# Capterra Product Reviews — Reviews by Product ID (`v0iddo/capterra-product-reviews`) Actor Pull Capterra.com product reviews via the public reviews page. One row per review with title, body, rating, reviewer name + role + industry, posted date, pros, cons. Specify maxReviewsPerProduct. - **URL**: https://apify.com/v0iddo/capterra-product-reviews.md - **Developed by:** [vøiddo](https://apify.com/v0iddo) (community) - **Categories:** Business - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Capterra Product Reviews Scraper — Reviews by Slug Pull Capterra.com product reviews via the public reviews page. One row per review — title, body, rating, reviewer name + role + industry, posted date, pros, cons. Specify product slugs + per-product cap. ### How to use Pass one or more Capterra product paths in the form `productId/slug`. Find these in the Capterra URL: `capterra.com/p/135003/Slack/reviews/` → path is `135003/Slack`. **Input shape** ```json { "products": [ "135003/Slack", "164800/Notion", "188405/Figma" ], "maxReviewsPerProduct": 50 } ```` | Field | Type | Default | Description | |---|---|---|---| | `products` | `string[]` | Slack / Notion / Figma | Capterra product paths in form `productId/slug` | | `maxReviewsPerProduct` | `integer` | `50` | Cap reviews collected per product (max 5 pages × ~10 reviews) | **Example output row** ```json { "reviewId": "12345678", "product": "135003/Slack", "title": "Best team communication tool out there", "body": "We've been using Slack for 3 years across 4 departments...", "rating": 4.5, "reviewerName": "Jane D.", "reviewerRole": "Product Manager", "reviewerIndustry": "Computer Software", "postedAt": "2024-11-15", "pros": "Integrations, search, channels keep conversations organized", "cons": "Gets expensive at scale; notification overload without discipline" } ``` ### Pricing **Event:** `review_extracted` — $0.0003 per review One charge per review row emitted to the dataset. A 50-review run across 10 products (500 reviews) costs **$0.15**. ### Buyer - Competitor intelligence and win/loss analysis across SaaS categories - Monitoring your own product's review sentiment over time - Sales enablement: surfacing competitor weaknesses by reviewing cons at scale - Market research: aggregating reviewer roles and industries to identify target segments - Benchmarking rating trends across competing products ### Source Capterra serves React / Next.js pages — review content is embedded in the `__NEXT_DATA__` JSON blob within each product review page: ``` https://www.capterra.com/p/{productId}/{slug}/reviews/?page=N ``` Pages are scraped with a real Chrome User-Agent and `Accept-Language: en-US`. Pagination stops when the reviews array is empty or after 5 pages. If a product slug returns 404, it is logged and skipped without failing the run. # Actor input Schema ## `products` (type: `array`): Capterra product paths in form productId/slug ## `maxReviewsPerProduct` (type: `integer`): Cap reviews per product ## Actor input object example ```json { "products": [ "135003/Slack", "164800/Notion", "188405/Figma" ], "maxReviewsPerProduct": 50 } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = { "products": [ "135003/Slack", "164800/Notion", "188405/Figma" ] }; // Run the Actor and wait for it to finish const run = await client.actor("v0iddo/capterra-product-reviews").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${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 = { "products": [ "135003/Slack", "164800/Notion", "188405/Figma", ] } # Run the Actor and wait for it to finish run = client.actor("v0iddo/capterra-product-reviews").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 '{ "products": [ "135003/Slack", "164800/Notion", "188405/Figma" ] }' | apify call v0iddo/capterra-product-reviews --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=v0iddo/capterra-product-reviews", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Capterra Product Reviews — Reviews by Product ID", "description": "Pull Capterra.com product reviews via the public reviews page. One row per review with title, body, rating, reviewer name + role + industry, posted date, pros, cons. Specify maxReviewsPerProduct.", "version": "0.1", "x-build-id": "bJBa02mr2vhp89hE5" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/v0iddo~capterra-product-reviews/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-v0iddo-capterra-product-reviews", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/v0iddo~capterra-product-reviews/runs": { "post": { "operationId": "runs-sync-v0iddo-capterra-product-reviews", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/v0iddo~capterra-product-reviews/run-sync": { "post": { "operationId": "run-sync-v0iddo-capterra-product-reviews", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "products": { "title": "products", "type": "array", "description": "Capterra product paths in form productId/slug", "default": [], "items": { "type": "string" } }, "maxReviewsPerProduct": { "title": "maxReviewsPerProduct", "type": "integer", "description": "Cap reviews per product", "default": 50 } } }, "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 } } } } } } } } } } ```