Skip to main content

Typical Scenarios

Request Analysis Scenario​

In most cases, network time consumption and availability remain the standard for measuring user experience quality.

  • Excessively long response times greatly reduce customer tolerance, and the availability of critical payment interfaces directly affects GMV (Gross Merchandise Volume). In some cases, extremely long response times are often caused by slow backend responses.

  • During usage, users may experience various network errors due to network congestion or weak network environments, which often cannot be collected through server-side logs. Network errors that trouble operations personnel are often closely related to client-side environments.

CDN Quality Analysis Scenario​

As of November 2019, the number of CDN license holders issued by the Ministry of Industry and Information Technology has reached 579. Traditional CDN vendors and cloud service providers are all entering this field, with industry competition continuing to intensify. Since the CDN acceleration effect itself is not transparent, after adopting CDN acceleration services, how effective the vendor's allocation strategy actually is, whether it can reach the level during testing, and whether there is still room for optimization—for mobile applications, all of these lack effective monitoring means.

"Mobile CDN Analysis" automatically identifies various CDN vendors based on real user usage scenarios and comprehensively evaluates CDN quality by monitoring CDN vendors' response time, transmission rate, and availability. It also provides visualization report analysis to assist operations personnel in understanding the distribution strategies and acceleration effects of various CDN vendors.

User Perception Analysis Scenario​

In the digital era, as business scale gradually increases, applications carry increasingly complex business logic, and corresponding performance issues are also growing: application crashes, freezes, network delays, image loading failures, and other performance issues are like stubborn diseases that are difficult to eliminate. Various problems caused by performance directly affect business conversion rates and brand favorability.

Existing user experience optimization solutions no longer simply deal with the highest proportion of crashes and resolve the most numerous errors as in the past, but rather prioritize fixing bugs that most affect user experience in a targeted manner to improve user retention.

Mobile monitors three core scenarios: application launch, page display, and user operations, comprehensively analyzing "launch time," "first screen loading," and "user operation" metrics during application use from a business perspective, covering the entire application lifecycle, thereby comprehensively evaluating the user experience during use.

Launch Experience Analysis​

When users open two applications with the same functionality, if application A is ready for use in two seconds, application B will be immediately "sentenced to death" even if it's only delayed by three seconds. The launch experience of an app is the "first door" of direct intimate contact between real users and the product. When the operations team has difficulty acquiring a user at high cost (perhaps tens to hundreds, depending on the demographic) in today's scarce network traffic bonus, if the user downloads the app and has a very poor "first launch" user experience (slow startup or crash), it will lead to the user directly deleting the app.

"Mobile Launch Experience Analysis" is suitable for monitoring and analyzing app startup performance and exceptions during the process, divided into three categories: first launch, cold launch, and hot launch, including displays of application startup time, startup performance breakdown, regional analysis, exception statistics and tracking, slow startup individual samples, startup crash information, and startup error information.

Page Experience Analysis​

When users open an app to browse application pages, they often encounter phenomena where page display is not smooth enough and content is missing, causing great frustration for customers. As shown in the application page loading diagram below, the example page loads slowly, preventing normal interaction with the application. Especially for e-commerce applications during major promotions, first-screen loading issues prevent users who originally intended to purchase goods from browsing, leading to a decrease in order volume.

"Mobile Page Experience Analysis" is used to monitor and analyze app page loading time and page interactivity time, assisting product operations personnel in analyzing user experience of important pages through visualization charts. At the same time, it provides detailed individual sample waterfall diagrams for pages with slow loading and slow interactivity, providing important reference for developers to optimize page experience.

Operation Experience Analysis​

When users interact with applications, they often experience freezes, crashes, and spinning interfaces, preventing the use of certain core functions, and even leading to one-star negative reviews in app stores as shown in the figure below. When developers encounter such problems, they often find it difficult to locate and optimize these user experience issues due to the lack of reproduction scenarios and device information.

"Mobile Operation Experience Analysis" is used to monitor and analyze the availability and performance of app user operations, determining whether freezes, errors, or application crashes occur during use. At the same time, it provides "visual naming" services for product operations personnel, allowing them to understand the experience of key operations of concern through simple configuration by scanning a code to open the app; it provides "operation breakdown diagrams" for development and testing personnel, allowing them to understand various call relationships during the execution of "operation" methods through the "operation breakdown diagram" without needing to view the corresponding code logic, directly locating time-consuming methods, enabling rapid iteration of versions.

Availability Monitoring Scenario​

Applications often experience "crashes" and "freezes" during operation. Compared to crashes, freeze problems are more difficult to analyze for their root causes due to "constantly changing call stacks," "unclear user trajectories," and other reasons.

Through Mobile, developers can analyze all main thread call stacks during the freeze process (default 5s, configurable) by examining five call stacks during the freeze process, and can understand user trajectories and "network" conditions during the freeze process, analyzing the root causes of freezes from multiple dimensions and angles.

Network Environment Detection Scenario​

The vast majority of customer complaints are caused by network failures. It is generally difficult to analyze situations where "functions are unavailable" due to network problems during user use. Development and operations personnel cannot obtain first-hand information from the client and cannot define the problem based solely on customer descriptions.

The Mobile SDK has optimized the shortcomings of network detection being "built-in, triggered slowly, and data lagging" by adopting a mobile synthetic monitoring solution (active collection), which can quickly assist development and operations personnel in collecting client information. The mobile synthetic monitoring solution has the following capabilities:

  • Multiple Scenarios: It can detect client network environments for different user scenarios, divided into three major scenarios: "execute immediately," "execute after request," and "execute after request error," covering all situations.

  • Multiple Dimensions: Due to the uncertainty of network failures, it can be arbitrarily combined according to region, carrier, access method, and VIP customers (specifying a certain user through UserID), effectively reaching the area (dimension) of network failures.

  • Multiple Metrics: It can collect client network metrics, including: network latency, packet loss rate, request time consumption, jitter, hop count, and error conditions.