Analytical dimensions let you segment your data according to custom dimensions: customer size, industry, acquisition channel, geography, etc. They can be created on every Fincome object: invoice, invoice line, customer, product, or plan.

Two management modes are possible:

• Manual addition from Fincome or your Excel files: ideal for one-off or low-volume dimensions, which you can update over time.
• Automated addition: dimensions can also come up automatically from the metadata of your integrated billing tools (e.g.: Chargebee, Stripe, Sellsy…) or via the Fincome API if your internal systems already send this information.

💡 Note: invoice lines are the smallest common denominator for the most detailed analyses.

Before creating your dimensions, we advise you to read the article Determine the relevant dimensions in order to choose the dimensions most useful for your business.

1- Automatic feeds

a. Via the metadata of your integrated billing tools

If you have connected a billing tool to Fincome (e.g.: Chargebee, Stripe, Sellsy, Pennylane…), the custom fields already present in these systems (called custom fields or metadata) can be automatically imported as analytical dimensions.

Concretely:

• Fincome detects customer, product, or subscription metadata during synchronization.
• These fields become available as analytical dimensions in your analyses (filtering, breakdown, reporting…).

b. Via the Fincome API

The Fincome API can be used in two ways depending on your data configuration:

1. To send your complete billing data (invoices, subscriptions, customers) when you are not using a native connector,
2. Or simply to enrich your existing data with additional fields (metadata, business attributes, tags, etc.), even if your invoices are already synced via a connected tool.

In both cases, the attributes you add (for example an "acquisition channel" or "customer type" field) are automatically integrated as analytical dimensions in Fincome.

c. Via the CRM integration (HubSpot or Salesforce)

Based on a matching key for the objects to enrich between Fincome and your CRM, the metadata you choose to use can be brought up automatically with our integration.

Here is our HubSpot integration guide and the Salesforce one.

2- To add manually

a. From the Fincome interface

1. Go to the Data section.
2. Select the relevant data type (customer, invoice, product, etc.).
3. Click Add a column.
4. Name your dimension (e.g.: Customer size, Industry, Geography…).
5. Fill in the values:

• row by row,
• or by selecting several rows using the checkboxes on the left (you can filter before selecting).

b. Via Excel import

From the Data tab

You can also import data enrichment files. To do so:

1. Go to the "Data" section
2. Select the data type for the dimension you want to create
3. Click the "Enrich your data" button and download the template

Once the Excel file is downloaded, you will find the list of the chosen object (for example the list of all customers). To add dimensions:

1. Add as many columns as custom dimensions you want (one column = one dimension)
2. Fill in the dimension columns with the desired values for each row

Once the file is finalized, save it, then re-import it on the same page as the one used to download it.

From your initial data import (in the case where you integrate your billing data via an Excel file)

You can also add a column in your data import file. This column will automatically be considered an analytical dimension linked to the Customer object.

Add the values for each of the rows. When you import your data, the added columns will automatically be brought up as customer analytical dimensions.

Best practices

• Choose homogeneous and stable values (e.g.: "SMB", "Enterprise" rather than variable labels).
• Avoid duplicates or different spellings for the same value.
• Update your dimensions regularly when your segmentation evolves.

What next?

Once your dimensions are created, you can use them in your analyses to filter, break down, and compare your indicators.
➡️ See the article Use analytical dimensions in your analyses to learn how to put them into practice.

Updated on: 03/07/2026