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Analyze a distribution

Analyze the distribution of numeric properties that describe people, their behaviors, and how they traverse through your experience using Interana distribution view.

Why use distributions? Sometimes it’s not enough to know what the average user is like in your experience. For example, if you have different user segments who exhibit different behaviors, you might find that there are different modes according to your usage metrics. Or you might want to look for power users who act like extreme outliers. Distributions can help illuminate these cases.

Use distribution view

To get started:

  1. In the left menu bar, click Apps, then in the center panel click Distribution.

  2. In the Event property field, pick an actor property, event property, or flow property. Only numeric properties are available.

  3. In the Starting and Ending fields, select a time range you want to examine that property over.

  4. Hit GO. Interana suggests a default binning and displays a histogram.

For example, say your data set has an actor property BodyHeight. In this example, you might select a BodyHeight actor property. When you press GO, you’ll see a histogram of your user height. 

Adjust the range

To look at one part of the distribution, you can apply a filter to your property. You can do this in either of two ways. 

You can explicitly define limits, using the "Filtered to" line in the query builder. For example, if BodyHeight is in units of inches and you want to look at people greater than 6 feet tall, apply “Filtered to BodyHeight is greater than 72” to the original binning property. 

Or, to zoom in on any particular bin, click the bin and then click Zoom in. Interana applies the relevant filters in your query.

Whichever way you filter the range, zoom out by clicking the trash icons next to the value filter.

Note that ranges (and percentiles) identify inclusive and exclusive elements. A bracket indicates an inclusive range, and a parenthesis indicates an exclusive range. For example, integers described with this notation are as follows:

  • (0, 3) = 0, 1, 2, 3.
  •  [0, 3) = 1, 2, 3.
  • [0, 3] = 1, 2.

bin_detail.png

Adjust binning

To adjust the binning while you are zooming or adjusting the range, click Modify Bin+Measure.

You can adjust the bin size or count. When you pick one, Interana automatically recalculates the other based on the range of values in your bin property and applied filters.

Adjusting binning also lets you create interesting analyses. When investigating event properties, you can bin by either a count of all events, over a property, or over a calculation of a property.

Example: Analyze song lengths

As a basic example, consider a music service dataset with an event property called SongLength.

If you are interested in the distribution of songs played over the past couple weeks, irrespective of the unique songs, then distribute across SongLength, using the default query.

However, if you are more interested in seeing the distribution of unique songs, then click Modify Bin+Measure. The default measure specified is count of events. To count the unique songs played, in the Measure field, select Song. As a result, you will get a distribution of SongLength for unique songs.

Calculate binning properties

You can go beyond counting unique things: you can sum or average different properties over your binning property. Do this by creating bins based on a count or other function (sum, percentile, etc.) of a specific attribute.

Let’s return to our original example binning property: SongLength. To learn how SongLength relates to total play for all song plays, adjust your measure to sum of SongLength. Your resulting distribution might not look like a Gaussian curve anymore, but you might be able to discover whether your users spend more time playing shorter or longer songs.

Example: Find total spending per age bracket

For example, consider a commerce dataset with an event property called Age.

If you are interested in the distribution of all types of events, then distribute across Age, using the default query.

Or, to see the distribution of total money spent per age bracket, filter to events with action that matches purchase_confirmed, then click Modify Bin+Measure. The default measure specified is count of events. In the Measure field, select sum and price. The result is a distribution of total money spent per age group.

sum(price) by age.png

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