ReapX

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.

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.

Compare live listings on AliExpress. Start with AliExpress listing URLs; each returned listing keeps titles, prices, original price, ratings, and review volume.

Compare AliExpress products, offers, and identifiers. Start with AliExpress product URLs; each returned product keeps product identifiers, titles, prices, original price, and ratings.

Compare returned AliExpress ratings. Start with AliExpress product or listing URLs; each returned rating keeps ratings, titles, review volume, orders count, and product identifiers.

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.

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.

Build a lead file from Amazon. Start with Amazon page URLs; each returned lead keeps names, email addresses, titles, companies, and domain.

Take a working snapshot of Amazon products and offers. Start with Amazon URLs; each returned record keeps titles, authors, prices, ratings, and review volume.

Compare returned Amazon ratings. Start with Amazon product or listing URLs; each returned rating keeps ratings, titles, authors, prices, and review volume.

Read Amazon reviews as a source-linked corpus. Keep rating, title, text, author, date, helpful votes, review identity, and source link together.

Keep Amazon search results in rows you can compare. Start with Amazon searches or result URLs; each returned search result keeps titles, prices, names, list price, and descriptions.

Compare returned Booking prices. Start with Booking product or listing URLs; each returned price record keeps price user currency, price hotel currency, price user unformatted, price hotel unformatted, and offer identifiers.

Read Booking reviews as a source-linked corpus. Start with Booking review or listing URLs; each returned review keeps overall reviews count, review identifiers, reviewed at, author names, and author country code.

Compare Booking listings, stays, and travel-market facts. Start with Booking URLs; each returned record keeps country code, property names, property identifiers, latitude, and longitude.

Compare live listings on eBay. Start with eBay listing URLs; each returned listing keeps listing identifiers, titles, prices, price text, and price type.

Take a working snapshot of eBay listings and offers. Start with eBay URLs; each returned record keeps titles, authors, prices, descriptions, and publication dates.

Compare returned eBay prices. Start with eBay product or listing URLs; each returned price record keeps prices, titles, price string, list price string, and ratings.

Compare eBay products, offers, and identifiers. Start with eBay product URLs; each returned product keeps titles, prices, ratings, review volume, and currencies.

Read Facebook comment threads as a corpus. Start with Facebook post or video URLs; each returned comment keeps comment, text, authors, handles, and publication dates.

Compare company records from Facebook. Start with Facebook company URLs; each returned company keeps email addresses, phone numbers, audience size, page names, and websites.

Build a contact file from Facebook. Start with Facebook page URLs; each returned contact keeps email addresses, phone numbers, audience size, page names, and websites.

Collect Facebook page records with names, audience counts, page identifiers, and source links. Start with Facebook URLs; each returned record keeps names, audience size, page identifiers, source links, and followers label.

Collect published contact emails from Facebook. Start with Facebook page URLs; each returned email record keeps email addresses, phone numbers, audience size, page names, and websites.