Data Explorer

Data Explorer gives you the ability to filter and use your data based on metrics or Events and group them by platform, country, or version. You can query your game data based on predefined metrics or events, apply dimension filters, and group by which splits the series into each group in that dimension. You can toggle between a bar chart, line graph, area graph, pie chart, and stacked bar chart.

Unity Analytics has the following features and improvements to legacy Unity Analytics:

  • Data is refreshed at least every two hours (after the SDK has been installed).
  • Multi-dimensional filters with tailored filter values.
  • Group by dimension.
  • A simpler user interface.
  • Improved data visualization.
  • Transparency around metric definitions.

The current available metrics are:

MetricDescription
DAUNumber of unique players per day.
DAU (new vs. returning)Percent of DAU who were new on that day.
WAUNumber of unique players in the previous seven days.
MAUNumber of unique players in the previous 30 days.
DAU per MAUPercentage of MAU who played on a particular day (DAU/MAU).
New usersDaily users who are new that day.
Session lengthTime elapsed from when the user starts the app, and exits.
Number of sessionsNumber of sessions played that day.
Sessions per userAverage number of sessions for each user.
Total daily play timeTotal playing time of all players on that day.
Daily play time per DAUAverage playing time of users playing on that day.
Day 1 retentionPercentage of users who returned to your game after one day.
Day 7 retentionPercentage of users who returned to your game after one week.
Day 30 retentionPercentage of users who returned to your game after 30 days.
ARPPUAverage revenue per paying user (This metric includes revenue from both transaction and ad impression events where available).
ARPDAUAverage revenue per daily active user (This metric includes revenue from both transaction and ad impression events where available).
TransactionsCount of all transactions.
Paying usersNumber of DAUs who spent money that day.
Revenue per transactionTransaction amount divided by number of transactions.
Total revenueSum of all transaction amounts.

Number of sessions played in the last 30 days.

Events can be further grouped by event parameters. Event parameters are extra information sent with the Event.

In the example of a Fruit Machine-like game, spinSummary is an Event, and numberWinningLine is an Event parameter.

Use the aggregate filter based on event counts by the user. "Aggregate by Average" means the average event count across all users. "Aggregate by Max" means the maximum number of events sent by any given user, and so on.

You can summarize your data in a table view. You can select sum or average, which adds a selector, and a new row in the summary table of Data Explorer.