Need advice about which tool to choose?Ask the StackShare community!
Fathom Analytics vs Google Analytics: What are the differences?
Fathom Analytics: Simple, open source website analytics library. Fathom tracks users on a website (without collecting personal data) and give you a non-nerdy breakdown of your top content and top referrers. It does so with user-centric rights and privacy, and without selling, sharing or giving away the data you collect. It's a simple and easy to use for website owners at any technical level; Google Analytics: Enterprise-class web analytics. Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications.
Fathom Analytics and Google Analytics can be categorized as "General Analytics" tools.
Fathom Analytics is an open source tool with 5.59K GitHub stars and 226 GitHub forks. Here's a link to Fathom Analytics's open source repository on GitHub.
We have integrated Panelbear on our Website, rather than Google Analytics, because it is way more respecting of the User's Privacy. Whilst Google Analytics gives us in-depth information on virtually everything, we don't even need that much. Panelbear keeps it simple and in addition to that, displays the data well structured in a simple and intuitive dashboard
Pros of Fathom Analytics
- Self hosted2
- Privacy friendly1
Pros of Google Analytics
- Free1.5K
- Easy setup926
- Data visualization890
- Real-time stats698
- Comprehensive feature set405
- Goals tracking181
- Powerful funnel conversion reporting154
- Customizable reports138
- Custom events try83
- Elastic api53
- Updated regulary14
- Interactive Documentation8
- Google play3
- Industry Standard2
- Advanced ecommerce2
- Walkman music video playlist2
- Medium / Channel data split1
- Irina1
- Financial Management Challenges -2015h1
- Lifesaver1
- Easy to integrate1
Sign up to add or upvote prosMake informed product decisions
Cons of Fathom Analytics
Cons of Google Analytics
- Confusing UX/UI11
- Super complex8
- Very hard to build out funnels6
- Poor web performance metrics4
- Very easy to confuse the user of the analytics3
- Time spent on page isn't accurate out of the box2