Websites Using Qgiv

Qgiv is an online fundraising platform helping nonprofit, faith-based, healthcare, and education organisations raise funds.

Categories: Performance monitoring

Official website: https://www.qgiv.com

30 websites using Qgiv

• sonoran.edu
• upwardaz.org
• flyfishersinternational.org
• leslielohman.org
• mt-washington.com
• humanebroward.com
• mds-foundation.org
• thefridacinema.org
• midway.edu
• gsutigers.com
• ichelp.org
• globalwildlife.org
• kaweahhealth.org
• marine-conservation.org
• contemporaryartscenter.org
• theodorepayne.org
• ataxia.org
• elijahlist.com
• mightyearth.org
• uofmhealthsparrow.org
• ncpc.org
• occc.edu
• rabbitroom.com
• concord.org
• nuclearmuseum.org
• lupus.org
• museumofplay.org
• bloomerang.co
• qgiv.com
• canadiangeographic.ca

Qgiv is ranked #48 of 61 in Performance monitoring by website adoption.

Performance monitoring alternatives ranked by popularity

1. New Relic — 4,481 websites
2. StatusCake — 1,173 websites
3. Dynatrace — 1,001 websites
4. Datadog RUM — 710 websites
5. StatusPage — 451 websites
6. AWS CloudWatch RUM — 0 websites
7. ActBlue — 0 websites
8. AlumnIQ — 0 websites
9. AppDynamics — 0 websites
10. Arreva — 0 websites

Technologies commonly used with Qgiv

• Open Graph — 80% co-occurrence
• PHP — 77% co-occurrence
• WordPress — 57% co-occurrence
• Google Tag Manager — 57% co-occurrence
• Google Analytics — 57% co-occurrence
• MySQL — 57% co-occurrence
• Schema.org — 57% co-occurrence
• Font Awesome — 57% co-occurrence

How WhatStack detects Qgiv

WhatStack detects Qgiv 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 Qgiv?

Qgiv is an online fundraising platform helping nonprofit, faith-based, healthcare, and education organisations raise funds.

How many websites use Qgiv?

WhatStack has detected Qgiv on 30 websites in our database.

How do you detect Qgiv?

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