RepVue Scraper

Extract verified sales-employer ratings, compensation benchmarks, and full review threads from RepVue.com — the "Glassdoor for sales reps" where Account Executives, SDRs, BDRs, and CSMs rate the companies they actually work for. Paste company URLs, drop in bare slugs (Salesforce, Gongio, Outreach), or filter the directory by industry and company size — every row carries a recordType discriminator so you can split companies and reviews from one dataset in a single click.

Built for sales operators, recruiters, RevOps teams, and market-intelligence analysts who need RepVue-grade employer signal — verified comp, % to quota, and rep-level reviews — without signing in, hitting per-search limits, or wrestling with a JavaScript-heavy SPA themselves.

Why This Scraper?

• Two record types in one run — company rows carry the RepVue Score, review counts, headcount, funding source, and a compensation roll-up; review rows carry the verified-rep flag, full body, average metric rating, reviewer status (Current Employee / Former Employee), and any official company response
• 21 industries × 5 company-size bands = 105 directory facet combinations — Software, SaaS-adjacent Internet, Pharma and Biotech, Medical Devices, Finance, Manufacturing, Telecom, Real Estate, Retail / Automotive, and 12 more, crossed with 1–50 / 51–250 / 251–1,000 / 1,001–10,000 / 10,001+ employee bands
• Compensation breakdown by role — per-role avg base, median base, avg OTE, median OTE, average quota attainment, highest potential earnings, and a dataFreshness flag (current vs aged >12 months) for AEs, SDRs, BDRs, Enterprise AEs, Mid-Market AEs, CSMs, Sales Engineers, and every other role RepVue tracks
• Verified-only signal — every review row carries ratingVerified: true/false and verifiedReviewPercent on the parent company, so you can filter to the rep-verified subset RepVue actually displays publicly
• Flexible date filter — reviewsSince accepts a calendar date (2025-04-01), an ISO timestamp, or a relative window (30d, 6 months, 1 year) — useful for quarterly comp-shift tracking and post-RIF morale snapshots
• Three input modes, mixable — full company URLs (https://www.repvue.com/companies/Salesforce), bare slugs (Outreach, Gongio), and directory URLs with encoded filters (/companies?industries.name[]=Software) — combine any of the three in one run
• Lean output mode — includeReviews: false returns one row per company (rating, review count, compensation summary) and drops the cost to $0.01 per company — ideal for full-directory market sizing
• Content-category tags on every review — RepVue tags each review with topics like "Compensation", "Leadership", "Product", "Work-Life Balance", and "Inbound Lead Flow" so you can slice reviews by what the rep was actually rating
• Reviewer-role and reviewer-location signal — every review surfaces the reviewer's role tag (Account Executive, SDR, etc.) and location tag, letting you isolate "what AEs in North America say about Salesforce in 2026"

Use Cases

Sales Lead Research & Account Intelligence

• Pull every Software company on RepVue with 1,001–10,000 employees plus avg-OTE benchmarks for outbound prospecting
• Identify companies whose reviewers consistently flag "weak inbound lead flow" — a hot signal for marketing-automation pitches
• Build a watchlist of companies whose hasActiveJobs is true and activeJobsCount is climbing month-over-month

Recruiter Sourcing & Pipeline Building

• Find every B2B SaaS company in the 251–1,000 band that pays Account Executives over $250K OTE
• Track which companies have the highest verified-review-percent — high verification = a real, engaged sales population
• Flag companies whose compensationDataFreshness is "aged" so you know which comp numbers your candidates will discount

Compensation Benchmarking

• Aggregate avg base, avg OTE, and avg quota attainment across an entire industry for board-deck-grade comp reports
• Compare per-role compensation across 21 industries — Software AE OTE vs Healthcare AE OTE vs FinTech AE OTE
• Track comp drift quarter-over-quarter using reviewsSince=90d against a stored snapshot

Market Intelligence & GTM Strategy

• Pull every company in two industries side-by-side to map relative RepVue Score, culture rating, and product rating
• Identify "RepVue darlings" (overallRating > 80, reviewCount > 50) for case-study targeting and competitive positioning
• Spot companies trending downward by sampling reviewsSince=30d versus the historical aggregate

Job-Seeker Diligence

• Read every verified review from current and former AEs at a shortlist of target companies before accepting an offer
• Compare quotaAttainment across 5 finalist companies — % to quota is the single best leading indicator of comp realism
• Check companyResponse to see whether leadership engages with rep feedback or stays silent

Investor & Equity Research

• Surface employee-experience signal on private B2B SaaS portfolio companies that don't show up on Glassdoor
• Track product, leadership, and incentive-comp-plan ratings as a leading indicator before a Series C raise
• Use fundingSource plus headcount trajectory plus compensation freshness to triage a portfolio at scale

Getting Started

Pull one company's profile and most-recent reviews

{
    "startUrls": ["Salesforce"],
    "maxReviewsPerCompany": 50
}

Sweep the Software directory, companies only (lean + cheap)

Skip reviews entirely for a quick market scan — only the company row, no review charges:

{
    "industries": ["Software"],
    "companySizes": ["1,001-10,000", "10,001+"],
    "includeReviews": false,
    "maxResults": 500
}

Quarterly comp-shift snapshot

Mix slugs, URLs, and a relative date filter to grab the last 90 days of verified review activity across a shortlist:

{
    "startUrls": [
        "Salesforce",
        "https://www.repvue.com/companies/Gongio",
        "Outreach",
        "HubSpot"
    ],
    "reviewsSince": "90d",
    "maxReviewsPerCompany": 200,
    "includeCompensation": true,
    "maxResults": 1000
}

Input Reference

What to Scrape

Parameter	Type	Default	Description
startUrls	string[]	[]	RepVue inputs in any combination. Accepts full company URLs (https://www.repvue.com/companies/Salesforce), bare slugs (Salesforce, Gongio, Outreach), or directory URLs with encoded filters (https://www.repvue.com/companies?industries.name[]=Software). Leave empty to crawl the full directory.
industries	string[]	[]	Industry filter for directory mode. Options: Construction, Direct-to-Consumer, Education, Finance, Healthcare and Hospitals, Information Technology and Services, Internet, Leisure / Hospitality, Manufacturing, Media and Publishing, Medical Devices, Natural Resources / Mining, Pharma and Biotech, Professional / Business Services, Real Estate, Retail / Automotive, Software, Staffing and Recruiting, Telecom, Transportation, Wholesale.
companySizes	string[]	[]	Employee-size band filter for directory mode. Options: 1–50, 51–250, 251–1,000, 1,001–10,000, 10,001+.

Output Control

Parameter	Type	Default	Description
includeReviews	boolean	true	Embed each company's verified reviews as separate rows. Turn off for a quick directory scan that returns only company-card rows — much faster and cheaper.
includeCompensation	boolean	true	Include compensation fields on each company row plus the per-role compensation breakdown. Turn off only if you want the lightest possible payload.

Filters & Limits

Parameter	Type	Default	Description
reviewsSince	string	(none)	Only include reviews created on or after this point. Accepts a calendar date (2025-04-01), an ISO timestamp (2025-04-01T12:00:00Z), or a relative value (30d, 6 months, 1 year).
maxReviewsPerCompany	integer	50	Cap on reviews per company, most-recent first. 0 lifts the cap (internal ceiling of 2,000 still applies).
maxResults	integer	100	Hard cap on total rows across every company (companies + reviews combined). 0 lifts the cap (internal ceiling of 100,000 still applies). The actor stops requesting new pages once this number is reached but keeps the full final page.

Output

Every row carries a recordType field — company or review — so a single dataset query can split the two streams in your downstream pipeline.

company rows

{
    "recordType": "company",
    "name": "Salesforce",
    "slug": "Salesforce",
    "url": "https://www.repvue.com/companies/Salesforce",
    "industry": "Software",
    "companySize": "10,001+",
    "description": "Salesforce is the global leader in CRM.",
    "logoUrl": "https://ik.imagekit.io/repvue/nqkacy7hk1xi8bjgakz9sm06ou5m",
    "website": "https://www.salesforce.com/",
    "careersUrl": "https://www.salesforce.com/company/careers/",
    "fundingSource": "Public",
    "headcount": 74895,
    "fka": null,
    "customerClaimed": true,
    "freePreview": false,
    "published": true,
    "publishedStatus": "full",
    "overallRating": 82.4,
    "averageRating": 4.12,
    "reviewCount": 1438,
    "verifiedReviewCount": 1284,
    "verifiedReviewPercent": 89.3,
    "quotaAttainment": 64.2,
    "hasActiveJobs": true,
    "activeJobsCount": 412,
    "productRating": null,
    "cultureRating": null,
    "incentiveCompPlanRating": null,
    "leadershipRating": null,
    "inboundLeadFlowRating": null,
    "professionalDevelopmentRating": null,
    "avgBaseSalary": 112400,
    "avgOTE": 248900,
    "avgQuotaAttainment": 64.2,
    "compensationByRole": [
        {
            "role": "Enterprise Account Executive",
            "roleSlug": "enterprise-account-executive",
            "sampleSize": 184,
            "baseSalary": 135200,
            "medianBaseSalary": 130000,
            "ote": 287400,
            "medianOte": 280000,
            "highestPotentialEarnings": 612000,
            "quotaAttainment": 61.4,
            "dataFreshness": "current"
        }
    ],
    "compensationDataFreshness": "current",
    "scrapedAt": "2026-05-18T09:01:42Z"
}

Core company fields

Field	Type	Description
recordType	string	Always "company"
name	string	Company display name
slug	string	RepVue URL slug
url	string	Public RepVue profile URL
industry	string	RepVue's canonical industry classification
companySize	string	Employee band (1-50, 51-250, 251-1,000, 1,001-10,000, 10,001+)
description	string	Company description as shown on RepVue
logoUrl	string	CDN URL of the company logo
website	string	Corporate website
careersUrl	string	Direct link to careers page
fundingSource	string	Public / Private / Venture-backed, etc.
headcount	integer	Last reported headcount
fka	string	"Formerly known as" name (when applicable)
customerClaimed	boolean	Profile claimed by the company
freePreview	boolean	Free-preview flag
published	boolean	Currently visible on RepVue
publishedStatus	string	RepVue's publication state. "full" for the standard publicly-listed profile; other values indicate limited or in-flight listings.
hasActiveJobs	boolean	RepVue is currently listing open roles
activeJobsCount	integer	Number of active job listings
scrapedAt	string	ISO-8601 timestamp of extraction

Ratings (company row)

Field	Type	Description
overallRating	number	The RepVue Score (0–100) — RepVue's headline composite
averageRating	number	Average rating on the 0–5 scale shown next to the score
reviewCount	integer	Total reviews on RepVue
verifiedReviewCount	integer	Reviews from sales reps who verified their employment
verifiedReviewPercent	number	Verified share of reviewCount, as a percent
quotaAttainment	number	Company-level avg quota attainment (%)
productRating	number	Product sub-rating (returned as null on the canonical company dict; populated when RepVue exposes it)
cultureRating	number	Culture sub-rating
incentiveCompPlanRating	number	Incentive comp plan sub-rating
leadershipRating	number	Leadership sub-rating
inboundLeadFlowRating	number	Inbound lead flow sub-rating
professionalDevelopmentRating	number	Professional development sub-rating

Compensation (company row)

Field	Type	Description
avgBaseSalary	number	Weighted-average base salary across all roles (USD)
avgOTE	number	Weighted-average on-target earnings across all roles (USD)
avgQuotaAttainment	number	Weighted-average % to quota across all roles
compensationByRole	object[]	Per-role compensation breakdown — see fields below
compensationDataFreshness	string	"current" or "aged" (any role contributing data is >12 months old)

Each element of compensationByRole carries: role, roleSlug, sampleSize, baseSalary, medianBaseSalary, ote, medianOte, highestPotentialEarnings, quotaAttainment, dataFreshness.

review rows

{
    "recordType": "review",
    "id": 119332,
    "slug": "salesforce-review-av94tu0k",
    "companySlug": "Salesforce",
    "companyName": "Salesforce",
    "companyUrl": "https://www.repvue.com/companies/Salesforce",
    "url": "https://www.repvue.com/companies/Salesforce/reviews/salesforce-review-av94tu0k",
    "body": "Overall, not a bad experience. However, if you are external it will be a learning curve, and you will not get a good territory.",
    "rating": 4.0,
    "ratingVerified": true,
    "reviewerStatus": "Current Employee",
    "reviewerRole": "Account Executive",
    "reviewerLocation": "US",
    "pinned": false,
    "upvotes": 1,
    "contentCategories": [],
    "promptQuestion": null,
    "followupQuestion": "How much does that territory disadvantage typically extend your expected ramp time?",
    "followupAnswer": "At least 3-6 months, depends on your manager.",
    "companyResponse": null,
    "metricRatings": {
        "id": 539783,
        "average_metric_rating": 4.0,
        "created_at": "2026-05-14T21:09:04.993+00:00"
    },
    "createdAt": "2026-05-14T21:09:45.212+00:00",
    "scrapedAt": "2026-05-18T09:01:42Z"
}

Field	Type	Description
recordType	string	Always "review"
id	integer	RepVue's internal review ID
slug	string	URL-safe review slug
companySlug	string	Parent company slug
companyName	string	Parent company name
companyUrl	string	Parent company profile URL
url	string	Direct link to the review
body	string	Free-text review body
rating	number	Reviewer's average metric rating (0–5)
ratingVerified	boolean	true when the reviewer verified employment
reviewerStatus	string	"Current Employee" or "Former Employee"
reviewerRole	string	Role tag (Account Executive, SDR, BDR, etc.)
reviewerLocation	string	Geography tag (US, Non-US, etc.)
pinned	boolean	Pinned to the top of the company's review feed
upvotes	integer	Community upvote count
contentCategories	string[]	RepVue topic tags (Compensation, Leadership, etc.) — may be an empty list when the reviewer didn't tag a topic
promptQuestion	string	Question the reviewer was answering, when RepVue surfaces the prompt text; null otherwise
followupQuestion	string	Optional follow-up question RepVue asked
followupAnswer	string	Reviewer's answer to the follow-up
companyResponse	string	Official response from the company, when one exists
metricRatings	object	Headline rating sub-object: id, average_metric_rating, created_at. Per-dimension sub-rating breakdowns are not exposed by RepVue's public profile data.
createdAt	string	ISO-8601 timestamp of the review
scrapedAt	string	ISO-8601 timestamp of extraction

Tips for Best Results

• Slugs are case-sensitive and don't always match the brand name. RepVue's URL slug is what wins — Gong is a 404, the correct slug is Gongio. When in doubt, copy the slug straight out of a https://www.repvue.com/companies/<slug> URL.
• Set includeReviews: false for whole-industry market scans. At $0.01 per company you can sweep the entire 21-industry directory and only pay the company line — perfect for board-deck comp tables, TAM sizing, and trigger lists.
• Use reviewsSince=90d for quarterly comp-shift tracking. Reviews are pulled newest-first and pagination stops the moment we cross your cutoff date — no wasted requests on old data.
• Combine industries and companySizes to scope a long-tail directory crawl. Software × 1,001–10,000 returns hundreds of companies; Construction × 1–50 may return zero — the actor returns a friendly status message with the filter values so you know to widen.
• compensationDataFreshness: "aged" means RepVue's data on that role is >12 months old. Use this to flag stale comp benchmarks in candidate negotiations and competitive-intel decks.
• Aggregate verifiedReviewPercent across a watchlist. Companies with a verified share under ~70% have a smaller, less engaged sales population — a leading-indicator on culture and review quality.
• Filter reviews by contentCategories. When you only care about compensation reviews, post-process recordType == "review" rows where "Compensation" is in contentCategories — much faster than reading every review body.

Pricing

Pay-Per-Event — $0.01 per company row and $0.0007 per verified review row. No compute charges — you only pay for the records returned.

Event	Fires when	Rate
Company record	Every company-card row pushed to the dataset	$0.01 each ($10 / 1,000 companies)
Verified review record	Every verified review row pushed (only when includeReviews is on)	$0.0007 each ($0.70 / 1,000 reviews)

Example costs

Assuming a typical mix of 50 reviews per company:

Companies	Reviews (50/co avg)	Company cost	Review cost	Total
100	5,000	$1.00	$3.50	$4.50
1,000	50,000	$10.00	$35.00	$45.00
10,000	500,000	$100.00	$350.00	$450.00
100,000	5,000,000	$1,000.00	$3,500.00	$4,500.00

Set includeReviews: false and the cost drops to the company column only: $1.00 / $10 / $100 / $1,000 for 100 / 1,000 / 10,000 / 100,000 companies respectively.

Integrations

Export data in JSON, CSV, Excel, XML, or RSS. Connect to 1,500+ apps:

• Apify API — Full programmatic access to runs and datasets
• Webhooks — POST results to your own endpoint the moment a run completes
• Zapier / Make / n8n — Workflow automation across thousands of apps
• Google Sheets — Direct spreadsheet export for collaborative analysis
• Slack / Email — Notifications on new results

Legal & Ethical Use

This actor collects publicly available information that RepVue chooses to display without a login wall — company profiles, aggregate ratings, and verified reviews. You are responsible for complying with RepVue's Terms of Service, the RepVue User Agreement, and all applicable laws including GDPR, CCPA, and other privacy regulations.

Do not use the collected data for harassment, doxxing, retaliation against named reviewers, or any unlawful purpose. RepVue reviewers are sales professionals sharing employer feedback — treat the data the same way RepVue's own product would, and avoid attempting to re-identify individual reviewers from role and location tags.