Articles on: Datas, Analytics & Integrations

πŸ“Š Measure your audience's behavior

Each user path is unique and can have an infinite potential of combinaisons.

To learn about your audience behavior and see their live trends, we need to use analytics.

Detect unsuspected identical behaviors, with instant feedback, improve your content or create more specific content.

Analytics is a business feature. To upgrade your account if needed, go to:


Through Triggers Β that upload data. The statistic representation is a Sankey diagram (perfect for transfer visualization) with branches sizes depending on the user traffic.


You can analyze the size of your audience and the time spent on your app.


You can compare the origins of your audience.

1. Create Analytics blocks

by clicking on Add blocks then select Analytics.

2. Place as many triggers

as you want, where you want user triggering it. You can place them after a Choice or any other block.

In the Bot example, the first choice is to take the Red or the Blue pill.
As we want to analyse both choices, let's create a block for both branches the Storyline can take.

3. Indicate the order of each trigger

As the Sankey Diagram represents a statistic vizualisation of the graph and as you might want to compare blocks which can be at different place in the graph, you need to specify the order number you want to attribute to each block.

In that graph, we can see the 3 series of orders aligned with their respective Analytics block (in dark green).Β 

The last order is always the STOPPED order, which helps you to measure the churn, aka why users leave the app. A transfer from a trigger to STOPPED would represent a user leaving the application.

In this example, Red pill trigger is order 1.

Blue pill trigger is order 1 too to be able to be compared with the Red pill trigger.

4. Indicate the name of each trigger

in the Analytics blocks.

Let's name it Red Pill.

Name of the trigger appearing and its percentage of users who activated it (among the users of the same trigger order) can be seen in the Sankey diagram by moving your mouse on a trigger.

Number of users in a transfer (between 2 triggers) can be seen by moving your mouse on their common link.
Here, 3 people (/6, the size of the transfer is indeed half the high of the diagram) went from Red pill to Choice C.

5. Open the Analytics menu

by going on Main Menu/Analytics.

Analytics menu opens.

6. Sort the results

by the filter you want.

Here, we have used the Mac users filter. We can see they are very equality spread into their first choices to choose the pill.

You can sort the playthrough by:

publishing version: it is possible to change the version during the export of the app.
devices: change between mobile and desktop devices who played the app. Multiple devices can play the same platform (ex: iPhone and iPad on Appstore)
countries: your audience may react differently from one culture to another.
platform: where your app is published. A platform can be played by multiple OS. (ex: Web by Mac and Windows devices).

The Publishing Version can be chosen during the export.

7. Analyze the size of your audience

with the Numbers tab.

You can see:

How much your app is used (number of analytics events)
How large your audience is (number of different payers)
How many times your app has been started (user session started)
How much time a user spends (Average time played by user & Average time played by user by session)
How much time you retain your audience (cumulated app time)

8. Compare the origins of your audience

with the Repartitions tab.

The pie charts are based on the filters.

Congrats, now you know how to generate and drive your creations from the datas of your audience!**

To understand all the elements in the interface, go see the Tool Elements

Updated on: 29/03/2021

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