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Panelbear

Panelbear helps you understand and grow your website, so you can deliver an amazing experience to your visitors.
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What is Panelbear?

Panelbear is a simple website performance and traffic analytics tool. Focus on what matters. Say goodbye to thousands of useless reports, the overview dashboard gives you an eagle's eye view on your website's most important metrics.
Panelbear is a tool in the General Analytics category of a tech stack.

Who uses Panelbear?

Panelbear Integrations

JavaScript, Python, Node.js, React, and HTML5 are some of the popular tools that integrate with Panelbear. Here's a list of all 18 tools that integrate with Panelbear.

Panelbear's Features

  • Focused metrics
  • Real-time data
  • Cookieless analytics
  • Performance monitoring
  • Filter and compare metrics
  • Blazingly fast

Panelbear Alternatives & Comparisons

What are some alternatives to Panelbear?
Google Analytics
Google Analytics lets you measure your advertising ROI as well as track your Flash, video, and social networking sites and applications.
Matomo
It is a web analytics platform designed to give you the conclusive insights with our complete range of features. You can also evaluate the full user-experience of your visitor’s behaviour with its Conversion Optimization features, including Heatmaps, Sessions Recordings, Funnels, Goals, Form Analytics and A/B Testing.
Piwik
Matomo (formerly Piwik) is a full-featured PHP MySQL software program that you download and install on your own webserver. At the end of the five-minute installation process, you will be given a JavaScript code.
Clicky
Clicky Web Analytics gives bloggers and smaller web sites a more personal understanding of their visitors. Clicky has various features that helps stand it apart from the competition specifically Spy and RSS feeds that allow web site owners to get live information about their visitors.
Databricks
Databricks Unified Analytics Platform, from the original creators of Apache Sparkâ„¢, unifies data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications.
See all alternatives
Related Comparisons
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