Segment your data with analytical dimensions
Determine the relevant analytical dimensions
Segmentation lets you enrich your data and compare your KPIs (MRR, churn, LTV, etc.) across relevant subgroups. But which dimensions should you create and analyze first? Here is a practical guide to help you choose the most useful dimensions. 1. The most common segmentation dimensions a. Native dimensions (in the case where an integration is used) These dimensions are automatically available because they come from your billing data. They may nevertheless require some cleaning worSome readersAdd analytical dimensions
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 metadaSome readersManage analytical dimensions
1. Where to find your analytical dimensions All your dimensions are grouped under Data → Custom dimensions. This page is restricted to administrators: if the menu does not appear, ask an administrator of your instance for access. You will find the complete list of your segments there, sorted by object: Customers Subscriptions Invoices Invoice line items Products / price plans Each dimension displays: its name, its type (text, list, number…), and the **numbFew readersUse analytical dimensions in your analyses
Why use analytical dimensions? Why use analytical dimensions? Analytical dimensions let you enrich your billing data in order to analyze your performance from different angles. Thanks to them, you can adapt your analyses to the reality of your business — by customer, product, region, acquisition channel, or any other business dimension. By using analytical dimensions in Fincome, you can: Filter and break down your KPIs (MRR, churn, NRR, ARPA, etc.) according to custom dimensions,Few readers
Analyze your KPIs
Analyze your cohorts
In Fincome, cohort analysis lets you track the evolution of a group of customers acquired over the same period, in order to assess their retention, expansion, or attrition over time. In other words, you can group your customers by acquisition date (for example, by month or by quarter) and observe how their indicators evolve after X months of using the product. This approach helps identify loyalty and growth trends across each generation of customers. In Fincome, a cohort therefore corresponds tFew readersAnalyze renewals
See which subscriptions renew and when in Fincome (Analytics > Retention > Renewals), where the commitment end date comes from, and how to export your customers' renewal dates.Few readersAnalyze your metrics continuously with the Rolling Window
The Rolling Window gives you an alternative way to read your indicators: a continuous analysis, in the form of an X-month moving average, instead of a view split by calendar month. Ideal for analyzing your momentum, detecting trend inflections, and neutralizing calendar-related edge effects. What is the Rolling Window? The Rolling Window (or sliding window) means calculating a KPI over the last X months, updating that window continuously. In practice, it is an **[X]-month moFew readersWhat can you do with the Fincome MCP? Use cases and example analyses
Who the Fincome MCP is for, how it works, what information it can return, and three examples of deliverables built in natural language.Few readers