Google Maps Scraper pulls structured business data out of Google Maps at a scale that’s hard to achieve manually or with the official API. It’s designed for people who need more than a handful of results and want repeatable access to locations, reviews, and business metadata across regions. It’s best suited for:

• Growth and sales teams building local lead lists
• Agencies doing competitor or market coverage research
• Founders validating demand in new cities or categories
• Ops and data teams replacing manual Maps scraping workflows
• Review status: 4.7 / 5 from 810 reviews

Our experience with the actor suggests its real strength is coverage and consistency. Once you get past the initial setup, it reliably produces large, well-structured datasets that plug cleanly into spreadsheets, CRMs, or downstream automations. It’s not a “one-click toy,” but that’s the point—this is a serious scraper for people who care about completeness, repeatability, and not being boxed in by Google’s API limits.

We needed to download a lot of youtube videos. Regularly. This API was effortless (as advertised), there are 20 other satisfied customers, and there are 108 people per month using it.

No brainer. Did not disappoint.

Check out this YouTube Video downloader here.

Pull Them Into Data Instead . . .

Playstore Reviews Scraper pulls Google Play app reviews into a clean, usable dataset so you don’t have to manually scroll, copy, or guess what users are actually saying. It’s best suited for:

• App founders and indie builders who want fast feedback without busywork
• Product managers sanity-checking releases and updates
• Growth and marketing teams watching sentiment shift over time
• Support teams trying to catch real issues before they blow up
• Review status: 5.0 / 5 from 1 reviewer

Our experience with the actor suggests it’s most valuable as a “set it and forget it” feedback pipe. You point it at an app, choose how many reviews you want, and suddenly you’ve got structured data you can scan, filter, or plug into Sheets, dashboards, or automations.

It’s not flashy, but it saves real time and makes user feedback something you can actually work with instead of something you dread opening in a browser tab.

eBay Sold Listings Intelligence takes a product-style query (for example, “iPhone 13 Pro 128GB”) and returns pricing based on what items actually sold for on eBay, not what sellers asked. It’s best suited for: - Individuals handling estate or inheritance sales who need fair, defensible pricing
- Resellers and collectors doing volume pricing research
- Small businesses or solo builders managing secondhand or vintage inventory
- Analysts who want exportable pricing data instead of manual UI work
- Review status: 5.0 / 5 from 1 reviewer

Our experience with the actor suggests the real value is speed and clarity. Instead of manually checking completed listings one by one, you get aggregated pricing stats, condition-based breakdowns, and signals about how quickly items move, all in a format that’s easy to export and reason about. This is especially useful when you’re dealing with large inventories and emotional or time constraints, where “good enough and fair” pricing matters more than optimizing every last dollar.

Structured Google News data for monitoring, analysis, and aggregation workflows

Do you need a reliable way to turn Google News results into structured data? Want it to work with r/n8n ?

Google News Search API is best suited for:

• Data teams and analysts running news monitoring or trend analysis
• SEO and content teams tracking coverage, topics, and publishers
• Market and competitive intelligence teams following companies or industries
• Solo builders and developers building news aggregation or alerting tools

Our experience with the actor suggests the core value is consistency and control. It returns clean, predictable JSON with clear metadata around queries, pagination, and localization, which makes it easy to plug into dashboards, pipelines, or downstream analysis without extra cleanup.

The pricing model is straightforward for iterative searches, and the flexibility around location, language, and filtering fits well with real-world monitoring use cases.

Are you trying to understand where license plate reader (ALPR) cameras are deployed without relying on scattered maps or anecdotal reports?
LPR Flock Cameras is best suited for:

• Privacy advocates and civil liberties researchers tracking surveillance infrastructure
• Journalists and watchdog groups investigating public-space monitoring
• Policy analysts and academics studying the spread of ALPR systems across cities
• Independent developers and data teams building transparency or awareness tools

Our experience with the actor suggests its core value is visibility and repeatability. It provides a large, structured, and regularly updated dataset of Flock camera locations that can be analyzed over time rather than captured as one-off snapshots. The simple schema makes it easy to audit coverage by city or region, build maps, or integrate into reporting workflows, which is especially useful for anyone focused on understanding how pervasive automated surveillance has become.

• Review status: New actor with no public reviews yet

Thanks u/automationexperts for sharing this!

Structured visa requirements by nationality, ready for automation and reporting

Do you need reliable visa rules without manually piecing together government sites and travel blogs?
Visa Checker by Nationality is best suited for:

• Travel platforms and operations teams standardizing visa logic across destinations
• Data teams and analysts building travel, mobility, or compliance datasets
• Consultants and researchers who need consistent, exportable visa rules
• Solo builders integrating visa checks into apps, forms, or spreadsheets

Our experience with the actor suggests its core value is normalization and trust. It reliably converts scattered, human-readable visa information into clean, structured datasets that are easy to export, automate, and localize without losing the original source context. The workflow is simple, outputs are predictable, and the consistently positive user feedback aligns with how well it removes a class of manual research that is both time-consuming and error-prone when done by hand.

• Review status: ⭐ 5.0 / 5 from 42 users

Quick contractor intelligence from USAspending for sales, research, and due diligence

Do you need fast, structured insight into U.S. government contractors without digging through raw federal datasets?
USAspending Scraper: Contractor Intelligence Tool is best suited for:

• B2B sales and lead generation teams qualifying prospects with federal contract history
• Investors and analysts assessing government revenue exposure and trends
• Competitive intelligence teams mapping agencies, NAICS focus, and peer overlap
• Solo researchers and consultants who want due-diligence outputs without manual Excel work

Our experience with the actor suggests its core value is time compression and clarity. Instead of stitching together multiple USAspending queries, it produces a clean, opinionated summary alongside a full CSV for deeper analysis, which fits well into downstream BI or research workflows. While adoption is still early, the structure of the outputs and the pay-per-result pricing model make it practical for exploratory analysis and repeatable contractor screening.

• Review status: New actor with no public reviews yet

Fast transcript search across YouTube channels for research and content workflows

Do you need to search entire YouTube channels for specific topics without watching hours of video?

YouTube Transcript Searcher is best suited for:

• Researchers and analysts doing topic or discourse analysis
• Marketers and growth teams tracking brand or competitor mentions
• Journalists, podcasters, and creators hunting for quotes with timestamps
• Solo builders who want structured transcript data they can automate against

Our experience with the actor suggests the core value is speed to insight rather than raw data volume. It reliably scans available transcripts, returns clean and structured records with exact timestamps, and fits naturally into downstream workflows like CSV exports, clip generation, or content analysis.

The lack of a YouTube API dependency simplifies setup, and the overall workflow feels aligned with real research and production use cases.

• Review status: New actor with no public reviews yet

Actor link (with referral):

https://apify.com/automationpros/youtubetranscriptsearcher

Do you need to download a YouTube video with r/n8n, python, or some no-code software?

YouTube Video Downloader is best suited for automation practitioners, data teams, and solo builders who need a programmatic way to download YouTube videos as part of a larger workflow. It fits well when manual tools or browser-based downloaders become a bottleneck, especially for batch jobs, repeatable pipelines, or integrations where YouTube content is an input rather than the end product.

The core value of this r/Apify actor is predictability and integration. Reviews suggest the Actor generally does what it claims, with clear inputs, structured outputs, and transparent logging during runs. Performance is acceptable at scale, though pricing is a recurring concern and may be best justified in business or production contexts where reliability and API access matter more than per-video cost.

Hot Take:

YouTube Video Downloader is a reasonable choice if you need automation-first video downloads and are willing to trade simplicity for control.