Analyzing Event Data

This page presents an example of event data analysis. In this example, we classify events with users' attributes, such as their gender, age, and location. The example assumes a case such as analyzing the audience who have entered a campaign questionnaire.

Analysis example

In this example, we assume that the following data is sent as an event data. This Event Data is named "MyUser".

  • "gender" ... String (M or F)
  • "city" ... String (San Francisco, Dallas, New York, ...)
  • "location" ... String (UK, EU, JP, ...)
  • "children" ... Int (0, 1,2,3, ...)
  • "age" ... Int (18, 20, 42, 44, ...)

Based on the above event data, we want to check the following metrics:

  • Metric #1: Average of "age" sliced by "city", "location", "gender" and "children".
  • Metric #2: Count of users (i.e. count of event data) sliced by "gender", "city", "location", "children" and "age".

Data example and expected results

The examples and expected results will be similar to that of app data analysis covered in Analyzing App Data. To learn the differences between app data and event data analysis, see Flex Analytics.

Just like app data analysis, the result becomes hard to interpret when the value of the specified dimension diverges. In our example, slicing the metric #2 with the dimension "age" will aggregate the count per age, which makes the result very hard to interpret (e.g., ten data for age 20, fifteen data for age 21, ..., six data for age 89). See Define the Classes to learn how you can deal with the situation.

How to configure

  1. Define a metric
  2. Send event data from the mobile app
  3. Analyze results in the developer portal
  4. Get analysis results with the API