Cubegle
Data • AI • Cloud
Case Study

Subscription & Product Analytics for B2B SaaS

A SaaS organisation needed clear visibility into MRR, churn, activation, and product usage — plus analytics embedded directly into their customer portal.

Overview

The client operated a B2B SaaS platform but lacked a reliable subscription analytics layer. Multiple tools tracked events and billing, but there was no unified view.

Problem

  • MRR and churn metrics were inconsistent across teams.
  • Difficult to segment customers by usage, plan, or lifecycle stage.
  • Stakeholders relied on spreadsheets and manual exports.
  • No analytics inside the customer-facing product.

Objectives

  • Define a single source of truth for subscription metrics.
  • Model cohorts, retention, and customer health scores.
  • Expose key metrics to internal and external users.
SaaS Analytics Architecture
Snapshot

Domain: B2B SaaS
Scope: Subscription analytics & embedded dashboards
Outcome: Unified MRR/churn view & in-app analytics

Solution

Cubegle implemented a subscription analytics model that centralised billing, product usage, and CRM data into a clean, consistent schema.

Key Workstreams

  • Standard MRR, ARR, churn, and expansion metrics.
  • Cohort and retention modelling.
  • Customer health scoring (usage + support + plan).
  • Embedded dashboards inside the SaaS product.

Architecture (High Level)

Events and billing data were normalised into a subscription layer which fed:

  • Internal BI dashboards for product, marketing, and finance.
  • Customer-facing analytics surface within the SaaS UI.
Tech Stack

Cloud DWH, ETL/ELT tools, BI tool (e.g. Power BI/Tableau/custom UI), embedded analytics framework, identity/permissions integration.

Cloud DWH ETL/ELT Power BI Analytics API

Impact

Unified Metrics Cohort Analysis In-App Analytics Better Alignment
  • Leadership gained a consistent view of subscription health.
  • Product teams could track feature adoption by cohort and segment.
  • Customers saw clear value through in-app analytics and reports.
  • Better alignment between sales, marketing, and product decisions.
Where This Applies

Ideal for SaaS businesses with growing customer bases and fragmented analytics, looking for robust subscription intelligence and product usage insights.