Wanted Jobs Scraper - Companies & Salary Benchmarks
Pricing
from $1.00 / 1,000 results
Wanted Jobs Scraper - Companies & Salary Benchmarks
Scrape Wanted Korea jobs, company profiles and occupation salary benchmarks by experience for recruiting and compensation research. Choose the collection mode and set a result limit for each input.
Pricing
from $1.00 / 1,000 results
Rating
0.0
(0)
Developer
ScrapingMonkey
Maintained by CommunityActor stats
0
Bookmarked
2
Total users
1
Monthly active users
7 days ago
Last modified
Categories
Security
Limited permissionsShare
Collect public job listings, employer profiles and occupation salary benchmarks with Wanted Scraper. Compare Korean vacancies and hiring requirements with occupation salary figures broken down by experience, alongside company information. Choose the records you need and export them to CSV, JSON or Excel without supplying a site login.
Use the results for Korean recruitment and salary benchmarking. Submit matching public inputs in one run, retain the original record links, and send the structured output to your recruitment spreadsheet, reporting dashboard or research database.
| At a glance | Details |
|---|---|
| 📥 Input | Search fields or links to the selected items; see the examples below |
| 📤 Output | One row per vacancy / company / salary record |
| 📄 Pagination | Automatic up to maxResults for each input, when more results are available |
| 🔐 Login required | No |
| ⚡ Processing | Multiple inputs per run with automatic retries for temporary errors |
| 💾 Delivery | One complete Apify dataset table; CSV, JSON and Excel export |
What the Wanted scraper collects 💼
Collect job listings, employer profiles and occupation salary benchmarks. Compare Korean vacancies and hiring requirements with occupation salary figures broken down by experience, alongside company information.
| Collection | What you receive |
|---|---|
| Wanted jobs scraper | Records containing job titles, employers, employment types, ready for vacancy discovery and hiring-demand research. |
| Wanted company profile scraper | Records containing industries, company descriptions, locations, websites, ready for employer qualification and recruitment account enrichment. |
| Wanted company search scraper | Records containing industries, company descriptions, ready for employer prospecting and recruitment account research. |
| Wanted job details scraper | Records containing job titles, ready for vacancy enrichment and candidate-requirement analysis. |
| Wanted salary benchmarks scraper | Salary-by-experience records for the supplied occupation tag, with years of experience and published growth figures. |
Data can include:
- Record identity: Record identifiers, public links and the published job title or company name.
- Pay and compensation: Annual occupation salary by experience, the reported growth figures, currency and pay period.
- Employer information: Employer names, identifiers and profile links, with the company information attached to the public record.
- Location and workplace: Published workplace and location information and addresses.
- Descriptions and requirements: Published job or company descriptions, candidate requirements and responsibilities and tasks.
- Skills and qualifications: Experience or seniority requirements and occupation classification.
- Employment and benefits: Employment and contract types and published benefits.
- Dates and hiring activity: Closing dates and visible job counts.
How to scrape Wanted 🚀
- Choose Job Search in What to collect, or select another collection mode.
- Fill in the search fields, or paste links to the items you want to collect.
- Set the maximum results and any optional filters.
- Start the Actor and review the collected rows.
- Export the dataset or connect it to your application.
Wanted jobs scraper — input example
maxResults: 10 means up to 10 results for each input. It does not guarantee that the website has that many matches. You can set the limit as low as 1.
Wanted company profile scraper — input example
Wanted company search scraper — input example
Wanted job details scraper — input example
Wanted salary benchmarks scraper — input example
Wanted data fields and complete output 📦
| Field group | Included data |
|---|---|
| Record identity | Record identifiers, public links and the published job title or company name. |
| Pay and compensation | Annual occupation salary by experience, the reported growth figures, currency and pay period. |
| Employer information | Employer names, identifiers and profile links, with the company information attached to the public record. |
| Location and workplace | Published workplace and location information and addresses. |
| Descriptions and requirements | Published job or company descriptions, candidate requirements and responsibilities and tasks. |
| Skills and qualifications | Experience or seniority requirements and occupation classification. |
| Employment and benefits | Employment and contract types and published benefits. |
| Dates and hiring activity | Closing dates and visible job counts. |
Each collected item is a separate row. input identifies the submitted value and result_type identifies the selected mode. All returned fields appear in one table; columns that do not apply to a mode can be empty.
A complete JSON result is shown for every collection mode below, in the same order as the input examples. Each example includes every field for its mode; text and lists are not shortened. Values are representative and can change.
Wanted jobs scraper — complete JSON result
Wanted company profile scraper — complete JSON result
Wanted company search scraper — complete JSON result
Wanted job details scraper — complete JSON result
Wanted salary benchmarks scraper — complete JSON result
Images, tags and other lists stay with their parent result instead of creating extra rows. Invalid or unavailable inputs, inputs with no results, and requests that fail after all retries produce a row with status: failed. At most one failed row is saved per input; it includes error_code and error_message explaining the outcome. A normal end of pagination after collected results does not add a failed row.
Input requirements and collection settings ⚙️
| Setting | What to enter |
|---|---|
What to collect (mode) | Choose the information to collect. |
Maximum results per search or link (maxResults) | Collect up to this many results for each search or link. Minimum: 1. |
Job title or keywords (keywords) | For example, accountant or software engineer. Leave empty to browse all jobs. For Job Search, Company Search. |
Company page links (companyUrls) | Paste one link per line. Example: https://www.wanted.co.kr/company/11699 For Company Profiles. |
Job listing links (jobUrls) | Paste one link per line. Example: https://www.wanted.co.kr/wd/286649 For Job Details. |
Occupation (occupation) | Choose occupation. For Salary Benchmarks. |
| Collection mode | Fields to use |
|---|---|
| Company Profiles | Company page links |
| Company Search | Company name |
| Job Details | Job listing links |
| Job Search | Job title or keywords |
| Salary Benchmarks | Occupation |
The result limit applies separately to each search or supplied link. Collection ends earlier when no more matching results are available.
Wanted scraping use cases 🎯
Hiring activity monitoring
Run repeat collections of Wanted listings and compare vacancy titles and original links over time to identify newly advertised roles and changes in hiring activity.
Vacancy enrichment
Turn known Wanted job links or supported identifiers into structured vacancy records for recruitment databases, job comparison tools and candidate research.
Experience-based salary planning
Compare published annual salary benchmarks for an occupation across experience levels to support compensation research for Korean hiring.
Employer qualification
Research organisations listed on Wanted before adding them to recruitment or partnership lists. Retain their published identity, company description and available hiring context with the original profile link.
Skills demand analysis
Analyse the skills, experience or qualifications actually published in Wanted records to compare hiring requirements across role groups and prepare recruitment briefs.
Pricing and saved-result behavior 💰
See the Actor's Pricing tab for the active pricing model and current rate. Store settings may change, so this README does not claim a fixed cost.
Under dataset-item pricing:
- Each collected item saved in the dataset is one result.
- Images, tags and other values attached to that item do not create additional rows.
- Automatic retry attempts do not create extra dataset rows.
- A saved
failedrow is also one billable dataset item, including invalid inputs, unavailable items, no results, or exhausted retries. At most one failed row is saved per input, including when some results were already collected. maxResultscaps all saved rows for each input, including its failed row. Repeated copies of the same input are processed once. More inputs or a higher limit can produce more saved results.
Wanted scraper API and integrations 🔌
Replace $ACTOR_ID with the ID shown in the Actor API tab and $APIFY_TOKEN with your token.
Use schedules for recurring collection, webhooks for completion notifications, and Apify integrations for Google Sheets, Make, Zapier, cloud storage, a CRM or your own application.
Reliability, retries, and public-data limits ⚠️
Temporary connection errors, timeouts and access restrictions are retried automatically, up to five attempts. Invalid inputs save a failed row without an HTTP request; confirmed unavailable items save a failed row without unnecessary retries. Exhausted retries also save a failed row. Results already collected remain available if a later request fails, and normal pagination completion adds no error row. Collection also stops after two consecutive fully processed pages add no new results, even if the website provides another cursor. Required detail lookups are completed before checking a page; new results reset the counter, and independent reply branches are checked separately. Failures while initializing the Actor, saving data or scheduling requests stop the run instead of being reported as a failed website result.
Search is fixed to Korea. Salary Benchmarks accepts public Wanted salary URLs or occupation tag IDs. Employer IDs and arbitrary job-title text are not salary inputs.
Wanted controls which information is publicly available. Removed, private or restricted items may be unavailable, and optional values can be null or empty. A run can still fail if the results cannot be saved.
Frequently asked questions ❓
Does it require an account on Wanted?
No. You do not need to provide an account, password or login cookies. Only publicly available information is collected.
How does maxResults work?
It limits the number of saved results separately for every input. The minimum is 1. With maxResults set to 10, each input returns at most 10 available results. A detail lookup normally returns one record per input.
What input does Salary Benchmarks require?
Paste a public Wanted salary URL, such as https://www.wanted.co.kr/salary/872 for server developers, or enter an occupation tag ID. Employer IDs and arbitrary job-title text are not salary inputs.
Which country does search cover?
Job Search and Company Search use the Korean site. Other countries and advanced search filters are outside the supported scope.
Why are some fields empty?
The website may not publish that value, or the field may belong to a different collection mode. Missing values remain null or empty instead of being guessed.
Can I export the results to a spreadsheet?
Yes. Download CSV, Excel or JSON from the Apify dataset. All returned fields are included in the same results table.
Support and responsible use 🛟
For a reproducible issue, share the run ID, selected mode, result limit and a safe public example through the support channel. Never disclose access tokens, passwords or proxy credentials.
Use public Wanted information lawfully and responsibly. Follow applicable privacy, copyright, data-protection, contractual and platform requirements when storing, analyzing or redistributing results.
