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23Q4
23Q4
  • GovStack
  • Contributing
  • Architecture and Nonfunctional Requirements
    • 2 Introduction
    • 3 GovStack Architecture
    • 4 Building Block Design Principles and Considerations
    • 5 Cross-Cutting Requirements
    • 6 Onboarding Products
    • 7 Standards
    • 8 UX Switching and Handover
    • 9 Other Resources
  • Security Requirements
    • 2 Description
    • 3 Terminology
    • 4 Security Management
    • 5 Cross-Cutting Requirements
    • 6 Standards
    • 7 Authorization Services
    • 8 Additional Security Modules
    • 9 Other Resources
  • GovStack UI/UX Guidelines
    • 1 Version History
    • 2 Description
    • 3 Service design good practice guidelines
      • 3.1 User-centred design
        • 3.1.1.1 Understand needs and requirements
        • 3.1.1.2 Involve others in the design process
        • 3.1.2.1 Test with users
        • 3.1.3.1 Share findings
        • 3.1.3.2 Monitor performance
          • 3.1.3.3 Set up analytics
      • 3.2 Accessibility and inclusion
        • 3.2.1.1 Test for accessibility
        • 3.2.2.1 Involve a diverse user group in the design
        • 3.2.2.2 Support multiple languages
        • 3.2.2.3 Foster a culture of inclusion
      • 3.3 Consistency
        • 3.3.1.1 Use simple language
        • 3.3.2.1 Implement a consistent style guide
        • 3.3.2.2 Use design patterns
        • 3.3.2.3 Use a frontend framework
        • 3.3.3.1 Interoperability
        • 3.3.3.2 Use integrations
        • 3.3.4.1 Work in the open
      • 3.4 Technology choices
        • 3.4.1.1 Choose the right level of security
        • 3.4.1.2 Design for privacy
        • 3.4.2.1 Optimise load times
        • 3.4.2.2 Account for connectivity issues
        • 3.4.3.1 Test across platforms
        • 3.4.3.2 Design cross-channel
    • 4 Design patterns
      • 4.1 Service patterns
      • 4.2 User flows
        • 4.2.1 Register
        • 4.2.2 Authenticate
        • 4.2.3 Asking users for feedback
        • 4.2.4 Find a service
        • 4.2.5 Check a users eligibility
        • 4.2.6 Make an application
      • 4.3 Page templates
        • 4.3.1 Feedback
        • 4.3.2 Perception survey
        • 4.3.3 Satisfaction
        • 4.3.4 Before you start
        • 4.3.5 Service sheet
        • 4.3.6 Asking users for consent
        • 4.3.7 Task list
        • 4.3.8 Asking users for information
        • 4.3.9 Check answers
        • 4.3.10 Outcome
    • 5 Use-case examples
    • 6 References
    • 7 Other Resources
  • Building Blocks
    • About Building Blocks
    • Consent
    • Digital Registries
    • E-Marketplace
    • E-Signature
    • Geographic Information System (GIS)
    • Identity
    • Information Mediation
    • Messaging
    • Payments
    • Registration
    • Scheduler
    • Workflow
  • Cloud Infrastructure
  • Use Cases
    • Reference Use Cases
  • Public Administration Ecosystem Reference Architecture (PAERA)
    • PAERA
  • Tools
    • Sandbox
  • Release Notes
    • 23Q4
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On this page
  • 1. Cloud-Based Analytics
  • 2. Self-Hosted Analytics
  • 3. Start with cloud

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  1. GovStack UI/UX Guidelines
  2. 3 Service design good practice guidelines
  3. 3.1 User-centred design
  4. 3.1.3.2 Monitor performance

3.1.3.3 Set up analytics

1. Cloud-Based Analytics

The cloud-based analytics solution, such as Google Analytics, is a straightforward and easy-to-setup method that offers robust data about your users' behavior. It's a beneficial choice for those who want to get started quickly and without much technical setup.

Setup: Begin by creating an account on the platform of your choice. You will then add the tracking code they provide to your website. Ensure this code is embedded on each page you wish to monitor.

Configuration: Within the platform, you'll set up goals or events that align with your Key Performance Indicators (KPIs). This allows the software to track specific user actions that are of interest to your business.

Monitoring: Once the setup is complete, you can start monitoring user behavior data through the platform's dashboard.

Remember to respect user privacy throughout this process, which involves informing users about the data you collect, why you collect it, and offering an option to opt out.

2. Self-Hosted Analytics

Self-hosted analytics, such as open-source platforms like Matomo or Plausible, offer more control over your data and are often favored by businesses that place a high emphasis on data privacy and security. This is particularly important if you value keeping data in-country due to regulatory or compliance requirements.

Setup: You'll need to set up these platforms on a server, which could be owned by you or rented from a hosting provider. After this, you'll add the platform-specific tracking code to your website.

Configuration: As with cloud-based solutions, you will need to define the events or goals that align with your KPIs.

Monitoring: Once configured, you can use the platform's dashboard to track user behavior and monitor your KPIs.

Server space considerations for self-hosting depend on several factors, including the amount of traffic your website receives and the level of detail in the data you are tracking. As a starting point, 1GB of space could handle over a million simple page views, but more complex tracking would reduce this. Consulting with a server or IT professional could provide a more accurate estimate based on your specific needs.

3. Start with cloud

It is also possible to start with a cloud-based solution for quick setup and immediate insights, then transition to a self-hosted solution as it's being set up. This allows you to benefit from analytics data right away, while your more robust, privacy-centric solution is being prepared.

Last updated 1 year ago

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