Recruiting teams
Employer mapping
Favorable to scraping
Build a first-pass company list with visible ratings, review volume, and job posting counts before deciding where to spend manual research time.
Job Boards$50Free
OpenWork Job Reviews Scraper for CSV Export
This OpenWork job reviews scraper exports public OpenWork company listing rows into a structured CSV for employer research, recruiting intelligence, and market mapping. Import the workflow into the UScraper local desktop app to collect company names, profile URLs, ratings, industries, review counts, job counts, followers, and raw listing text without writing scraper code.
Output
CSV
Fields
10
Pagination
Next loop
Waits
Built in
Template
Free
At a glance
Extract OpenWork company review listings
OpenWork is useful when you need a high-level view of Japanese employers before choosing which companies deserve deeper review. This template focuses on listing-page data, not private review bodies or gated detail fields. It captures the public signals available in each visible listing row: the company name, OpenWork profile URL, overall rating, industry text, employee review count, salary/pay review count, question count, job posting count, follower count, and the raw row text for audit trails.
The automation is intentionally easy to inspect. UScraper sets a large browser window, navigates to https://www.openwork.jp/company_list?src_str=, waits for a company link, exports every matching row, checks whether a Japanese next link is available, clicks it, waits, pauses for two seconds, and loops back to the export step. If no next page exists, the run ends cleanly.
Listing data in one file
Export the company-level OpenWork data that is practical for spreadsheet review before you shortlist profiles for manual inspection.
Pagination already wired
The workflow uses a next-page condition and click loop, so each listing page appends into the same CSV instead of separate files.
Local desktop execution
The stock workflow writes to your configured local folder and does not send the CSV through a hosted scraping actor.
Best-effort public capture
The export is designed around visible listing rows. Annual salary ranges or deeper review attributes may require profile pages, login, or approved OpenWork access.
Who this is for
OpenWork data extractor use cases
Market analysts
Japan hiring research
Favorable to scraping
Compare public employer signals across industries, then filter by review count or follower count to find companies with enough data to evaluate.
Agencies
Repeatable reporting
Nuanced outcome
Export controlled batches for approved research scopes while keeping OpenWork policy checks and data reuse decisions separate from collection.
For adjacent job-market workflows, pair this scraper with the Doda Job Listing Scraper, BizReach Job Listings Scraper, and Google Job Scraper by Keywords. The broader UScraper template library includes search, recruiting, and company-data templates for follow-up enrichment.
How to use
Configure the OpenWork reviews scraper workflow
2
Choose the listing entry point
The Navigate block starts from the OpenWork company listing URL. Add a query or filter in OpenWork first if your research needs a narrower industry or keyword set.
3
Confirm the export path
Structured Export writes openwork_job_reviews_public_listing.csv with headers enabled and append mode on. Change the save folder before client or production runs.
4
Run the pagination loop
UScraper waits for company links, exports visible rows, checks for the next page link, clicks it when available, waits for load, and repeats.
5
Open and audit the CSV
Review row counts, blank rating cells, duplicated company URLs, and raw listing text before using the file in dashboards or downstream analysis.
Output preview
CSV columns produced by the template
The export mirrors the workflow definition and keeps one row per visible OpenWork company listing. Because the bundle did not include a sample CSV, the rows below are realistic examples based on the configured output fields.
| company_name | company_url | overall_rating | industry | employee_review_count | job_postings_count | followers_count |
|---|---|---|---|---|---|---|
| Example Systems Japan | https://www.openwork.jp/company.php?m_id=example001 | 3.72 | Software and IT services | 1842 | 26 | 5120 |
| Sakura Manufacturing | https://www.openwork.jp/company.php?m_id=example002 | 3.18 | Manufacturing | 967 | 14 | 2310 |
| Tokyo Retail Group | https://www.openwork.jp/company.php?m_id=example003 | 3.54 | Retail and e-commerce | 1205 | 42 | 3890 |
openwork_job_reviews_public_listing.csvColumn
company_name
Visible company name from the OpenWork listing row.
Column
company_url
OpenWork company profile URL for source tracing and manual review.
Column
overall_rating
Visible overall score when OpenWork exposes it in the listing row.
Column
industry
Industry text parsed near the rating and review-count labels.
Column
employee_review_count
Employee review count normalized without comma separators.
Column
salary_pay_review_count
Count of salary and pay review entries when that label appears.
Column
questions_count
Question count from the listing row.
Column
job_postings_count
Visible job posting count for the listed company.
Column
followers_count
Follower count normalized into a numeric-looking cell.
Column
raw_listing_text
Cleaned full row text for audits when a parsed field looks wrong.
Headers included - each OpenWork listing page appends into one file
Frequently asked questions
OpenWork listings may be publicly visible, but automated collection can still be limited by OpenWork terms, robots directives, copyright, privacy law, and how you reuse employee-review data. Keep runs modest, avoid bypassing access controls, and get legal review before publishing, reselling, or training models on exported data.
Before you run
Practical limits and maintenance notes
Keep these constraints visible
Access
Login, CAPTCHA, or registration gates may appear
The workflow waits for public listing links. If the page blocks access, do not bypass controls; use manual review or an approved data-access route.
Drift
OpenWork labels and layout can change
Blank cells usually mean a label changed, a listing row uses a different layout, or the company lacks that metric. Update the export columns before rerunning large batches.
Policy
Employee-review data needs careful reuse
Treat the CSV as a research export, document your lawful basis, and avoid republishing personal or sensitive review-derived material without legal and platform-policy review.
Download the free template, install the local desktop app from UScraper download, and use this workflow whenever you need to export OpenWork reviews into a structured CSV.
Get Started
Download and use this template instantly
$50Free
What's Included
- Template JSON file ready to import
- Pre-configured scraping nodes
- Works with UScraper desktop app
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