RepVue Scraper: Company Reviews, Ratings and Sales Compensation

RepVue turns sales-rep company reviews into structured data. Get one rich record per company: the full profile and RepVue Score, sales-rep reviews, compensation by role (OTE, base pay, percentiles, and highest potential earnings), open sales jobs, and community questions. Search and filter the whole RepVue company index, or paste specific company links, then export to JSON, CSV or Excel, or read the results through the API.

Why This Scraper?

• One rich record per company. Profile, RepVue Score, ratings, reviews, and pay are merged into a single row, so you get the whole picture instead of stitching reviews back to companies yourself.
• Compensation by sales role. Median and average OTE, base pay, 75th-percentile pay, and highest potential earnings, plus a company-wide pay summary.
• Full review detail. Review body, numeric rating, verified flag, reviewer role and location tags, and upvotes, with a company response and a follow-up question and answer when RepVue recorded one.
• Two ways to work. Search and filter the whole RepVue company index, or paste specific company links or slugs.
• Real filters. Industry, minimum RepVue Score, and company size, with four sort options.
• Optional add-ons. Switch on open sales jobs and community Q&A per company only when you need them, so you don't pay for requests you don't use.
• Review depth control. Cap or uncap reviews per company independently of the run-wide company cap, and keep only reviews from a chosen date onward.

Use Cases

• Recruiters and talent teams: benchmark sales compensation and screen employer reputation before extending offers.
• RevOps and sales leadership: compare RepVue Scores, review sentiment, and pay bands across competitors.
• Compensation analysts: build OTE and base-pay benchmarks by role, industry, and company size.
• Job seekers and sales reps: research a company's reviews, pay ranges, and open sales roles before applying.
• Market researchers: track industry-wide rating and compensation trends across companies over time.

Data You Get

Sample shape: values are illustrative placeholders, not from a live company.

Field	Example
recordType	"company"
id	1
slug	"SampleCompany"
name	"Sample Company"
url	"https://www.repvue.com/companies/SampleCompany"
repvueScore	81.97
averageRating	3.5
ratings_count	715
verified_ratings_percent	91.19
industry	"Software"
size / sizeLabel	"to_10000" / "1001-10000"
funding_source	"Public"
last_headcount	2924
description	"Short company description text appears here."
website / careers_url	"https://www.example.com/" / "https://careers.example.com/"
compensation.summary	{ "highest_base": 165000, "lowest_base": 50000, "total_ratings_count": 212 }
compensation.roles[].role	"Account Executive"
compensation.roles[].median_ote / median_base_compensation	150000 / 75000
compensationRolesCount	1
reviewsCount	1
reviews[].body / rating / reviewer_role_tag	"Strong enablement..." / { "score": 4, "type": "overall" } / "Account Executive"
reviews[].rating_verified / upvotes	true / 0
jobsCount	0 (when Include jobs is on)
questionsCount	0 (when Include questions is on)
scrapedAt	"2026-01-01T00:00:00.000Z"

Every record is the same kind: a company profile with reviews, compensation, jobs, and community questions nested inside it, not separate rows you need to join yourself. Fields from the RepVue profile are passed through as-is alongside the computed convenience fields above, so an unusual company page can carry a few extra columns beyond this table.

How to Use

1. Pick a mode: search discovers and filters companies from RepVue's index, url scrapes the specific company links or slugs you paste.
2. In search mode, set your filters (industry, minimum RepVue Score, company size) and a sort order. In URL mode, paste company links or slugs.
3. Switch on the detail you need: reviews, compensation, open jobs, community Q&A, and set how many reviews per company.
4. Set Max companies to control run size and cost, then click Start.

Scrape three companies by link, with reviews and compensation:

{
  "mode": "url",
  "startUrls": [
    "https://www.repvue.com/companies/Klaviyo",
    "https://www.repvue.com/companies/Wiz",
    "https://www.repvue.com/companies/GrafanaLabs"
  ],
  "includeReviews": true,
  "includeSalaries": true,
  "maxReviews": 50
}

Find top-rated Software companies:

{
  "mode": "search",
  "industries": ["Software"],
  "minRepvueScore": 80,
  "sortBy": "repvue_score_desc",
  "maxItems": 25,
  "proxy": { "useApifyProxy": true, "apifyProxyGroups": ["RESIDENTIAL"], "apifyProxyCountry": "US" }
}

Recent reviews only, for one company:

{
  "mode": "url",
  "startUrls": ["https://www.repvue.com/companies/Klaviyo"],
  "includeReviews": true,
  "maxReviews": 100,
  "targetDate": "2025-01-01"
}

Profile and pay only, no reviews, largest companies:

{
  "mode": "search",
  "companySize": "over_10001",
  "includeReviews": false,
  "includeSalaries": true,
  "maxItems": 50
}

Run it from your code

Python:

from apify_client import ApifyClient

client = ApifyClient("<YOUR_APIFY_TOKEN>")
run = client.actor("abotapi/repvue-scraper").call(run_input={"mode": "url", "startUrls": ["https://www.repvue.com/companies/Klaviyo"]})
for company in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(company["name"], company["repvueScore"])

JavaScript:

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: '<YOUR_APIFY_TOKEN>' });
const run = await client.actor('abotapi/repvue-scraper').call({ mode: 'url', startUrls: ['https://www.repvue.com/companies/Klaviyo'] });
const { items } = await client.dataset(run.defaultDatasetId).listItems();

Or connect it to Make, Zapier, n8n, Google Sheets or webhooks from the Integrations tab.

Send results into your apps (MCP connectors)

Optionally pipe the scraped results into the apps you already use, via Model Context Protocol (MCP) connectors. This is an extra delivery step after the scrape: the Apify dataset is never changed.

What gets written to the connector: a condensed, human-readable summary of each company record, not the full JSON. Each item becomes one entry with a title and its key fields flattened to plain text. The complete record always stays in the Apify dataset.

1. Authorize a connector once under Apify, Settings, Integrations (Notion, Linear, Airtable, or Apify).
2. Select it in the "Pipe results into your apps" input field. If the picker is empty, you haven't authorized a connector yet.
3. For Notion, also set notionParentPageUrl to the page where items should be created.
4. Optionally lower maxNotifyListings to cap how many companies get exported per run; it never changes what lands in the dataset.

The connection is mediated by Apify's MCP proxy, so this actor never sees your third-party credentials. Leave the field empty to skip.

Input Parameters

Parameter	Type	Default	Description
mode	string	search	search discovers and filters companies from the index; url scrapes the links or slugs you paste.
search	string	(none)	Search mode: keep companies whose slug (the name in the RepVue URL) contains this text.
industries	array	[]	Search mode: keep only companies whose industry matches one of these terms.
minRepvueScore	integer	(none)	Search mode: minimum RepVue Score, 0 to 100.
companySize	string	"" (any size)	Search mode: headcount band filter (to_250, to_1000, to_10000, over_10001).
sortBy	string	name_asc	Order of returned companies. Name sorts only reorder search-mode discovery; RepVue Score and ratings-count sorts also reorder the result set in URL mode.
startUrls	array	none (prefill: ["https://www.repvue.com/companies/Klaviyo"])	URL mode: company links or bare slugs.
includeReviews	boolean	true	Attach sales-rep reviews to each company.
includeSalaries	boolean	true	Attach compensation by sales role plus a pay summary.
includeJobs	boolean	false	Attach the company's currently listed sales jobs (one extra request per company).
includeQuestions	boolean	false	Attach community questions and answers (one extra request per company).
maxReviews	integer	100	Cap on reviews attached to each company. 0 for all available reviews. Per-company depth, not a run cap.
targetDate	string	(none)	Keep only reviews created on or after this date (YYYY-MM-DD).
maxItems	integer	20	Stop after this many companies across the whole run. This is the only run-wide cap; 0 for no limit.
proxy	object	{ "useApifyProxy": true }	Connection settings.
maxResidentialMB	integer	0	Only applies on the Residential proxy group: after this many MB, the run auto-downgrades to Datacenter. 0 means no cap.
mcpConnectors	array	(none)	Optional: send a summary of each company to apps you authorized under Integrations.
notionParentPageUrl	string	(none)	Notion connector only: page under which company pages are created.
maxNotifyListings	integer	50	Cap on items written to each connector per run.

Output Example

Sample shape: values are illustrative placeholders, not from a live company.

{
  "recordType": "company",
  "id": 1,
  "slug": "SampleCompany",
  "name": "Sample Company",
  "industry": "Software",
  "size": "to_10000",
  "sizeLabel": "1001-10000",
  "funding_source": "Public",
  "last_headcount": 2924,
  "description": "Short company description text appears here.",
  "website": "https://www.example.com/",
  "careers_url": "https://careers.example.com/",
  "url": "https://www.repvue.com/companies/SampleCompany",
  "repvueScore": 81.97,
  "averageRating": 3.5,
  "ratings_count": 715,
  "verified_ratings_percent": 91.19,
  "compensation": {
    "summary": { "highest_base": 165000, "lowest_base": 50000, "total_ratings_count": 212 },
    "availableBusinessUnits": ["Sales"],
    "roles": [
      { "role": "Account Executive", "median_ote": 150000, "median_base_compensation": 75000, "average_highest_potential_earnings": 309529, "ratings_count": 85 }
    ]
  },
  "compensationRolesCount": 1,
  "reviews": [
    { "id": 1, "body": "Strong enablement and supportive leadership.", "rating": { "score": 4, "type": "overall", "user_status": "current" }, "reviewer_role_tag": "Account Executive", "rating_verified": true, "upvotes": 0 }
  ],
  "reviewsCount": 1,
  "jobsCount": 0,
  "jobs": [],
  "questionsCount": 0,
  "questions": [],
  "scrapedAt": "2026-01-01T00:00:00.000Z"
}

Plan Requirement

The default connection setting works out of the box and is the lowest-cost option, and the actor holds a separate connection in reserve for the search-mode discovery step, falling back automatically when a connection is refused. If search mode returns no companies, switch the proxy group to Residential under Connection, or use URL mode with specific company links instead.

FAQ

How much does it cost?

You pay per company record returned. Turning on reviews, compensation, jobs, or questions may add a per-company enrichment charge when that tariff is active. The Pricing tab shows the current rates. Use Max companies to cap the cost of any run.

Is it legal to scrape RepVue?

This actor collects only publicly available company review and compensation data. You are responsible for how you use it: follow RepVue's terms and the laws that apply to you, and get legal advice if you plan commercial redistribution.

Can I get only new or changed companies on a schedule?

You can schedule this actor from the Schedules tab, but each run scrapes fresh: there is no built-in mode that returns only companies or reviews that changed since the last run. Use targetDate to keep only reviews from a chosen date onward, or compare company slugs and RepVue Scores across runs yourself.

What's the difference between "Max companies" and "Max reviews per company"?

Max companies (maxItems) is the only run-wide cap: it stops the whole run after that many companies. Max reviews per company (maxReviews) only limits how many reviews are attached to each company already being returned; raising it does not add more companies.

Why did my run return no companies instead of failing?

If search-mode discovery can't read the site index, if URL mode has no startUrls, or if none of your companies matched, the run finishes successfully with an empty dataset and a status message explaining why. No placeholder or error row is written to the dataset, so you are not charged for any result rows. Check the run's status message, loosen your filters, switch the proxy group to Residential, or use URL mode with specific company links.

Can I use it with AI agents or MCP?

Yes. Call it from any Apify integration or MCP client, and use the connector field to push company summaries into Notion, Linear, or Airtable.

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