Metrics

Click any metric name below to open its dedicated page with the full definition, secondary metrics, and supported sensors.

VSI App provides a robust set of metrics to enable application performance monitoring and user behavior analysis across your web and native applications. Use App metrics for a holistic view of web and mobile app health, performance, and real-user experience, unifying performance analysis with user journey optimization. Metric values appear as time series and distributions in metric widgets, and alongside dimensional values in the dimension drill-down tables.

Metric Types

VSI App supports several metric types:

• Flow Metric: helps in the identification of crucial moments in user journeys to optimize applications and improve the user experience. For example, consider the metrics corresponding to the flow from searching for a video to successfully playing it.

• Individual Metric: associates with initial and follow up events. VSI App enables several types of individual metrics.

• Duration Metric: Measures the time interval between two events, such as the duration between the login screen event and the login success event.

• Conversion Metric: Measures the count or conversion rates of events from one stage to another, such as the count of sessions with successful login after opening the login screen.

• Event Aggregation Metric: Measures the number of events, or calculates the value of event attributes, such as the average duration of network requests.

• Ratio Metric: Displays the relationships or proportions using mapped event values and OOB/custom aggregation metric values, such as revenue per paying user.

  For this metric, select the Ratio metric settings with:

• Numerator: build from a mapped event, such as Total Revenue, calculated by total values

• Denominator: build from the predefined metric Unique Users

  For detailed analysis, applying this metric to a dimension in Trends, such as Device, shows how revenue per paying user varies across different device types.

• Out-of-Box Metric: enables application performance monitoring and user behavior analysis across web and native applications. The OOB metrics include these categories:

• Audience and Engagement: Insights into user activity patterns, session behaviors, and content consumption, enabling a comprehensive understanding of audience reach and engagement levels.

• QoE and KPI Metrics: Insights into performance issues on user sessions, highlighting areas where poor experience may affect engagement, satisfaction, or retention.

• Frustration Signals: Insights to user friction points, such as rage clicks (repeatedly clicking on an element in frustration), excessive app restarts, and clicks preceding web errors and mobile app crashes.

• Web User Experience: Insights into how users perceive and interact with web pages, highlighting performance bottlenecks, navigation delays, and error occurrences. A Presets dashboard offers quick starting points and commonly used metrics and metadata for Web use cases.

• Mobile User Experience: Insights into how users perceive app performance, including startup times, screen loading, and navigation speed. A Presets dashboard offers quick starting points and commonly used metrics and metadata for Mobile app use cases.

• Service Performance: Insights into how network performance impacts user experiences, highlighting slow responses, failed requests, and error rates. A Presets dashboard offers quick starting points and commonly used metrics and metadata for service use cases.

App also provides bad pattern metrics such as ANR -> Exit and Crash -> Exit to quantify sequences of events that indicate poor user experiences, including repeated errors, failed interactions, and app restarts. Unlike isolated incident tracking, these metrics capture the compounded impact of problematic event chains, offering a more holistic and actionable view of user frustration.

A App session starts when any system or user-defined event is received and ends after 90 seconds of inactivity.

Metrics can span a specific interval or a complete session.

• Session Metrics: Metrics based on data from events that occur throughout sessions that end within the selected time interval, for example App Video Bounce Rate metric from sessions that ended yesterday. If a session starts before the selected time interval but ends within it, the data for that session is still considered for the calculation of the session metrics.

• Interval Metrics: Metrics based on data from events that occur within a specific interval during sessions, for example, Total Events, the cumulative count of mapped events occurring within a specific interval during sessions.

In addition to the metrics designed by Conviva to optimize your analysis, VSI App supports a custom metric builder so you can create customized metrics based on your specific requirements. For more details, see Metric Builder.

Secondary Metric

As primary metrics, Conviva uses a proprietary combination of native and web applications events to provide a rich set of application performance and experience metrics. The DPI Sensor supports events, such as page_view and network_request.

Selecting a metric widget in VSI App also displays a secondary metric that provides a context or related data to help you more completely understand the primary metric. Secondary metrics enhance the interpretation and analysis of primary metrics.

Secondary metrics display in the dimension panel after clicking a metric widget in the metric panel, for example Ended Session Count displays as a secondary metric for App Video Bounce Rate.

Percentile Aggregation (Beta)

For Duration, Flow-Duration, and Custom Metrics, Conviva introduces percentile data percentile-ranked statistical aggregation for P50, P75, P90, P95, and P99 levels of Duration, Flow-Duration and Custom performances. Ranked-flow and custom performance data enable accurate measurement of performance distributions, minimizing the impact of long-tail outliers that can distort average-based metrics. Percentile aggregation provides a statistically robust representation of data and aligns Conviva analytics with industry-standard performance measurement practices.

By sorting and then ranking data, a percentile indicates the value below which a given percentage of observations fall. For example, within a ranked data set of session performance,

• P50 (50th percentile) means 50% of the session performance is completed at or below this value.
• P95 (95th percentile) means 95% of session performance is completed at or below this value, and only the slowest 5% take longer.

Out-of-Box Events

Check the auto-ingested events and minimum player versions for details about auto-collected event support.

Custom Events

Video Events

With these Video and App SDK versions, Conviva automatically sends video events to the App SDK:

Conviva video events (conviva_video_events) are also available using abbreviations as tag keys.

Out-of-Box Metrics and Metadata

Quickly get started analyzing your user experiences with out-of-box metrics and metadata.

Metrics By Metric Category

Metadata as Dimensions

Metric Definitions By Device

Metrics: Flow Metrics

Metric	Definition
Flow Name Init (Use the first initial event)	The number of initial events within the user-defined Flow Duration Limit, maximum 1 hour. Count the First initial event if multiple initial events happen (user configured).
Flow Name Init (Use the last initial event)	The number of initial events within the user-defined Flow Duration Limit, maximum 1 hour. Count the Last initial event if multiple initial events happen (user configured).
Flow Name Complete # %	Complete #: The number of initial events followed by a complete event within the user-defined Flow Duration Limit, maximum 1 hour. Complete %: Complete # / Init
Flow Name Complete Duration	The time from the initial event to the complete event within the user-defined Flow Duration limit, maximum 1 hour.
Flow Name Success # %	Success #: The number of completed flows (initial event followed by a complete event within the configured success window). Success %: Success # / Init
Flow Name Flows with Errors # %	Flows with Errors #: The number of Flows with at least one error. Flows with Errors %: The number of Flows with errors divided by the total number of Flows.
Flow Name Abandoned Flows # %	Abandoned Flows #: Initial events with no complete event or with a complete event occurring beyond the user-defined Flow Duration Limit (up to 1 hour). Abandoned Flows %: Abandoned Flow # / Init
Flow Name Abandoned Flows with Errors # %	Abandoned Flows with Errors #: The number of abandoned flows that had at least one error. Abandoned Flows with Errors %: Abandoned Flows with Errors # / Init
Flow Name Completed Flows with Errors # %	Completed Flows with Errors #: The number of completed Flows with at least one error. Completed Flows with Errors %: Completed Flows with Errors # / Init
Flow Name Total Error Count	The total number of Flow errors in both completed and abandoned flows.
Flow Name Errors in Abandoned Flows	The number of errors in abandoned Flows.
Flow Name Errors in Completed Flows	The number of errors in completed Flows.
Flow Name Network Request Avg Duration	The average network request response time after the first initial event within the Flow completion window, maximum 1 hour.
Flow Name Network Request Failure # %	Network Request Failure #: The number of network request failures on or after the first initial event within the Flow completion window, maximum 1 hour. Network Request Failure %: Network Request Failure # / Network Request Count
Flow Name Network Request Count	The number of network requests on or after the first initial event within the Flow completion window, maximum 1 hour.