Websites Using Cackle

Cackle is a cloud services platform for increasing conversion using comments, feedback collection, online consultant and surveys.

Categories: Comment system

Official website: https://cackle.me

32 websites using Cackle

• bloknot-zaporozhie.ru
• radioiskatel.ru
• getvideo.org
• italy4.me
• oteatre.info
• synthesit.ru
• e-champs.com
• sochi-bloknot.ru
• billionnews.ru
• volleybolist.ru
• kuda-spb.ru
• bloknot-moldova.ru
• saratov24.tv
• bloknotanapa.ru
• wot-leader.net
• popadiv10.ru
• bloknot-taganrog.ru
• kudamoscow.ru
• pnevmat24.ru
• bloknot-volzhsky.ru
• afanasy.biz
• bloknot-stavropol.ru
• bloknot-volgodonsk.ru
• envybox.io
• pluggedin.ru
• oka.fm
• bloknot.ru
• uainfo.org
• azh.kz
• overclockers.ru
• astral.ru
• film.ru

Cackle is ranked #4 of 20 in Comment system by website adoption.

Comment system alternatives ranked by popularity

1. Facebook Comments — 8,373 websites
2. Disqus — 1,789 websites
3. Annoto — 0 websites
4. Chirpy — 0 websites
5. Commento — 0 websites
6. Coral — 0 websites
7. Cove — 0 websites
8. Cusdis — 0 websites
9. Giscus — 0 websites
10. GraphComment — 0 websites

Technologies commonly used with Cackle

• PHP — 91% co-occurrence
• Yandex Metrica — 91% co-occurrence
• jQuery — 69% co-occurrence
• Nginx — 59% co-occurrence
• Liveinternet — 59% co-occurrence
• Open Graph — 56% co-occurrence
• FancyBox — 50% co-occurrence
• Google AdSense — 47% co-occurrence

How WhatStack detects Cackle

WhatStack detects Cackle by analyzing HTTP headers, HTML source code, JavaScript globals, meta tags, cookies, DNS records, and ads.txt entries using signature-based pattern matching across 10 different analyzers.

Frequently Asked Questions

What is Cackle?

Cackle is a cloud services platform for increasing conversion using comments, feedback collection, online consultant and surveys.

How many websites use Cackle?

WhatStack has detected Cackle on 32 websites in our database.

How do you detect Cackle?

We analyze HTTP headers, HTML source, JavaScript globals, meta tags, cookies, DNS records, and ads.txt entries to identify Cackle with high accuracy using signature-based pattern matching.