# 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, 1 monthly users, 79.3% 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 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

## 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/<slug>` and `/companies/<slug>/salaries`
3. **Reviews** — `/companies/<slug>/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.

## `resumeCursor` (type: `string`):

Leave empty for a fresh crawl. To CONTINUE a previous run where it stopped — without paying again for records you already received — paste the `resumeCursor` value from that run's Output (the run's OUTPUT key). Resume promptly: the previous run's data expires with your account's retention window (free tier: your ~10 most recent runs).

## `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 '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_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 '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# 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 <YOUR_API_TOKEN>"
            ]
        }
    }
}

```

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/FLeZvy3dT9nGvNP53/builds/xyjdeCizZNSI99UNK/openapi.json