Desk Research

Objective: Understand existing solutions and user expectations in server and site analytics.

Analyzed existing products with similar features to understand standard functionalities and user interface layouts.

Interviews

Key Questions

1.How do you typically use analytics dashboards?
2.What are your main challenges with current analytics interfaces?
3.Which features do you find most useful in understanding server and site performance?

Co-relation between Metrics

Analytics users highlighted the importance of correlating server and site metrics as It helps us understand the impact of server performance on user experience and vice versa

User Centric Visualization

"Visualizations should be user-centric. They need to be easy to interpret, customizable to our preferences, and capable of presenting complex data in an understandable way."

Detailed Segmentation

They want to analyze how their server and site performance cross different countries, browsers, and devices. For example, understanding how users from a particular country experience the site or identifying if there are performance variations across different browsers and devices for enhanced trend identification

Mobile Accessibility

Insights

1.Users need a balance between detailed data and summary insights.

2.Customizable dashboards are highly valued for focusing on relevant data.

3.Clear visual indicators for critical issues or alerts are essential.

Brainstorming

Solution

Dashboard:Developed a unified dashboard that consolidates server andsite analytics, addressing the fragmented user experience which is alsocustomizable according to your interest

Correlation Between Metrics:Introduced subpages for site analytics, allowing users tocorrelate data based on various granular parameters like

1.Geographical Considerations (Country):

Research Findings
1.User Experience Variability:
Page load times can vary significantly based on a user's geographical location. Different countries may have varying internet speeds and infrastructure, impacting page load performance.
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2.Regional Content Optimization: Understanding page load and HTTP request metrics by country enables the optimization of content delivery strategies, including the use of content delivery networks (CDNs) tailored to specific regions.

2.URL Grouping

Research Findings:
1.Content Categorization:
Grouping URLs based on certain criteria helps categorize content types, enabling a more granular analysis of page load and HTTP request patterns.
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2.Performance Comparison:
Analyzing URL groups allows for performance comparison between different sections or types of content on the website.

3.Browser Analysis

Research Findings:
1.Browser Compatibility:
Different web browsers may render content differently and have varying performance characteristics. Analyzing page load and HTTP requests by browser helps ensure compatibility and optimal user experience across different platforms.
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2.Browser Market Share:
Understanding the most commonly used browsers provides insights into where development efforts should be focused to cater to the majority of users.

4.Device Type

Research Findings:
1.Mobile vs. Desktop Performance:
Page load times can significantly differ between mobile and desktop devices. Analyzing performance based on device type helps ensure a seamless experience for users on different devices.
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2.Responsive Design Optimization:
Insights into the performance on various devices guide the optimization of responsive design elements to enhance user experience.

5.Connection Type

Research Findings:
1.Mobile Network Considerations:
Users accessing websites through mobile networks may experience different connection speeds. Analyzing page load and HTTP requests based on connection type helps optimize for users on slower connections.
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2.Impact on Resource Loading:
Different connection types (3G,4G, Wi-Fi) can impact how resources, such as images or scripts, are loaded.Understanding these dynamics aids in resource optimization.

6.Industry Practice

Research Findings:
1.Comprehensive Analytics:
Inclusion of these parametersaligns with industry best practices for comprehensive analytics. It allows fora more nuanced understanding of user interactions and website performance.
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2.Informed Decision-Making:
Such detailed analytics empower organizations to make informed decisions regarding content delivery strategies,platform compatibility, and overall website optimization.

Predictive Analytics and Alerts:Implemented predictive analytics features and an intuitivealerting system for proactive issue identification and resolution.

Mobile Responsiveness: Ensured mobile responsiveness to address the need foron-the-go monitoring.

Potential Problems

1.Information overload due to the high volume of data points.
2.Difficulty in navigating between different subpages and understanding the data.
3.Challenges in identifying critical alerts and anomalies amidst the extensive data.

Impact Assessment

Metrics for success

1.User engagement: Time spent on the dashboard and frequency of use.
2.Task completion rate: Efficiency in finding and interpreting data.
3.User feedback: Satisfaction with the interface and features.

Expected Outcomes

Results

The designed monitoring system, informed by insights from interviews and desk research, addresses the identified problems and fulfills the needs expressed by both developers and analytics users.
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The iterative design process, involving regular feedback loops and continuous refinement, ensures that the dashboard remains aligned with evolving user requirements and industry best practices.
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Regular updates and improvements based on user feedback will contribute to the sustained success and effectiveness of the Jio Platforms Analytics Dashboard.