Which Scraper Should You Use? A Guide to My Actors and Extensions

You need one export, but the tool list includes a browser extension, a discovery scraper, a single-record lookup, and an analysis actor. They may touch the same platform while solving different parts of the work.

I build these tools around specific tasks. This guide maps my public actor catalog and listed browser extensions to those tasks, then points to a practical starting workflow.

I maintain the tools linked here. This is a portfolio guide, rather than an independent ranking of competing vendors. Catalog availability, pricing, and input contracts can change; the linked product documentation is the place to confirm a run's settings.

First choose where the work should happen

Use a Chrome extension when you are already reviewing a page and want an interactive local workflow. Use an Apify actor when you need saved inputs, API calls, scheduled runs, or a dataset for another system.

That distinction helps with setup. It does not guarantee identical coverage between a browser capture and a cloud run. Test the exact source and fields you need.

Find and analyze competitor ads

Start with the identifier you have. A brand name calls for discovery. A known ad ID calls for lookup. A collected creative calls for analysis.

For a first project, export a small Meta sample, tag its offers, then check selected ad IDs over time. Use the LinkedIn research guide for a B2B message map or the creative analysis guide once you have usable assets.

Public ad records help you study messaging. They cannot establish a competitor's conversions or profitability. Keep your interpretations separate from the source fields.

Export community and profile research

For Facebook, choose between the cloud collection guide and a local browser export. A known post lookup is a narrower operation than feed discovery.

For Reddit, read the browser-versus-archive comparison. The previous reddit-scraper actor is deprecated. The replacement is archive-based and does not provide global keyword search, direct-thread extraction, or guaranteed current coverage. Inspect availability before starting a job.

Keep source references and record the sample boundaries. Public-profile extraction also depends on which fields the source actually exposes; no-login access does not guarantee a complete profile.

Research reviews, products, jobs, and demand

These datasets have different meanings. A public availability flag is not stock quantity. A displayed sold price is not a verified net transaction amount. A job listing is not proof of a completed hire.

Google Trends is relative interest data, normalized within the requested context, rather than an absolute search-volume count. Google's Trends data FAQ explains that distinction. Keep batch context attached to exported values.

Choose a focused browser extension

EaseMyLink remains documented as a closed project on the portfolio. It is not an active recommendation for a new workflow.

Catalog Prep is now available alongside the Shopify actor. Use the extension-versus-API guide for local capture or scheduled collection, and the export comparison when evaluating alternatives.

Design the deliverable before expanding collection

Choose one output: an ad message map, a community research memo, a review issue list, or a validated catalog worksheet. Name the source fields and analysis fields separately.

Run a small sample, compare a few records with the source, and preserve the coverage report. Then increase the scope only when you can explain what the output includes and what remains unknown.

The scrapers page and project directory provide the portfolio overview. For a repeatable team process, continue with the agency workflow.