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
}

Accepted link shapes in URL mode: a bare slug (Klaviyo, case-sensitive), a numeric company id, https://www.repvue.com/companies/<slug>, and the same link with a /reviews, /salaries, /jobs or /questions suffix or a ?page=N or ?tab=reviews query; all normalize to the one company.

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	the example company page https://www.repvue.com/companies/Klaviyo	URL mode: company links, numeric ids or bare slugs. A /reviews, /jobs, /salaries or /questions suffix and any ?page=N or ?tab= query are normalized to the company, so they return the same company row as the plain link. If you leave the field out in URL mode, the example company is scraped instead of finishing with an empty dataset. Clear the list explicitly to scrape nothing.
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 the maximum of 1000. Per-company depth, not a run cap.
targetDate	string	(none)	Keep only reviews created on or after this date (YYYY-MM-DD).
minReviewRating	integer	0	Keep only reviews whose average metric rating (the mean of the review's metric scores, 1 to 5, can be fractional) is at least this value; 0 keeps all. Reviews with no rating are dropped when this is above 0.
reviewSort	string	default	Order of attached reviews: default, newest, rating_desc, rating_asc, upvotes. Non-default orders read all available review pages (up to 1000) before the cap.
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.
resumeFromRunId	string	(none)	Run id or dataset id of an earlier run; companies it already collected are skipped.
incrementalMode	boolean	false	Remember each company between runs and add changeType, changedFields, firstSeenAt, lastSeenAt. Unchanged companies are not re-emitted and carry no enrichment charge.
stateKey	string	(none)	Name of the saved baseline; empty derives it from your company set, filters and collect toggles (never the caps).
emitUnchanged	boolean	false	Also output companies marked UNCHANGED.
emitExpired	boolean	true	After a complete scan, output EXPIRED rows for previously tracked companies no longer found. Each EXPIRED row is one charged dataset item and counts toward Max companies; turn this off to avoid them.
ignoreFieldsForChanges	array	[]	Field names that must not count as a change (they stay in the output).
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

URL mode reads company data from RepVue's data service, which answers on the default (datacenter) connection setting, so no residential proxy is needed. The actor keeps a backup connection in reserve and switches to it automatically when a connection is refused; if your Apify plan has no proxy access at all, the run fails with a message saying a paid plan or your own proxy URLs are required.

Search mode lists companies from the site's public index pages. The site sometimes answers those pages with a security checkpoint; the actor retries each page several times on new connections, and discovery fails only when the checkpoint keeps appearing. In that case the run ends as failed with the message "Company discovery is unavailable: the site's public pages kept answering with a security checkpoint after repeated retries on new connections, so Search mode cannot list companies right now. Try again later, or use URL mode with specific company links or slugs instead." Switching the proxy group does not help; try again later or use URL mode.

FAQ

How much does it cost?

You pay per company record pushed to the dataset, plus one detail-enrichment event per company that carries enriched detail (reviews, compensation, jobs or questions). In incremental mode, each EXPIRED row is also one charged dataset item that counts toward Max companies; turn off emitExpired to avoid them. Skipped, unmatched or failed companies are never charged. The Pricing tab shows the current rates. Use Max companies to cap the cost of any run.

Which dataset views are available?

The output tab offers Overview, Reviews, Jobs and Questions views; the last three unwind the nested lists into one row per review, job or question.

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?

Yes. Turn on Incremental mode and schedule the actor from the Schedules tab. Each company is marked NEW, UPDATED, UNCHANGED, REAPPEARED or EXPIRED, with the changed field names. Unchanged companies are not output, and an unchanged company is not charged the detail-enrichment event. A company whose fetch failed keeps its previous baseline, and EXPIRED rows are only produced after a complete, uncapped, non-resumed scan. The Changes view of the dataset shows these columns. Use ignoreFieldsForChanges for fields such as ratings_count that you do not want to count as a change.

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, or no page could be loaded, the run ends as failed with a status message explaining why. If URL mode has no startUrls, or none of your companies matched, the run finishes 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, 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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