Completion numbers alone don't show where users drop off. Learn how to use Hive Analytics charts and funnels to check step-by-step conversion and drop-off from content acceptance to completion.
Blog · Page 5
- Analyzing User Flow from Content Start to Completion
- Removing Test Data to Analyze Real Service Performance
When events from QA servers and test apps get mixed in, user counts, revenue, and purchase conversion rate no longer reflect reality. With Metric Filter Management in Hive Analytics, register a Server ID or App ID and exclude test data from every chart, funnel, retention, and dashboard at once.
- Where Data Analysis Starts: Aligning Your Organization's Metric Standards
When commonly used metrics like active users (AU) or revenue are calculated differently across teams, the same period can produce different numbers. Learn how Hive Analytics' Metric feature lets you define events, aggregation methods, and formulas once and reuse them everywhere.
- Analyzing Real User Data by Filtering Out Internal Test Accounts
With Excluded User Management in Hive Analytics, register a User ID or Device ID once and that user's events are automatically excluded from every chart and dashboard, so you can review operational metrics based on real users only.
- Finding Marketing Performance Differences by Dimension
Overall metrics can hide performance differences that only show up when you break the data down by country, market, OS, and other dimensions. See how Hive Analytics helps you narrow in on where the gap is.
