Hey, fellow scrapers! 👋

I’ve been working on a data pipeline for the MENA region and just published our first major Actor: Avito Maroc Scraper. Avito is the absolute giant of classifieds in Morocco (cars, real estate, electronics, jobs), but their UI structure updates frequently, making traditional CSS selectors a nightmare to maintain.

The Technical Approach: Instead of fighting the DOM, I built this scraper to strictly intercept the underlying NEXT_DATA JSON payloads.

• Zero CSS Reliance: If the data is on the page, the actor gets it directly from the backend state. It’s incredibly stable.
• Dynamic Attribute Parsing: Avito has vastly different attributes per category (e.g., Mileage and Transmission for cars vs. Rooms and Square Meters for apartments). The actor dynamically maps these into clean, structured JSON objects.
• HD Images: It bypasses the compressed UI thumbnails and extracts the full high-res image URLs.

AI-Ready Output: I specifically designed the output to be ingested into LLM context windows and RAG pipelines. It spits out pristine, standardized JSON that you can immediately pipe into your vector databases or autonomous agents.

Quick Note on Proxies: Avito has some pretty aggressive anti-bot protection. While datacenter proxies might work for tiny runs, you really need Apify Residential Proxies if you want to scale this for thousands of items.

👇 How to get started:

Don't want to deal with code or infrastructure? You can run it directly from the cloud and download the data in Excel/CSV/JSON. Just paste an Avito link and click start: 👉 https://apify.com/scraper_guru/avito-maroc-scraper

I’m on a mission to build out the "Data Mine" for the MENA region. I'd love your feedback!

A lot of outbound workflows start too late.

By the time a rep notices that a company launched something new, expanded a product line, published a newsroom update, or announced a hiring push, the signal is already cold.

So I built Apollo News Signal Monitor on Apify.

It monitors company RSS feeds, blogs, and newsroom pages, filters for relevant updates, deduplicates them across runs, and turns them into review-ready Apollo actions. Depending on the mode, it can:

detect signals only

create review tasks

prepare sequence actions

support human review before anything is pushed

It also extracts clean fields like title, URL, publish date, summary, snippet, relevance score, outreach angle, and suggested first line. There is also an optional AI mode, but it still works with deterministic fallback logic if AI is disabled.

A few things I wanted to solve with it:

- Apollo is strong for execution, but not really built as an external signal monitoring layer for public feeds and newsroom pages.

- Most “signal-based outreach” setups still require too much manual checking

- A lot of useful company intent is hiding in RSS, blog posts, and news pages, but teams do not operationalize it well

The actor currently supports:

- RSS / Atom / blog / newsroom monitoring

- auto-discovery of feed URLs when possible

- HTML fallback when no feed exists

- dedupe state so the same signal is not processed twice

- keyword-based relevance scoring

- Apollo task / sequence / review workflows

- dataset + SUMMARY output for downstream automation

Example use case: Track target accounts like OpenAI, Anthropic, Stripe, or vertical-specific companies, then route only meaningful updates into Apollo so reps have a timely reason to reach out. The README example on the actor page uses exactly that kind of setup.

Would love feedback from people doing:

- signal-based outbound

- Apollo automation

- sales workflows in n8n / Zapier / custom stacks

- account monitoring for SDR teams

Actor: https://apify.com/solutionssmart/apollo-news-signal-monitor

Still guessing hashtags on TikTok? That’s why your reach is stuck.

This tool pulls real-time trending hashtags directly from TikTok Creative Center — so you can catch trends early instead of copying them late.

👉 https://apify.com/akash9078/tiktok-trending-hashtags-scraper

🔥 What you get:
• Top 100 trending hashtags
• Views, post count & engagement data
• Trend movement (rising/falling)
• Filters by country, niche & timeframe

💡 Perfect for:
Creators • Marketers • Agencies • Builders

Most people use hashtags after they go viral.
This helps you use them while they’re going viral.

That’s the difference between:
500 views vs 500K views.

⚡ Bonus:
• API ready (plug into automations)
• Clean JSON output
• Super low cost to run

If you’re serious about TikTok growth, this saves hours of manual research.

Try it 👇
https://apify.com/akash9078/tiktok-trending-hashtags-scraper

Salut tout le monde,

Je vous partage un petit projet que j'ai sorti y'a pas longtemps. A la base je suis pas un gros dev, je suis surtout un reseller Vinted qui galèrais pas mal à chopper les bonnes affaires avant tout le monde.

J'ai un peu tout essayé pour automatiser mes recherches et mes alertes. J'ai même payé des abos sur des bots connus comme Monitorius etc. Attention c'est des bons outils, mais franchement, devoir se retaper toute la configuration des filtres à la main sur leur interface pour chaque petite recherche, ça m'a vite pris la tête. En plus desfois c'était pas super flexible quand tu cherches des trucs ultra niches.

Du coup vu que je bidouille un peu, je me suis penché sur Apify. Mon idée c'était d'avoir un outil le plus simple et bête possible : tu fais ta recherche normalement direct sur le site Vinted avec tes filtres précis (marque, taille, prix, état...), tu copies l'URL, tu la colle dans le scraper et paf, il te sort toute la data au propre (JSON/CSV) avec les prix, les vendeurs et les photos HD. Zéro config à faire.

J'ai réussi à faire un truc qui tourne super bien, je l'ai appelé Vinted Turbo Scraper.

C'est hyper pratique pour ceux qui veulent faire du batching de masse ou monitorer des liens précis sans se prendre la tête avec les paramètres.

Je vous met le lien ici. Avec les 5$ de crédits gratuits que donne Apify par mois, y'a largement de quoi scraper des milliers d'articles gratos pour tester.

Lien :https://apify.com/kazkn/vinted-turbo-scraper

Hésitez pas si vous avez des questions ou des retours. Je prend tout vos avis ou critiques pour l'améliorer !

Hey Guys! 👋

Following up on my last post about the Channel Scraper, I want to share another tool we just published to help you extract YouTube data at scale without wrestling with quotas.

If you’ve ever built a YouTube search scraper using the official YouTube Data API, you know the headaches: managing API keys, handling complex pagination, and having to make separate API calls just to get the actual video stats (views, likes, comments) and channel details.

To solve this, I built the YouTube Search API Actor.

It provides a simple interface to scrape YouTube search results with comprehensive metadata, automatically combining multiple API endpoints into one clean dataset.

🚀 Why use this over the direct YouTube Data API?

• No API Key Required: It authenticates via an external token server, meaning zero quota management on your end.
• Auto-Pagination: It handles pagination behind the scenes to fetch up to 1,000 video results in a single run.
• Combined Endpoints: Instead of just getting search results, it automatically fetches full video statistics AND channel statistics at the same time.
• Clean Data: Automatically decodes HTML entities in titles/descriptions and extracts hashtags into a clean array.

🎛️ Advanced Search Filters

You aren't just limited to basic keyword searches. The Actor supports all the advanced filtering options you need to get highly targeted datasets:

• Sort/Order: By Date, Rating, Relevance, Title, Video Count, or View Count
• Date Range: Filter by publishedAfter and publishedBefore (RFC 3339 format)
• Location & Language: Set specific regionCode (e.g., US) and relevanceLanguage
• Video Specifics: Filter by Duration (short, medium, long), Definition (HD/Standard), and License (Creative Commons/YouTube).
• Live/Events: Search for Live, Upcoming, or Completed broadcasts.

📋 What does the output look like?

You get a rich, structured dataset (exportable as JSON, CSV, Excel, etc.) that includes video metrics, channel metrics, and extracted keywords.

JSON

{
  "title": "Video Title",
  "id": "VIDEO_ID",
  "url": "https://www.youtube.com/watch?v=VIDEO_ID",
  "text": "Video description...",
  "viewCount": 10000,
  "likes": 1000,
  "commentsCount": 100,
  "duration": 180,
  "date": "2023-01-01T00:00:00Z",
  "hashtags": ["hashtag1", "hashtag2"],
  "keywords": ["keyword1", "keyword2"],
  "channelName": "Channel Name",
  "channelUsername": "username",
  "numberOfSubscribers": 1000000,
  "channelViewCount": 50000000,
  "channelVideoCount": 500
}

🔗 Try it out & Build Your Stack

👉Get the YouTube Search API Actor Here

Note: This Actor currently focuses exclusively on video search results (not playlists or standalone channels in the search feed).

If you are building a complete content analysis pipeline, this pairs perfectly with our other tools:

• YouTube Channel Scraper(For deep-diving into specific competitors)

Let me know what you think! If you have any feature requests (like adding playlist search support) or find any bugs, drop a comment below or open an issue on the Apify platform.

Happy scraping! 🕷️