Read Yelp reviews as a source-linked corpus. Start with Yelp review or listing URLs; each returned review keeps review identifiers, author display names, text, and review URL.
2
Users / 30d
29
Runs / 30d
—
Rating
Updated 1 Oct 2026
Apify builder
@reapx
Leaderboard position
out of 6,984
New Actors / 30d
#5628
Total Actors
#76
Active users / 30d
#298
Total users
#706
Runs / 30d
#484
Total runs
#221
Portfolio stats
New Actors / 30d
0
Total Actors
196
Active users / 30d
231
+31 since first snapshot
Total users
458
Runs / 30d
6K
+2.6K since first snapshot
Total runs
409.7K
Portfolio history
Daily publishing
0
Each bar represents one UTC day.
No new public Actors were detected during this 30-day window.
Actor portfolio
196 matching of 196 Actors · page 2 of 9
Read Yelp reviews as a source-linked corpus. Start with Yelp review or listing URLs; each returned review keeps review identifiers, author display names, text, and review URL.
2
Users / 30d
29
Runs / 30d
—
Rating
Map YouTube audiences for account research. Start with YouTube follower URLs; each returned follower keeps follower list available, names, subscriber count, search term, and channel identifiers.
2
Users / 30d
29
Runs / 30d
Collect published contact emails from Instagram. Start with Instagram page URLs; each returned email record keeps public email, public email field, handles, names, and phone numbers.
2
Users / 30d
33
Runs / 30d
Follow an Instagram hashtag across the posts and accounts using it. Keep captions, creators, dates, media, engagement, and source links in the order returned.
2
Users / 30d
31
Runs / 30d
Keep TikTok search results in rows you can compare. Start with search terms, TikTok searches or result URLs, and result count; each returned search result keeps search term, author handles, author nickname, music author, and author identifiers.
2
Users / 30d
30
Runs / 30d
Keep YouTube channels and published videos in one searchable export. Review identity, titles, dates, descriptions, audience signals, engagement, and source links together.
2
Users / 30d
28
Runs / 30d
Read Facebook reviews as a source-linked corpus. Start with Facebook review or listing URLs; each returned review keeps total reviews, reviews, recommend percent, and source links.
1
Users / 30d
27
Runs / 30d
Read LinkedIn publishing activity from exact post URLs. Keep the author, text, publication time, company context, and source link attached to each post.
1
Users / 30d
31
Runs / 30d
Keep Telegram search results in rows you can compare. Start with Telegram searches or result URLs; each returned search result keeps titles, authors, descriptions, position, and seller details.
1
Users / 30d
33
Runs / 30d
Keep Instagram reels as comparable video records. Review creator, caption, publication time, plays, likes, comments, media, and source link across a saved URL list.
1
Users / 30d
33
Runs / 30d
Build a lead file from Instagram. Start with Instagram page URLs; each returned lead keeps names, public email, public email field, phone numbers, and is business account.
1
Users / 30d
30
Runs / 30d
Build a clean file of LinkedIn people from profile URLs, public identifiers, or searches. Keep names, roles, employers, locations, audience size, experience, and education together for prospecting and company research.
1
Users / 30d
38
Runs / 30d
Compare MercadoLibre products, offers, and identifiers. Start with MercadoLibre product URLs; each returned product keeps product identifiers, titles, prices, currencies, and condition.
1
Users / 30d
39
Runs / 30d
Compare Airbnb listings, stays, and market signals. Start with Airbnb URLs; each returned record keeps price qualifier, address locality, titles, prices, and ratings.
1
Users / 30d
28
Runs / 30d
Compare returned Airbnb prices. Start with Airbnb product or listing URLs; each returned price record keeps price qualifier, price status, prices, price string, and titles.
1
Users / 30d
28
Runs / 30d
Read Airbnb reviews as a source-linked corpus. Start with Airbnb review or listing URLs and reviews per listing; each returned review keeps review volume, review identifiers, review source, review status, and author names.
1
Users / 30d
28
Runs / 30d
Compare live listings on AliExpress. Start with AliExpress listing URLs; each returned listing keeps titles, prices, original price, ratings, and review volume.
1
Users / 30d
28
Runs / 30d
Compare returned AliExpress ratings. Start with AliExpress product or listing URLs; each returned rating keeps ratings, titles, review volume, orders count, and product identifiers.
1
Users / 30d
28
Runs / 30d
Read AliExpress reviews as a source-linked corpus. Start with AliExpress review or listing URLs; each returned review keeps reviewer country, review identifiers, reviewer names, product review total, and date.
1
Users / 30d
28
Runs / 30d
Keep AliExpress search results in rows you can compare. Start with AliExpress searches or result URLs; each returned search result keeps titles, prices, original price, discount percent, and orders count.
1
Users / 30d
28
Runs / 30d
Build a lead file from Amazon. Start with Amazon page URLs; each returned lead keeps names, email addresses, titles, companies, and domain.
1
Users / 30d
28
Runs / 30d
Take a working snapshot of Amazon products and offers. Start with Amazon URLs; each returned record keeps titles, authors, prices, ratings, and review volume.
1
Users / 30d
28
Runs / 30d
Compare returned Amazon ratings. Start with Amazon product or listing URLs; each returned rating keeps ratings, titles, authors, prices, and review volume.
1
Users / 30d
28
Runs / 30d
Read Amazon reviews as a source-linked corpus. Keep rating, title, text, author, date, helpful votes, review identity, and source link together.
1
Users / 30d
28
Runs / 30d
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