One MRR the whole board agrees on
Billing, CRM and product usage joined once, in a warehouse you already run. MRR, ARPU, churn, retention, LTV and CAC with one written definition each, and plan-versus-actual by team without a week of month-end work.
For founders, CFOs and RevOps leads of B2B SaaS companies past product-market fit.
If this sounds like your week
- Finance, sales and marketing each report a different MRR. The board asks which one is right, and there is no answer.
- Churn is a spreadsheet someone updates by hand. You can’t slice it by cohort, plan or acquisition channel.
- Billing, the CRM and product usage live in three systems nobody has joined, so LTV and CAC are guesses.
- Plan versus actual by team takes a week of manual work at every month end.
- Sales comp and team KPIs get argued about every quarter because there is no agreed source of truth.
- The CRM is full of duplicates and dead accounts, and every report inherits the mess.
What gets built
- Sources
- Billing and subscription data, CRM, customer activity and product usage, marketing and campaign data.
- billing exports, CRM data, REST APIs, Google Analytics, Google Ads
- Warehouse
- PostgreSQL or the warehouse you already run, with automated preparation in SQL and Power Query; cleanup of duplicates, inconsistencies and incorrect master data. ClickHouse and dbt if the volume calls for it.
- PostgreSQL, SQL, Power Query (M), ClickHouse, dbt
- Data model
- One metric layer with formal definitions for MRR, ARPU, churn, retention, LTV, CAC, plan-versus-actual and cohorts; month-over-month, year-over-year and rolling periods; Row-Level Security by role and department.
- DAX, Power Query (M), SQL
- Reporting
- Executive dashboards; marketing analytics (campaign performance, lead efficiency, acquisition and retention); sales analytics (funnel, conversions, revenue attribution, deal efficiency); employee KPI dashboards for sales and operations, published through Power BI Service with Gateway refresh.
- Power BI Desktop, Service, Gateway
Work I can describe
For a B2B SaaS company selling subscription services to business clients, I built the analytical and reporting layer for subscriptions, revenue, customer activity and operations. The Power BI data model combined billing, subscriptions, CRM, customer activity and marketing data; the DAX metric layer covered MRR, ARPU, churn, retention, LTV, plan-versus-actual and cohort analysis, with month-over-month, year-over-year and rolling-period logic. On top of it: marketing analytics (campaign performance, lead efficiency, acquisition and retention metrics), sales analytics (funnel performance, conversions, revenue attribution, deal efficiency) and employee KPI dashboards for sales and operational teams. The work included data-quality analysis and database cleanup of duplicates, inconsistencies and incorrect master data, and model optimization for performance and stable refresh, delivered to management as executive-level dashboards.
Clients are not named.
How we start
- I
Discovery call
The board pack: which metrics are disputed, and which systems each number comes from.
- II
Data audit
Billing, CRM and usage: duplicates, dead accounts, and the definitions each team is using today.
- III
Model, reporting, handover
A metric layer agreed with finance and sales in writing; then the dashboards; then documentation, scheduled refresh and monitoring so your team runs it.
Send the board pack nobody agrees on.
Attach the three MRR figures and say which system each one comes from. That is enough for a first call.
Email dauren.m@lief.devEmail Dauren