🆚 Gainsight vs. Shepherd

Type

Digital adoption platform
Digital adoption platform

About

Gainsight is a customer success platform that helps businesses analyze churn risk, improve customer retention, manage renewals, and measure customer lifecycle performance.

The platform provides customer health scoring, onboarding and renewal workflows, product usage analytics, journey orchestration, survey collection, and revenue forecasting tools.

Read more…

Shepherd is an open-source, fully featured, digital adoption platform (DAP) and user on-boarding service.

Headquarters

San Francisco, California, United States
Middleburg, Virginia, United States

Website

Pricing

Free version ❌
$10,000+/year
Free version ✔️ Versions older than v14.0.0 or for open-source, personal and non-commercial sites, open source
Business (5 projects) $50
Enterprise (unlimited projects) $300

Categories

Digital Adoption › Rank #2
Digital Adoption › Rank #6
JavaScript Libraries › Rank #252

Popularity

Determined by the number of sites using each technology.

The Gainsight digital adoption platform is 2.5 times more popular than Shepherd.
Total websites

Market share

Digital Adoption

Popularity by country

Determined by the number of sites detected from each country.

Gainsight is more popular in the United States, the United Kingdom, and Norway, while Shepherd is more popular in France, Brazil, and Russia.
United States
United Kingdom
Norway
Australia
Canada
Sweden
Germany
Spain
Finland
Netherlands

Awards

Popularity by domain category

Determined by the number of sites in each category.

Gainsight is more popular among sites focused on business, education and reference, and health, while Shepherd is more commonly used on religion and ideology, blogs and wiki, and forum, bulletin boards sites.
Business
Education/Reference
Health
Marketing/Merchandising
Non-Profit/Advocacy/NGO
Online Shopping
Sports
Recreation/Hobbies
Travel
Finance/Banking

Top sites

Top-ranked sites that use these technologies.

Name
Rank
#12,040
#14,283
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Name
Rank
View more ➝

See also

🗃️ About This Data