This Kununu scraper tutorial shows how to turn approved Kununu company profile URLs into a clean CSV with the Kununu Lead Scraper template for UScraper. You will prepare input URLs, import the workflow, confirm the export path, run a validation batch, and troubleshoot common issues before using the data for employer research or account list review.
Before you start
Prerequisites for scraping Kununu leads
You need UScraper installed as a local desktop app, the current Kununu Lead Scraper template, and a short list of Kununu company profile URLs your team is allowed to process. Start with three to five profiles, not a long account universe, because Kununu pages can vary by country, language, profile completeness, and anti-bot state.
Before automation, review the live profile pages, Kununu robots.txt, and Kununu terms. This article is a technical guide, not legal advice. Public visibility does not automatically mean a field is appropriate for collection, enrichment, or outreach.
Treat compliance as part of the workflow. Keep request volume modest, avoid restricted areas, do not bypass access controls, and preserve source URLs so exported rows can be audited later.
Workflow
How the Kununu leads scraper works
The Kununu Lead Scraper template is built around a guarded multi-URL loop. It navigates to each employer profile, waits for the page body, pauses for rendered content, checks whether the page says "confirm you are human", and only exports if that check is clear. If a challenge appears, the workflow gives a finite manual-solve window, refreshes, checks again, and ends safely if the challenge remains.
That flow matters because a blocked page should not become a fake lead row. The CSV should represent profiles that loaded enough for the export logic to read visible fields.
| Block | Purpose | Validation check |
|---|---|---|
| Navigate | Opens each configured Kununu profile URL | Replace sample URLs with reviewed profile pages. |
| Wait for Page Load and Sleep | Lets the page and dynamic modules render | Keep these waits during the first run. |
| Text Contains | Checks for a human verification page | Do not remove challenge detection to chase row count. |
| Structured Export | Appends one row from the loaded profile | Confirm filename, save folder, headers, and append mode. |
| Loop Continue | Advances to the next profile URL | Deduplicate input URLs before running. |
Runbook
How to scrape Kununu companies step by step
Collect approved profile URLs
Build a focused list of direct Kununu employer profile URLs, such as pages for companies your team is already researching. Avoid broad, open-ended crawling for the first pass.
Replace sample URLs
Open Navigate and replace the bundled sample URLs with your approved company profile list. Keep one profile per URL and remove duplicates.
Confirm the export path
In Structured Export, keep kununucom-leads-scraper.csv or rename it for the project. Clear older test files before a clean run because the template uses append mode.
Run a validation batch
Run three to five profiles, compare the CSV against the live pages, then widen the batch only after names, ratings, review counts, and source URLs look correct.
Export shape
Kununu to CSV fields and JSON workflow excerpt
No CSV sample ships with the bundle, so the JSON workflow definition is the authoritative sample. The table below describes the intended export shape and what to inspect after your first run.
| CSV column | What it captures | Validation check |
|---|---|---|
unternehmen_name | Company name from the heading or page metadata | Required for a usable row. |
ob_aktiv | Active, claimed, or employer-active signal when visible | Blank is acceptable if the profile does not show a signal. |
standort | Location or headquarters text | Compare against the visible profile and structured data. |
branche | Industry or category text | Expect differences across German and localized layouts. |
kundenbewertung | Visible rating value | Check decimal formatting and nearby rating labels. |
anzahl_der_bewertungen | Review count text | Compare with the profile's visible Bewertungen count. |
unternehmen_url | Canonical profile URL without tracking parameters | Use this for dedupe and audit. |
progress | Source marker for the processed profile URL | Keep it until cleanup is complete. |
Truncated workflow excerpt:
{
"project": {
"name": "Kununucom Leads Scraper",
"description": "Scrapes public Kununu company profile URLs and exports lead-style fields."
},
"blocks": [
{
"title": "Navigate",
"config": {
"urls": [
"https://www.kununu.com/de/deutsche-post",
"https://www.kununu.com/de/deutschebahn",
"https://www.kununu.com/de/lidl-deutschland"
]
}
},
{
"title": "Text Contains",
"description": "Check whether Kununu is showing a human/CAPTCHA challenge",
"config": {
"selector": "body",
"text": "confirm you are human",
"caseSensitive": false
}
},
{
"title": "Structured Export",
"config": {
"fileName": "kununucom-leads-scraper.csv",
"fileMode": "append",
"rowSelector": "body",
"columns": [
"unternehmen_name",
"ob_aktiv",
"standort",
"branche",
"kundenbewertung",
"anzahl_der_bewertungen",
"unternehmen_url",
"progress"
]
}
}
]
}
Quality control
Validate rows and fix common Kununu scraper issues
Open the CSV beside the live profiles and inspect rows from the beginning, middle, and end of the run. Sort by unternehmen_url to catch duplicate inputs, then review blank fields before enrichment.
| Symptom | Likely cause | Fix |
|---|---|---|
| Empty company name | The profile did not load or a challenge page was shown | Rerun one URL and watch the browser state. |
| Blank rating or review count | The profile hides the module, loaded late, or changed markup | Extend the wait and retest a small batch. |
| Repeated rows | Duplicate URL list or append-mode rerun | Deduplicate by unternehmen_url and clear test CSVs. |
| CAPTCHA text appears | Challenge detection was changed or bypassed | Restore the Text Contains check and stop the run when blocked. |
For recurring employer research, save the input URL list, run date, CSV filename, owner, and field changes beside the export. That run log is more useful than trying to reconstruct scope from a spreadsheet weeks later.
Alternatives
UScraper vs Octoparse, Apify, and Kununu scraper APIs
If you are comparing tools, separate "I need a reviewable CSV from selected profiles" from "I need managed cloud scraping infrastructure." UScraper is strongest for supervised local desktop runs, exact URL control, and quick CSV validation. The Octoparse Kununu template is relevant if your team already works in that no-code environment. Apify actors such as Kununu company scrapers and Kununu reviews scrapers are relevant when you want cloud runs, datasets, or API-based orchestration. API vendors such as Scrappa's Kununu API are a different lane again.
| Option | Best fit | Trade-off |
|---|---|---|
| UScraper local desktop app | Selected employer profiles, local CSV review, editable workflow blocks | You manage URL lists, pacing, and validation. |
| Hosted no-code template | Teams already standardized on a cloud scraping workspace | Data custody, pricing, and template behavior follow that provider. |
| Apify actor or scraper API | Scheduled runs, datasets, tokens, and developer integrations | Requires account setup, vendor billing, and API operations. |
| Manual research | Tiny lists or sensitive one-off checks | Slow, hard to repeat, but easiest to review case by case. |
Start with the smallest defensible workflow: one approved company list, one CSV, one validation pass, and one documented purpose.
FAQ
Kununu leads scraper FAQ
Kununu profile data may be publicly visible, but automated collection can still be limited by terms, robots guidance, database rights, privacy law, and local rules. Review the current Kununu policies, keep runs modest, avoid private or login-only data, and get legal review before commercial reuse.
Next step
Download the Kununu leads scraper template
Use the Kununu Lead Scraper template as the download path, then keep this tutorial open during your first validation run. For adjacent workflows, browse the UScraper template library or return to the UScraper blog for more local desktop app scraping tutorials.