Measures & Dimensions
Measure and Dimensions are the core of the widgets for our dashboards. On this page, we will get to know more about them.
A widget is comprised of data, which is split into measures and dimensions:
Measures are, in simple terms, the data that we want to visualise as numbers or in a chart.
Dimensions are the groupers, meaning something that we want to split the data (that we get from the measures) by.
You're limited to the Measures and Dimensions that are specified in your schema, which determines what data will be available for you.
Initially, for your measures and dimensions, you'll have access to activity conversion data, as well as data from the real-time feed such as the following events; payment, login, registration, casino, sportsbook, lottery, and cart.
Below, we will learn more about Measures and Dimensions.
Select Data Scope
When creating a widget (or using the Explore functionality), you first need to select what data scope you want to use.
Let's quickly explain why that is. Some data (measures and dimensions) are simply not "related" and can't/shouldn't be combined when creating charts. That's why we have divided all the data into different data scopes to make it easier for you to create your dashboards with ease and that behave as expected.
Each data scope, as shown below, also lists what type of data they contain so you can make sure to pick the best suitable one for your upcoming widget.
The Data Scopes:
Explore casino players' activity from a 360-degree view. The scope includes casino events, bonus events, payment events, and login events with breakdowns by system singularity player feature states.
Activity Conversion Metrics:
Explore high-level activity conversion metrics. The scope includes conversion data relating to sent activities along with channel performance metrics.
In-Depth Activity Performance
Explore Activity performance from a 360-degree view. The scope includes data for players 90 days before and after they were targeted by an activity. All casino performance data, filtered for players targeted by the selected activity.
Player Feature Movements
This is a scope for player features in the Singularity model. Every current state and movement within the singularity model is featured in this view.
Measures determine what data that we want in our widgets.
Examples of measures are deposit amount, bonuses turned real, actives, and gross gaming revenue. Just to mention a few of them.
What measures and how many you want to use is completely up to you. This is directly related to what data you're looking to display for your widget.
When adding a measure, you'll see all the options available in a drop-down menu. All measures you'll find beneath a specific category/section.
Depending on the Data Scope you have chosen, you'll have different measures available.
Filters for Measures
When you've selected a measure, all the data connected to it will be pulled from the system. There will be times where all data is relevant and there will be other times when you only want specific data from the measure you've selected. In the case of the latter situation, when you only want a specific selection of data from your measure, you can use filters to achieve this.
Adding filters is easy. When you've added a measure, you simply click on the funnel icon, to the far right, which will add additional fields for you to add your filters.
Once you've entered the filter of your choice you save it by clicking on the disk icon, and by clicking on the plus icon you can add additional ones.
You can add as many filters as you need to your measures.
Also, multiple values can be added per filter. Simply type the value and hit enter or the comma key between each value you'd like to add.
🙋 Note: If you have multiple measures, the filters will apply to all of them.
Below we have 2 examples of measures with added filters.
The Measure 'User Details: Count' is referring to the player count which is the number of players registered to your site. Without any filter, this means all players will be included.
Should you instead want the number of players that are registered from Germany, we can add the filter 'Country equals "DE"'.
The Measure 'Activity Conversion: Conversion Rate' is referring to the conversion rate of your activities. Without any filter, all of your activities will be included in the conversion rate value that you'll get from this measure. This means you'll get the conversion rate across all activities combined (calculated: count of players that deposited within conversion period of an activity / divided by / count of all activity fires).
Should you instead want to see the conversion rate for a specific activity, we need to add the filter 'Activity ID equals "1337"' (Activity Conversion: Activity ID).
Filter by Time (Dimensions)
Let's say that activity 1337, in the example above, is an automated/recurring activity. This means that the conversion rate would be calculated over all time, for every time the activity has been fired. If you instead wanted to see the conversion rate for a specific time period you need to add a time dimension, which is found in the section beneath the measures.
With the time dimension 'Activity Fire Date' set to 'Last week' and 'w/o grouping' you'll always get last week's conversion rate for the activity.
There's a lot of different options and alternatives when it comes to time dimensions. Read more here.
We get the data from the measures and the dimensions are something that we want to split the data by.
Examples of dimensions are splitting data by country, casino vendor, acquisition source, or by month. The first 3 examples are "regular" dimensions whilst the last one, splitting by month, is an example of a time dimension.
What dimensions and how many you want to use is up to you. This is directly related to how granular you want to be with the data you've selected for your widget. It's worth keeping in mind what chart type you would like to use, as some are limited to a certain number of dimensions (and measures).
When adding a dimension, you'll see all the options available in a drop-down menu. All dimensions you'll find beneath a specific category/section.
Depending on the Data Scope you have chosen, you'll have different dimensions available.
Worth noting is that it's possible to combine the regular dimensions with time dimensions. It's also possible to have regular dimensions without a time dimension and the other way around.
Time dimensions behave like any other dimension but have more flexibility.
For a time dimension, you can select a time period and break it down by a particular level of granularity. For example, you can choose the time period 'This Year' and have it split by day, week, or month, etc.
With time dimensions, you first select which time dimension you want to use in the field to the far left.
Next up you select a time period, to filter on data that has been collected from that specific period of time. Here you have multiple choices to choose from:
Let's go through them all one by one to get a better understanding of what they mean.
Custom: Select a start and end date, which gives you data from a specific time period.
All time: All data, from all time, that has been collected will be pulled.
Today: Data from the current day. Days are calculated as calendar days, meaning that the day starts after midnight and ends at the next one (UTC time).
Yesterday: Data from the previous day. Also calculated as calendar days.
This week: Data from this calendar week. A calendar week starts on Monday and ends on Sunday.
This month: Data from this calendar month. A calendar month starts on the 1st and ends on the last day of the month.
This quarter: Data from this quarter. A quarter starts on the first day of the quarter and ends on the last day of the quarter.
This year: Data from this calendar year.
Last 7 days: Data from the last 7 days. Calculated from now and 7 days back in time.
Last 30 days: Data from the last 30 days. Calculated from now and 30 days back in time.
Last week: Data from the previous calendar week. A calendar week starts on Monday and ends on Sunday.
Last month: Data from the previous calendar month. A calendar month starts on the 1st and ends on the last day of the month.
Last quarter: Data from the previous quarter. A quarter starts on the first day of the quarter and ends on the last day of the quarter.
Last year: Data from the previous calendar year.
Yesterday and Day before: Data from yesterday and the day before (in calendar days).
Last Week and Week before: Data previous week and the week before (in calendar weeks);
Last Month and Month before: Data from the previous month and the month before (in calendar months)
Last Quarter and Previous Quarter: Data from the last quarter and the quarter before.
When the time period has been selected, last but not least, you need to decide on the granularity of the data.
W/o Grouping: This gives you one single value (from the selected time period), without any additional groupings.
Second: This gives you values grouped/split by seconds.
Minute: This gives you values grouped/split by minutes.
Hour: This gives you values grouped/split by hours.
Day: This gives you values grouped/split by days.
Week: This gives you values grouped/split by weeks.
Month: This gives you values grouped/split by months.
Quarter: This gives you values grouped/split by quarters.
Year: This gives you values grouped/split by years.
Once you've decided on the data (measures and dimensions) you want for your widget, it's time to decide how you want to display it. This is decided by choosing a chart type. Read more about chart types here.