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Segmenting Data with Analytical Axes
Tirer des clés de lecture sur ma performance grâce aux axes analytiques
Thanks to analytical axes, Fincome lets you enrich your billing and banking data for in-depth performance analysis.
By building analytical axes into your Fincome dashboard, you can:
- Enrich your data to add any axis reflecting the operational granularity of your business tracking
- Filter and break down any KPI according to these newly created axes
- Save any set of filters for use at any time, for any relevant KPI
Analytical axes can be created for any type of data (invoice, invoice line, customer). Depending on the type of axis you wish to create, choose the type of data that seems most relevant to you. Note that invoice lines are the lowest common denominator, as they are a component of the invoice.
Go to the "Data" section, and select the type of data for which you wish to create an analytical axis. You can then click on the "Add a column" button, and name your axis (e.g. "Customer size", "Business sector", "Geography", etc.).
To assign values to your axis, you can then:
- assign a value directly to each line
- select several lines using the selection buttons to the left of each line (you can filter your data and then select the filtered lines)
You can also import data enrichment files. To do so, go to the "Data" section, select the data type for the axis you wish to create and click on the "Enrich your data" button. If you load an Excel file as the source of billing data for your Fincome dashboard, you can directly add an additional column to the Excel file you import into Fincome.
Once you've created your axes and assigned them values, go to the "Analytics" section. You can now filter your indicators and break them down according to the axes you've created! When you have one or more filters active, you can save the selection as a segment, enabling you to find your favorite filters easily every time you analyze your performance.
Some use cases shared by our users:
- Breakdown of MRR growth by geography to see which segment is the most dynamic
- Churn analysis by product to see if one offer is underperforming compared to others
- Analysis of ARPA by customer category to better understand purchasing behavior