# RepVue Scraper - Sales Rep Employer Reviews, OTE & Quota Data (`jungle_synthesizer/repvue-employer-scraper`) Actor Scrape RepVue.com for B2B SaaS sales compensation and employer review data. Extract company profiles with OTE, base salary, commission structure, quota attainment, ramp time, and employer ratings across ~5K companies. - **URL**: https://apify.com/jungle\_synthesizer/repvue-employer-scraper.md - **Developed by:** [BowTiedRaccoon](https://apify.com/jungle_synthesizer) (community) - **Categories:** Lead generation, Business, Other - **Stats:** 3 total users, 2 monthly users, 100.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per event This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 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 ## RepVue Scraper - Sales Rep Employer Reviews, OTE & Quota Data Scrape RepVue.com for verified B2B SaaS sales compensation and employer review data. Extract company profiles with OTE, base salary, quota attainment, and employer ratings across 5,000+ companies. Get per-role salary breakdowns and anonymous sales rep reviews without an account. ### What You Get Each run returns structured records covering: **Company data** — RepVue score (0–100), total review count, industry, employee count, company description, and direct link to the RepVue profile. **Salary data (per role)** — Median and average OTE, base compensation, average quota attainment, and 75th percentile OTE for roles like Account Executive, SDR, BDR, and Account Manager. **Review data** — Individual sales rep reviews including rating, role, date, pros/cons text, quota attainment percentage, and current/former employee status. ### Use Cases - **Sales compensation benchmarking** — Compare OTE and base salaries across companies and roles in B2B SaaS, FinTech, HR Tech, and adjacent verticals. - **Employer research** — Evaluate culture, leadership, product-market fit, and inbound lead flow before joining a company. - **Talent intelligence** — Track which companies sales reps rate highest and monitor trend changes over time. - **Market analysis** — Aggregate compensation data across an industry segment or company size band. ### Inputs | Field | Type | Description | |---|---|---| | `mode` | select | `companies` (profiles + salaries), `reviews`, or `both` | | `companySlugs` | array | Specific RepVue slugs to scrape (e.g. `salesforce`, `hubspot`). Overrides catalog mode. | | `industry` | select | Filter by industry (B2B SaaS, FinTech, HR Tech, etc.) | | `companySize` | select | Filter by employee count range | | `minRating` | integer | Minimum RepVue score (0–100) | | `maxItems` | integer | Maximum records to return (0 = unlimited) | #### Example Input ```json { "mode": "both", "companySlugs": ["salesforce", "hubspot", "mondaycom"], "maxItems": 100 } ```` ### Output Schema #### Company / Salary record ```json { "company_name": "monday.com", "company_slug": "mondaycom", "company_url": "https://monday.com", "repvue_url": "https://www.repvue.com/companies/mondaycom", "industry": "Project Management", "employee_count": "1001-5000", "overall_rating": 83.02, "total_reviews": 477, "avg_ote": 157000, "avg_base_salary": 95000, "review_role": "Account Executive", "review_date": "2024-03-15T00:00:00.000Z", "review_rating": 4.2, "review_pros": "Great product, strong brand recognition in the market.", "review_quota_attainment": "60-80%", "review_is_current_employee": true } ``` ### How It Works RepVue uses Next.js App Router with React Server Components. Data is embedded in streaming RSC payloads (`self.__next_f.push(...)` script blocks) rather than standard `__NEXT_DATA__` — the scraper concatenates all RSC blocks and extracts structured data objects from the resulting payload. The crawler operates in three levels: 1. **Company listing** — `/companies/page/N` (306 pages, ~10–20 companies each) 2. **Company profile + salaries** — `/companies/` and `/companies//salaries` 3. **Reviews** — `/companies//reviews?page=N` (50 reviews per page) Use `companySlugs` to target specific companies directly and skip the listing crawl. ### Limits and Notes - All data is public — no RepVue account required. - Rate limiting is handled automatically with exponential back-off. - Set `maxItems` to a small value (10–50) for quick tests; 0 for a full catalog run (~5,000 companies). - Full catalog runs with reviews can produce millions of records and take several hours. # Actor input Schema ## `sp_intended_usage` (type: `string`): Please describe how you plan to use the data extracted by this crawler. ## `sp_improvement_suggestions` (type: `string`): Provide any feedback or suggestions for improvements. ## `sp_contact` (type: `string`): Provide your email address so we can get in touch with you. ## `mode` (type: `string`): Scrape company profiles, reviews only, or both. ## `companySlugs` (type: `array`): Specific RepVue company slugs to scrape (e.g. 'salesforce', 'hubspot'). Overrides filter/catalog mode. ## `industry` (type: `string`): Filter companies by industry. Leave empty to include all. ## `companySize` (type: `string`): Filter by employee count range. Leave empty to include all. ## `minRating` (type: `integer`): Minimum overall RepVue score (0-100). Only companies at or above this score are returned. ## `maxItems` (type: `integer`): Maximum number of records to return. Set to 0 for unlimited. ## Actor input object example ```json { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "both", "companySlugs": [ "salesforce", "hubspot" ], "minRating": 0, "maxItems": 5 } ``` # Actor output Schema ## `results` (type: `string`): No description # 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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "both", "companySlugs": [ "salesforce", "hubspot" ], "industry": "", "companySize": "", "minRating": 0, "maxItems": 5 }; // Run the Actor and wait for it to finish const run = await client.actor("jungle_synthesizer/repvue-employer-scraper").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 = { "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "both", "companySlugs": [ "salesforce", "hubspot", ], "industry": "", "companySize": "", "minRating": 0, "maxItems": 5, } # Run the Actor and wait for it to finish run = client.actor("jungle_synthesizer/repvue-employer-scraper").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 '{ "sp_intended_usage": "Describe your intended use...", "sp_improvement_suggestions": "Share your suggestions here...", "sp_contact": "Share your email here...", "mode": "both", "companySlugs": [ "salesforce", "hubspot" ], "industry": "", "companySize": "", "minRating": 0, "maxItems": 5 }' | apify call jungle_synthesizer/repvue-employer-scraper --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jungle_synthesizer/repvue-employer-scraper", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "RepVue Scraper - Sales Rep Employer Reviews, OTE & Quota Data", "description": "Scrape RepVue.com for B2B SaaS sales compensation and employer review data. Extract company profiles with OTE, base salary, commission structure, quota attainment, ramp time, and employer ratings across ~5K companies.", "version": "0.1", "x-build-id": "fdUujfaCedZZKsYbU" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jungle_synthesizer~repvue-employer-scraper/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jungle_synthesizer-repvue-employer-scraper", "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/jungle_synthesizer~repvue-employer-scraper/runs": { "post": { "operationId": "runs-sync-jungle_synthesizer-repvue-employer-scraper", "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/jungle_synthesizer~repvue-employer-scraper/run-sync": { "post": { "operationId": "run-sync-jungle_synthesizer-repvue-employer-scraper", "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", "required": [ "sp_intended_usage", "sp_improvement_suggestions" ], "properties": { "sp_intended_usage": { "title": "What is the intended usage of this data?", "minLength": 1, "type": "string", "description": "Please describe how you plan to use the data extracted by this crawler." }, "sp_improvement_suggestions": { "title": "How can we improve this crawler for you?", "minLength": 1, "type": "string", "description": "Provide any feedback or suggestions for improvements." }, "sp_contact": { "title": "Contact Email", "minLength": 1, "type": "string", "description": "Provide your email address so we can get in touch with you." }, "mode": { "title": "Mode", "enum": [ "companies", "reviews", "both" ], "type": "string", "description": "Scrape company profiles, reviews only, or both." }, "companySlugs": { "title": "Company Slugs", "type": "array", "description": "Specific RepVue company slugs to scrape (e.g. 'salesforce', 'hubspot'). Overrides filter/catalog mode.", "items": { "type": "string" } }, "industry": { "title": "Industry Filter", "enum": [ "", "AdTech", "B2B SaaS", "FinTech", "HR Tech", "MarTech", "Security", "DevTools", "E-Commerce", "HealthTech", "Insurance" ], "type": "string", "description": "Filter companies by industry. Leave empty to include all." }, "companySize": { "title": "Company Size Filter", "enum": [ "", "1-50", "51-200", "201-500", "501-1000", "1001-5000", "5001+" ], "type": "string", "description": "Filter by employee count range. Leave empty to include all." }, "minRating": { "title": "Minimum Rating", "type": "integer", "description": "Minimum overall RepVue score (0-100). Only companies at or above this score are returned.", "default": 0 }, "maxItems": { "title": "Max Items", "type": "integer", "description": "Maximum number of records to return. Set to 0 for unlimited.", "default": 5 } } }, "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 } } } } } } } } } } ```