# Moengage Search Spider (`getdataforme/moengage-search-spider`) Actor The Moengage Search Spider scrapes and aggregates data from Moengage's customer engagement ecosystem, delivering structured insights for market analysis and competitive intelligence.... - **URL**: https://apify.com/getdataforme/moengage-search-spider.md - **Developed by:** [GetDataForMe](https://apify.com/getdataforme) (community) - **Categories:** AI, Automation, E-commerce - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $9.00 / 1,000 results 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 --- ## Moengage Search Spider The Moengage Search Spider is an Apify Actor engineered to scrape and aggregate data from Moengage's ecosystem, focusing on customer engagement platforms, retention tools, and related services. It delivers structured insights into product offerings, enabling users to perform in-depth market analysis and competitive intelligence. Ideal for businesses, researchers, and analysts seeking actionable data on customer data platforms without manual effort. ### Features - **Comprehensive Data Extraction**: Scrapes detailed information on Moengage products, including categories, titles, and descriptive briefs for thorough analysis. - **High Reliability**: Ensures consistent data quality with robust error handling and retry mechanisms for uninterrupted scraping. - **Performance Optimized**: Leverages Apify's infrastructure for fast, scalable data collection, handling large volumes efficiently. - **Customizable Inputs**: Allows flexible configuration to target specific customer-related searches or filters. - **Structured Outputs**: Provides clean JSON-formatted results, ready for integration into dashboards, reports, or databases. - **Seamless Integration**: Works effortlessly within the Apify platform, supporting exports to CSV, Excel, or APIs. - **Unique Value**: Focuses exclusively on Moengage's domain, offering niche insights not available from general web scrapers. ### Input Parameters | Parameter | Type | Required | Description | Example | |-----------|------|----------|-------------|---------| | Customer | string | No | Specifies the customer identifier for the spider, allowing targeted data retrieval based on user-defined criteria. | "customer" | ### Example Usage #### Input Configuration ```json { "Customer": "example_customer" } ```` #### Output Example ```json [ { "CATEGORY": "WEBSITE", "TITLE": "Customer data platform", "BRIEF": "Elevate Your Consumer Engagement Journey: Boost Conversions by 60% and Increase Customer Retention by 50% with Actionable Insights and Rich Data!", "actor_id": "sLybScp0FLkdtd6Os", "run_id": "IxL6HXv3LGgCaYCu8" }, { "CATEGORY": "WEBSITE", "TITLE": "Customer Retention Platform", "BRIEF": "MoEngage is a customer retention platform that enables brands to get churning customers back with insights-led analytics and engagement.", "actor_id": "sLybScp0FLkdtd6Os", "run_id": "IxL6HXv3LGgCaYCu8" }, { "CATEGORY": "WEBSITE", "TITLE": "Customer Engagement Platform", "BRIEF": "Our customer engagement platform personalizes experiences in real-time, driving higher conversions, engagement & retention to drive upto 40% higher conversions.", "actor_id": "sLybScp0FLkdtd6Os", "run_id": "IxL6HXv3LGgCaYCu8" } ] ``` ### Use Cases - **Market Research and Analysis**: Gather insights on customer engagement trends to inform product development and strategy. - **Competitive Intelligence**: Monitor Moengage's offerings to benchmark against competitors in the retention and engagement space. - **Price Monitoring**: Track service descriptions and features for pricing comparisons and market positioning. - **Content Aggregation**: Collect briefs and titles for creating comprehensive reports or knowledge bases on customer platforms. - **Academic Research**: Support studies on digital marketing tools by providing structured data on engagement technologies. - **Business Automation**: Automate data feeds for CRM systems or analytics tools to streamline decision-making processes. ### Installation and Usage 1. Search for "Moengage Search Spider" in the Apify Store 2. Click "Try for free" or "Run" 3. Configure input parameters 4. Click "Start" to begin extraction 5. Monitor progress in the log 6. Export results in your preferred format (JSON, CSV, Excel) ### Output Format The actor outputs data as a JSON array of objects, each representing a scraped item. Key fields include: - **CATEGORY**: The classification of the item (e.g., "WEBSITE"). - **TITLE**: The title of the product or service. - **BRIEF**: A short description or summary of the item. - **actor\_id**: The unique identifier for the Apify actor run. - **run\_id**: The specific run identifier for traceability. This structured format ensures easy parsing and integration into downstream applications. ### Support For custom/simplified outputs or bug reports, please contact: - Email: support@getdataforme.com - Subject line: "custom support" - Contact form: https://getdataforme.com/contact/ We're here to help you get the most out of this Actor! *** # Actor input Schema ## `Customer` (type: `string`): The customer for the spider. ## Actor input object example ```json { "Customer": "customer" } ``` # Actor output Schema ## `results` (type: `string`): Scraped data items from dataset # 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("getdataforme/moengage-search-spider").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("getdataforme/moengage-search-spider").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 getdataforme/moengage-search-spider --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=getdataforme/moengage-search-spider", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Moengage Search Spider", "description": "The Moengage Search Spider scrapes and aggregates data from Moengage's customer engagement ecosystem, delivering structured insights for market analysis and competitive intelligence....", "version": "0.0", "x-build-id": "yQfhpNdv3IY8IgrYX" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/getdataforme~moengage-search-spider/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-getdataforme-moengage-search-spider", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/getdataforme~moengage-search-spider/runs": { "post": { "operationId": "runs-sync-getdataforme-moengage-search-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/getdataforme~moengage-search-spider/run-sync": { "post": { "operationId": "run-sync-getdataforme-moengage-search-spider", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "Customer": { "title": "Customer", "type": "string", "description": "The customer for the spider.", "default": "customer" } } }, "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 } } } } } } } } } } ```