Start with one useful dataset
Practical Apify guides for first-time users
Each guide starts with a bounded input, explains the output, shows what to verify, and links to a runnable public example. No scraper setup experience required.
First Apify run
Run your first Apify Actor and export one job
Use one current public listing to learn inputs, run status, datasets, and CSV export. No code required.
Read the guideGoogle Sheets and n8n
Send LinkedIn jobs to Google Sheets
Run one verified public job, secure the Apify credential, deduplicate by job ID, and schedule only after a manual test.
Read the guideVideo intelligence
Analyze one public YouTube video with Apify
Choose metadata, monitoring, sponsor evidence, chapters, or a source-only brief, then inspect one bounded result.
Read the guideYouTube discovery
Compare search, comment, channel and playlist workflows
Choose a bounded YouTube workflow by buyer question, billable unit, evidence fields, and first-run price.
Compare the toolsFreelance marketplaces
Scrape freelance jobs and marketplace demand
Choose a public contract-job source, run a bounded sample, verify fields, and understand the five private Freelancer.com workflows.
Read the guideBuyer guide
Choose the right LinkedIn jobs scraper
Compare search, details, intelligence, and monitoring by input, paid unit, current price, and bounded public Task.
Read the guideJobs data
Scrape LinkedIn jobs into a clean dataset
Run one keyword and location, inspect the fields, export the rows, and avoid common pagination and description mistakes.
Read the guideAPI integration
Use a LinkedIn jobs scraper as an API
Protect your token, start an asynchronous run, poll status, retrieve the dataset, and validate rows before import.
Read the guideAI tools and MCP
Use LinkedIn jobs data in ChatGPT or Claude
Connect the remote MCP server, inspect the right Actor, verify billing mode, and approve a bounded first run.
Read the guideChatGPT and MCP
Use Neuton Apify scrapers in ChatGPT
Discover public-data Actors, inspect inputs and prices, set a hard spending cap, and verify the result.
Read the guideMonitoring
Monitor new LinkedIn jobs without noisy alerts
Create a baseline, compare stable IDs, require posting-date evidence, and keep partial runs out of state.
Read the guideHiring intelligence
Build company intelligence from public job posts
Use consistent queries and source-linked evidence without treating job counts as growth or purchase predictions.
Read the guideRemote jobs
Collect Jobicy and Remotive jobs responsibly
Compare two public remote-job feeds, run a bounded search, verify application links, and schedule updates within source limits.
Read the guideSales and market research
Turn job postings into company hiring signals
Aggregate public vacancies by employer without pretending that hiring activity is a prediction of revenue or purchase intent.
Read the guideAcademic research
Build a paper dataset from three scholarly sources
Choose Crossref, OpenAlex, or PubMed, start with a narrow query, and keep persistent identifiers for evidence.
Read the guideB2B market intelligence
Measure software demand from public job postings
Use explicit tool terms, bounded company samples, and source-linked evidence without claiming a purchase prediction.
Read the guide