type": "TECH_STACK", "change": "ADDED", "severity": "HIGH", "detail": "New technology detected: OpenAI"}, {"type": "HIRING", "change": "HEADCOUNT_CHANGE", "severity": "HIGH", "detail": "Open positions increased: 5 → 12"} ], "threats": ["⚠ Competitor adopted OpenAI — may indicate new AI capabilities", "📈 Competitor expanding headcount significantly"] } } ```` ### Use Cases - **Pricing alerts** — Get notified the moment a competitor changes prices - **Tech stack tracking** — See when competitors adopt new tools (especially payment, AI, or CRM platforms) - **Hiring intelligence** — Spot growth signals before they hit the market - **Market positioning** — Track how competitors' messaging evolves over time - **Investment research** — Monitor portfolio companies without quarterly updates ### Pricing Pay-per-event: - **$0.90 per competitor snapshot** — Full profile scrape - Additional charges for change-detected events when comparisons find changes The total per-run cost depends on the number of competitors and pages scraped. A typical run monitoring 5 competitors costs **~$4.50 + change-event charges**. ### Tips - Set up a recurring schedule (daily or weekly) for continuous monitoring - Snapshots are stored in the actor's key-value store — comparisons only work after at least two runs - Use custom pricing and jobs URLs if your competitors use non-standard paths - The first run on each competitor establishes the baseline — no comparison is generated ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("reflective_plagioclase/competitor-watchdog").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("reflective_plagioclase/competitor-watchdog").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 reflective_plagioclase/competitor-watchdog --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=reflective_plagioclase/competitor-watchdog", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Competitor Watchdog — Intelligence Pipeline", "description": "Monitors competitor websites — detects pricing changes, tech stack shifts, content updates, and hiring trends.", "version": "0.1", "x-build-id": "ob2K707GltghZ43Aw" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/reflective_plagioclase~competitor-watchdog/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-reflective_plagioclase-competitor-watchdog", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/reflective_plagioclase~competitor-watchdog/runs": { "post": { "operationId": "runs-sync-reflective_plagioclase-competitor-watchdog", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/reflective_plagioclase~competitor-watchdog/run-sync": { "post": { "operationId": "run-sync-reflective_plagioclase-competitor-watchdog", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": {} }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```