Analyzing & Reporting Teams

Custom metrics and dimensions for analyzing app ecosystem performance.

Updated 2026-07-06 analytics, reporting, data, custom metrics
Analyzing & Reporting Teams (custom metrics and dimensions, app ecosystem performance)

  • Easily create custom metrics and dimensions to analyze the most critical performance areas

  • Monitor detailed metrics and related dimensions to determine the health of the app ecosystem

Analyzing & Reporting Teams Task Details

Data Science Tasks

 Description

Ingest Data

Access Pulse: Integration Tools

With the Conviva DPI sensor, collect data automatically.

For more details, see DPI Integration.

Create Custom Dashboard

Access Pulse: Custom Dashboards

Create personalized dashboards and discover new insights by combining widgets and display options to emphasize key insights.

  • Showcase metrics and dimensions in summary, table, or distribution formats.

  • Edit, delete, and share your created dashboard, allowing shared dashboard recipients to view or clone it.

For more details, see Custom Dashboards.

Integrate AI alerts with PagerDuty

Access Pulse: Settings > PagerDuty

Integrate AI alerts with PagerDuty to enhance DPI AI alerts with PagerDuty escalation management and notifications.

You need a PagerDuty account with configured services to integrate Conviva alerts with the configured PagerDuty services.

For more details, see Conviva PagerDuty Integration Guide for DPI.

Set AI Alerts Email Subscriptions

Access Pulse: Settings > Email Subscriptions

Sets up email notifications for prompt updates when performance issues meet AI alert conditions.

  • Utilizes the AI Alert Email Subscriptions to administer user email subscriptions, subscribe or unsubscribe users.

  • Configures specific metric notifications based on severity levels for each user.

For more details, see AI Alert Email Subscription.

Build Custom Metrics and Dimensions for Advanced Analysis

Access Pulse: Activation

With the activation tools, set up event mappings to build customized metrics and add new dimensions to efficiently transform application events into advanced data insights. For example, map new live video attempt events and create the Live Video Attempt to Play Time metric based on the live video attempt and live video play events to identify user engagement with video content and facilitate analysis of any underlying factors contributing to delays in playback.

For more details, see Semantic Mapper and Metric Builder.