> ## Knowledge Base Index > Fetch the complete knowledge base index at: https://help.fincome.co/sitemap.xml > Use this file to discover available pages before exploring further. > Pure-Markdown content can be obtained by appending a '.md' suffix to the content URLs listed in the sitemap (without the trailing slash). # Use 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, * **Compare your performance** between different customer segments, products, or markets, * **Save your favorite filters** to reuse them in your future analyses. || Before going further, make sure you have configured your dimensions. If that is not yet the case, see the article [Add analytical dimensions](https://help.fincome.co/en/article/add-analytical-dimensions-99dnuy/). --- # 1- Filter your indicators and save custom segments Filters let you restrict the analysis to a specific subset of your data (for example, your European customers or your monthly subscriptions). ![](https://storage.crisp.chat/users/helpdesk/website/-/6/2/0/e/620ea71851239000/capture-decran-2026-08-07-a-16_1r6oogt.png) ### ➤ Apply a filter 1. Go to the **Analytics** section of Fincome then choose the indicator you want to analyze. 2. Click **Filter above the chart** (funnel-shaped icon). 3. Select the desired analytical dimension (e.g.: *Industry*, *Customer size*). 4. Choose one or more values to include or exclude. 5. Your charts and tables automatically update according to the applied filter. ### ➤ Combine or compare several filters of the same type Fincome lets you play with two filter logics: **__Combine several values in the same filter__**__:__ * Example: if you add a filter `Country = France + Belgium`, * You will get **a single curve** grouping the data of both countries (France **and** Belgium), * It is as if you had selected several values in the same field. **__Create several separate filters on the same dimension__**__:__ * Example: if you create a filter `Country = France` and another filter `Country = Belgium`, * You will get **two distinct curves** on the chart: one for France, the other for Belgium, * This lets you **visually compare** two subgroups on the same indicator. | In summary: several values in the same filter → a single cumulative curve; several filters of the same type → differentiated curves. ### ➤ Save your filters as a custom segment Once your filters are configured, you can save this combination to reuse it at any time: 1. Apply the desired filters. 2. Click **Save the segment**. 3. Give your segment an explicit name (e.g.: *Enterprise customers – Europe*). 4. Then find it in one click in the list of your saved segments. --- # 2- Break down your KPIs by analytical dimension ![](https://storage.crisp.chat/users/helpdesk/website/-/6/2/0/e/620ea71851239000/capture-decran-2026-08-07-a-16_19txf87.png) The **breakdown** lets you split an indicator according to the values of an analytical dimension, to visualize its distribution. 1. Click **Break down** next to the filter. 2. Select a dimension (e.g.: *Product*, *Acquisition channel*, *Region*). 3. Fincome then displays the distribution of the KPI according to this dimension (for example: MRR by product). || Unlike the filter, the breakdown does not exclude any data: it compares the subcategories of the same set. ### ➤ Difference between filtering and breaking down | Action | Goal | Effect on the data | | ---- | | **Filter** | Restrict the analysis to a specific scope | Excludes all other data | | **Break down** | Visualize the distribution of an indicator | Displays all the data, segmented by the value of a dimension | || 💡 Good habit: filter first to define your analysis scope, then break down to compare within that scope. ### ➤ Limits of the breakdown * Only one breakdown can be applied at a time. * You cannot break down data that is already aggregated (for example MRR movements that are already broken down). * If you have already broken down a piece of data, you must **reset** the breakdown before choosing a new one. --- # 3- Combine filters and breakdown The **Filter** and **Break down** functions are not mutually exclusive: you can combine them to deepen your analyses. The best practice consists of: 1. **Filtering** your dataset first to define the scope, 2. Then **breaking down** an indicator within that scope. | Example: Filter your dashboard on the cohort of customers acquired in Q1 2024, then break down that cohort's churn by product type. You will thus get the distribution of churn product by product within that cohort. || 💡 It is not possible to nest several successive breakdowns, but you can chain several filters before breaking down. --- # Concrete use cases A few examples of analyses possible with your analytical dimensions: * **Break down MRR growth by geography** to identify the most dynamic areas. * **Analyze churn by product** to spot underperforming offers. * **Compare ARPA by customer category** to understand purchasing behaviors. * **Measure retention by acquisition channel** to adjust your marketing strategy. * The HR company **Octime** took full advantage of filters and cohort breakdown in Fincome to structure its SaaS growth. By analyzing its key indicators by time cohorts, the team was able to track the evolution of MRR, retention, and customer expansion according to the acquisition date. > Result: Octime identified the best-performing cohorts, optimized its pricing, and improved collaboration between the Finance and Product teams. > 🔗 *Read the full story:* [Structuring the growth of an HR SaaS – Octime x Fincome](https://www.fincome.co/fr/customers-stories/structurer-croissance-saas-rh-octime-fincome)