Unified Cross-Platform Performance Metrics

With the fast pace of life today, people expect information to be available to them at the speed of light, regardless of which device or apps they’re using. Through the power of social media, their experiences — both good and bad — are instantly shared with the world, and many of those tweets, comments, and reviews are about apps…

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Slack
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Liang Shi
•14 min read•advanced•
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•View Original
ChefProtocol BuffersSwiftThrift

Overview

The article discusses how Slack unified performance metrics across its Desktop, iOS, and Android applications to enhance user experience and streamline performance tracking. It emphasizes the importance of consistent metrics definitions and the implementation of cross-platform performance indicators to improve app responsiveness and user satisfaction.

What You'll Learn

1

How to implement unified performance metrics across multiple platforms

2

Why consistent performance definitions improve app development

3

When to apply Time to Visible and Time to Usable metrics

Key Questions Answered

What are the benefits of unified cross-platform performance metrics?
Unified cross-platform performance metrics allow for consistent tracking of app performance across different platforms, enabling better business decisions and improved user experience. They help in setting aligned benchmarks and objectives, ensuring that users have a seamless experience regardless of the device they use.
How does Slack measure app launch time?
Slack measures app launch time using two key metrics: Time to Visible (TTV) and Time to Usable (TTU). TTV captures the time taken to display cached content, while TTU measures the time until the most recent content is displayed, reflecting the user experience during app launch.
What challenges did Slack face in implementing cross-platform metrics?
Slack encountered challenges such as platform constraints, different implementations across platforms, and the need for standardized metrics definitions. These issues required extensive collaboration among developers, backend teams, and data analysts to ensure accurate and actionable performance tracking.

Key Statistics & Figures

Percentage of sessions with no cached content on mobile
Less than 1%
This indicates that most mobile users have cached content available, improving their app launch experience.
Percentage of desktop sessions needing to pull content from the server
100%
All desktop sessions require a network request to fetch content, highlighting the difference in caching behavior between platforms.
Percentage of iOS launches triggered by a notification
8%
This statistic helps understand user engagement and how notifications influence app usage on iOS devices.
Percentage of Android launches triggered by a notification
21%
This higher percentage suggests that Android users are more likely to respond to notifications, impacting app launch metrics.

Technologies & Tools

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Backend
Thrift
Used for performance metrics specification to provide a unified and language-neutral interface.
Backend
Protocol Buffers
Explored for better support on Swift in future iterations of performance metrics.

Key Actionable Insights

1
Establish a common vocabulary for performance metrics across platforms to facilitate better communication and understanding among teams.
This is crucial for ensuring that all teams are aligned on performance goals and can effectively collaborate on improvements, ultimately leading to a better user experience.
2
Implement Time to Visible and Time to Usable metrics to accurately gauge user experience during app launches.
These metrics provide insights into how quickly users can access meaningful content, allowing developers to optimize launch processes and improve overall app responsiveness.
3
Regularly review and update performance metrics to adapt to changes in user behavior and technology.
As user expectations evolve and new features are added, it's important to ensure that performance metrics remain relevant and continue to provide valuable insights.

Common Pitfalls

1
Failing to standardize performance metrics across platforms can lead to confusion and misalignment among teams.
When different teams use varying definitions and vocabularies for metrics, it complicates data analysis and can result in incorrect conclusions about app performance.
2
Neglecting to account for special cases in app launch metrics can skew performance data.
Without tracking unique scenarios, such as no cached content or user interventions, the metrics may not accurately reflect the user experience, leading to misguided optimization efforts.

Related Concepts

Cross-platform App Development
Performance Optimization Techniques
User Experience Metrics
Data Analysis In Software Engineering