• Analyze your KPIs

  Analyze your cohortsAnalyze renewalsAnalyze your metrics continuously with Rolling WindowFew readers

• Analyze your cohorts

  In Fincome, cohort analysis allows you to track the evolution of a group of customers acquired during 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 quarter) and observe how their metrics evolve after X months of product use. This approach helps identify retention and growth trends for each customer generation. In Fincome, a cohort therefore corresponds to a groupFew readers

• Analyze your metrics continuously with Rolling Window

  The Rolling Window offers you an alternative reading mode for your metrics: acontinuous analysis, over the last X days or X months, instead of a month-by-month segmented view. Ideal for analyzing your momentum, detecting trend inflections and neutralizing calendar-related edge effects. What is a Rolling Window? A Rolling Window (or sliding window) consists of calculating a KPI over the last X days or the last X months, updating that window continuously. Some possible examplesFew readers

• Use analytical dimensions in your analyses

  Why use analytical axes? Why use analytical axes? The analytical axes allow you to enrich your billing data in order to analyze your performance from different angles. Thanks to them, you can tailor your analyses to the reality of your business — by customer, product, region, acquisition channel or any other business dimension. By using analytical axes in Fincome, you can: Filter and break down your KPIs (MRR, churn, NRR, ARPA, etc.) according to custom dimensions, Compare yFew readers

• Analyze renewals

  Analyzing subscription renewals is essential for recurring-revenue businesses. It provides visibility into upcoming due dates and allows anticipating churn risks (customer cancellations) or, conversely, expansion opportunities (upsell/cross-sell). Fincome’s Renewals section offers a clear view of the portion of MRR/ARR that will be renewed over a given period, calculated automatically. This lets you accurately forecast your future revenue, spot renewal opportunities at a glance, and reduce churnFew readers

• Determine the relevant analytical dimensions

  Segmentation allows you to enrich your data and compare your KPIs (MRR, churn, LTV, etc.) by relevant subgroups. But which axes should you create and analyze first? Here is a practical guide to help you choose the most useful dimensions. 1. The most common segmentation axes a. Native axes (when an integration is used) These axes are automatically available because they come from your billing data. They may, however, require some cleaning (harmonizing product, plan, or country laFew readers

• Segment your data with analytical dimensions

  Determine the relevant analytical dimensionsAdd analytical dimensions Use analytical dimensions in your analyses (/help-center/en/conducting-in-depth-analyses/segment-your-data-with-analytical-dimensions/use-analytical-dimensions-in-your-analyFew readers

• Add analytical dimensions

  The analytical axes allow you to segment your data according to custom dimensions: customer size, industry, acquisition channel, geography, etc. They can be created on each Fincome object: invoice, invoice line, customer, product or plan. Two management modes are possible: Manual addition from Fincome or your Excel files: ideal for occasional or low-volume axes that you can update over time. Automated addition : axes can also be automatically pulled from the metadata ofFew readers

• Manage analytical dimensions

  1. Where to find your analytical axes All your axes are grouped in Data → Custom axes. You will find the complete list of your segments there, sorted by object: Customers Subscriptions Invoices Invoice lines Products / pricing plans Each axis displays: its name, its type (text, list, number…), and the number of values currently associated. 2. Actions available on your axes View existing values Click on an axis to display all the values associated wFew readers