PROFIT & GROWTH ANALYTICS
See why your revenue is declining, and at which customers.
A decline in the annual figures doesn't tell you where it comes from. In four to six weeks, we show how much of it comes from customers who have left, how much from customers who buy less, and how much from price and product mix. Per customer, per product group and per salesperson.
Revenue decline broken down in euros: lost customers, volume, price and mix
Lost and shrinking customers by name, with their salesperson
Power BI report in your own environment, no vendor lock-in
Fixed price upfront: Data Quick Scan €3,500, Revenue Diagnostic from €24,000 excl. VAT
We never share your data with third parties
Why a revenue decline stays unexplained for so long
Revenue is usually tracked as one number: this month against the same month last year. When that number drops, everyone has an explanation. Sales points to price pressure, purchasing to the mix, management to the market. All three may be right, and that is exactly the problem: in the total, the causes are mixed together. A customer who has left, a customer who buys half as much and a customer who has switched to a cheaper item all cost revenue, but each calls for a different conversation. Revenue Diagnostic separates them: how much of the decline comes from where, in euros, with the customer names attached.
What customers recognize
"Everyone thought we were losing customers. That turned out to be minor. Our regular customers had simply started buying cheaper products."
Client, anonymized
Looking at the total, or at what's behind it
The old approach
Monthly revenue against last year, followed by the discussion
"It's the market" as an explanation nobody tests
Price, volume and mix combined in one number
A customer only stands out once they are gone completely
Slowly shrinking customers stay under the radar
Salespeople assessed on revenue, not on what's left of it
The order book sits in a separate overview
Nobody sees how dependent revenue is becoming on a few large customers
The Novarix approach
Revenue difference in euros per cause: lost customers, volume, price, mix and currency
Lost, shrinking and stable customers by name
Shrinkage visible while the customer is still ordering
New customers by starting year: how many are still ordering after one, two and three years
Revenue and margin per salesperson, over multiple years
Order book through the end of next year alongside current revenue
Dependency on the largest customers over the years
Daily refresh, immediate alerts
Our approach in four phases
From initial data assessment to delivered report: four phases, four to six weeks, fixed price. No surprises along the way.
PHASE 0 - BEFORE THE PROJECT
Data Quick Scan
Assessment of transaction, order, customer and item data
Check whether the history goes back far enough: at least three years
Written advice + quote for the main package
Amount credited if you proceed
PHASE 1 - WEEK 2-3
Build data model
Load transaction, customer and item data
Record each customer's first order and their development since
Split the revenue difference across lost customers, volume, price, mix and currency
Data model ready for daily refresh
PHASE 2 - WEEK 4
Analysis and validation
Identify lost, shrinking and stable customers
Revenue and margin per salesperson over multiple years
Order book and dependency on the largest customers
Review interim results
PHASE 3 - WEEK 5-6
Delivery and handover
Power BI report in your own environment
Management presentation with the five key findings and recommended actions
Documentation of model, calculation rules and assumptions
Two weeks of support, plus an intake for optional ongoing guidance
Why Novarix for a revenue analysis
We build a diagnosis that settles the discussion about the revenue decline: an amount per cause, and for each amount the customers behind it. Sales knows whom to visit, and management sees whether it's about price, product range or customer retention.
The methodology comes from practice: we work with sales and ERP data from B2B distributors and manufacturers in four countries. Not a dashboard with a downward line, but an explanation per customer.
We never share your data with third parties
Fixed price upfront
No open-ended commitment, no hourly billing. The price is fixed before we start.
Your own environment
The report runs in your own Power BI. Model and data are yours, no vendor lock-in.
Proven methodology
Developed and running live at multiple B2B organizations.
Concrete outcome
Revenue difference per cause in euros, with the customer names attached.
Short turnaround time
Four to six weeks from start to delivered report.
Optional guidance
After delivery, we can act as your sounding board every month.
Package and investment
Package contents
Power BI report with six analyses at customer level
Revenue difference split across lost customers, volume, price, mix and currency
Lost, shrinking and stable customers by name
Revenue and margin per salesperson, over multiple years
Order book through the end of next year and dependency on the largest customers
Management presentation with the five key findings and recommended actions
Data model ready for daily refresh, including documentation
Two weeks of support
Investment
Two steps:
1
Data Quick Scan - entry point
€3,500
Two-day data assessment. Every diagnosis starts with this: so it's clear upfront whether the data can support the analysis. Credited if you proceed.
2
Main package - fixed price
From €24,000
excl. VAT, starting price for companies up to €20 million in revenue, final price after the Quick Scan.
Why this pays off
The diagnosis shows per cause, in euros, where the revenue went and at which customers the conversation should start. This way the investment is measured against concrete amounts: not a cost item, but measurable returns.
Customer experiences
Frequently asked questions
Answers to your questions.
Questions we often receive before starting a Revenue Diagnostic project.
We never share your data with third parties
Which organizations is Revenue Diagnostic suitable for?
For B2B distributors and manufacturers whose revenue is declining or flat, where nobody can say exactly why. Typically companies with €5 to €100 million in turnover, with a Power BI environment or willingness to set one up.