Pricing
A model you can trust — even with heterogeneous portfolios.
Thousands of SKUs, customer segments, contractually locked prices, new products without historical data. Aggregate models hand you average values that do not hold up in detail — and that you cannot defend in front of sales.
You know this
Data collection has displaced analysis.
Your day begins with spreadsheets. It ends with spreadsheets. Somewhere in between you were meant to do the analysis.
Price lists that have grown over years. Contract prices that blur how much room is left. SKUs with barely any historical data. And models that give you a number — without explaining why.
Model quality does not only determine the number. It determines whether the number has any effect.
Predictive Portfolio Pricing
Predictive. Explainable. Defensible.
01
Heterogeneous portfolio diagnostics
Model quality visible per cluster. You see where the model holds firm and where the data is thinner. No false precision — and no blanket beauty of aggregates.
02
New-product pricing
New products without historical price data. Valento draws on structural similarities to existing SKUs and external market data — and shows you the range of uncertainty alongside it.
03
Contract-aware margin calculation
What is genuinely movable revenue — and what is contractually locked? The separation that makes ROI calculations and price adjustment scenarios reliable in the first place.
04
Explainability for every recommendation
Every price recommendation comes with a rationale — at cluster, SKU and customer level. You can defend it in front of sales and in front of management without reaching into a model black box.
Platform stage
Five phases. After each one you decide whether the next follows.
The Margin Scan is a one-off snapshot taken from a data export. The platform works differently: on a live connection to your order and invoice data. That is the difference between looking once and being told proactively, before something happens. What the connection involves — interface, frequency, scope of data — we clarify before phase 01, not after. Each phase works on its own; none assumes you will book the next.
01
Visibility
What is happening to my margin right now?
Margin development per article, customer and site — not as a quarterly report but continuously. You see erosion while it happens instead of reconstructing it at year-end.
The problem becomes visible. What you do about it is your call.
02
Forecasting
Where is this heading for trouble?
Cost trends are projected forward, as a range rather than a single number. Articles whose costs rise faster than their price surface before they break through the floor.
The rear-view mirror becomes an early-warning indicator.
03
Pricing logic
What would the right price be?
Target margin and price floor per article and customer segment, with full cost transparency and a traceable derivation. What is genuinely movable stays separated from what is contractually locked.
We do not decide the price. We supply the maths you decide it with.
04
Simulation
What happens if conditions turn?
Material shock, tariffs, exchange rates, wage round: you lay a scenario over the entire portfolio and see which articles fall below target margin, which turn unprofitable, and how much price you need to hold the line.
The answer for your shareholders or advisory board takes minutes instead of weeks.
05
Automation
Who is watching when nobody has time?
The system checks every order against cost forecast, price floor and customer development — and speaks up by itself. Cost threshold crossed, order below floor, customer margin tipping.
In phase 1 you have to find the problem. In phase 5 it finds you.
Model-based recommendations from your data — not a guaranteed outcome. The decision and the responsibility remain yours.
From real data · anonymised
76 margin-loss products — separated into strategy and erosion for the first time.
In one case study we identified 76 products with a margin-loss pattern. Before Valento, all 76 simply carried on without any distinction — each with an employee who kept “his reason” for the low price in his head.
The model separates two groups: deliberately strategically priced products (market entry, key account, cross-selling lever) — and unintended erosion. The former stay where they are. The latter are the actual lever.
The separation is not a reporting feature. It is the basis on which a pricing manager can formulate recommendations that ease the conversation between controlling and sales.
Three steps, full control
How it works.
01
30-minute conversation
We walk through the methodology using typical portfolio data. No sales slides.
02
Margin Scan
Two short appointments, one pseudonymised data export. Your portfolio, your cluster diagnostics. Per cluster, you see where the model holds and where your data needs sharpening.
03
Platform
Ongoing price recommendations with a rationale, new-product pricing, contract-aware margin calculation. You decide the scope.
Next step
30 minutes on the methodology.
We show how the model handles heterogeneous portfolios — using real cluster examples. You decide whether a Margin Scan on your portfolio makes sense.
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