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

{
  "mode": "both",
  "companySlugs": ["salesforce", "hubspot", "mondaycom"],
  "maxItems": 100
}

Output Schema

Company / Salary record

{
  "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.