Board revenue pack
The recurring set of numbers leadership needs, tied back to the model that produces them.
B2B SaaS
Revenue reporting when the numbers do not agree
SaaS teams often have a defensible number in the CRM, another in billing, and a third in finance. We build the layer that explains the gap and gives the business one place to start.
Common sources
- Revenue systems
- Salesforce · HubSpot · Stripe
- Data layer
- Snowflake · dbt · Airflow
- Reporting
- Tableau · Power BI
The problem
What SaaS teams usually notice first
The visible issue is a dashboard nobody quite trusts. The cause is usually a set of definitions that changed in different places at different times.
Pipeline does not tie to bookings
Sales can explain the forecast and finance can explain the closed number, but the bridge between them is rebuilt by hand each month.
ARR and MRR rules drift
Discounts, upgrades, pauses and churn rules live in spreadsheets or in tool logic that nobody wants to touch.
Cohorts are hard to defend
Retention and expansion analysis depends on the customer record, and that record is different in each source system.
The approach
Put the revenue logic in one tested layer
The work starts with the disputed number. From there we agree the metric, trace the source fields, build the model, and document the rules so the same question produces the same answer next month.
Definitions first
What counts as pipeline, booking, churn, expansion and active revenue is written down before the dashboard is designed.
Reconciliation built in
The model shows where CRM, billing and finance differ, so a variance becomes an explanation rather than a meeting.
Handover included
Tests, docs and ownership are part of the delivery, so your team can change the model without calling us back for every field.
What the page is meant to qualify
These are not packages. They are the common entry points behind SaaS work.
RevOps model clean-up
CRM, billing and warehouse rules brought into one place, with tests for the definitions people argue about most.
Customer and cohort view
A shared customer grain for retention, expansion and account health reporting.
What clients say
Igor was part of a consultancy project focused at expansion for FirstAgendas products in USA. I had the pleasure of taking part in both interviews and workshops facilitated by the group.
Igor had a very professional approach to the assignment and they provided us with great insights and recommendations to the upcoming expansion. Some of the findings have already been implemented and others will follow.
Troels Skovsbøll Emborg
Head of Marketing, FirstAgenda
I highly recommend Igor for his exceptional skills in Tableau, SQL, ELT and his quick ability to pickup new things. His expertise in these areas, combined with his strong analytical mindset, makes him an invaluable asset in any data-driven project.
Igor consistently delivers high-quality work and demonstrates a strong commitment to continuous learning and improvement. He is a dedicated professional with a passion for leveraging data to drive actionable insights. It has been a pleasure and privilege to work with Igor, hope we will continue to work together for many more years.
Vinay Katdare
Tech Lead, NewPage Solutions
It was my huge pleasure to work with Igor on a data project where he was delivering different dashboards over a few weeks remotely. The scope of the work was constantly changing but thanks to Igor's professional approach he mastered it perfectly.
His strength: organized, clear, on top of things, communicates well, proactive and involves stakeholders when necessary. Its a great feeling to know that your projects are in good hands - in those of Igor.
Zdenka de Booij
Account Executive, InterWorks
How an engagement usually starts
Pick the number in dispute
We start with one report or metric, because a concrete disagreement is faster than a long discovery phase.
Trace it back to source
Fields, joins and business rules are mapped until the gap has a name.
Build the governed version
The agreed definition moves into dbt and the dashboard reads from that tested model.
Leave the change path behind
Documentation and tests show what to edit when the pricing model or sales process changes.
Questions SaaS teams ask early
Do we need to replace the CRM reports?
Usually no. CRM reports are useful for sales activity. The warehouse is where cross-system revenue logic belongs.
Can you work with messy historical data?
Yes, if we agree what the history is allowed to answer. Some questions need a clean rule from today rather than a false answer for the past.
Do you only work with SaaS?
No, but B2B SaaS revenue data is where most of our work starts. We take pharma and ecommerce work where the problem is the same: important numbers split across systems that disagree.
Next step
Which number do you not trust?
Bring the report nobody trusts. We will tell you what is actually wrong underneath it.
Thirty minutes, straight to the problem. No deck, no pitch, and a written summary afterwards either way.