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Leak 04 · Pricing & Margin - Inconsistent pricing across similar customers

Two customers of the same size, buying the same item in the same quantity, pay prices that differ by 20%. Not by design. By accumulation.

Diagnostic note. Symptoms, required records, an initial check, and possible fixes. This shorter note does not include a full worked example.

What is it?

Prices for similar customers drift apart through years of individual quotes, special deals, and different salespeople with different habits. The spread is invisible in aggregate margin and only appears when you line customers up side by side. The low end of the spread is usually where the money is.

Family
Pricing & Margin
Primary owner
Pricing Manager
Secondary owners
VP Sales, Branch Managers
Primary impact
Gross margin
Typical data source
ERP invoice lines, customer master
Detection difficulty
30-day measurability

Ask yourself

For your top 50 items, do customers of similar size and type pay within a defined band of each other?

Yes, partially, no, or don’t know. “Don’t know” is the most useful answer, because it points at the test below.

What does it look like?

Warning signs. None of these proves the leak exists. They tell you where to look.

  • Wide price ranges on the same item at similar quantities across customers of the same segment.
  • Salespeople who cannot say what a “normal” price is for a common item.
  • Customers who discover a peer’s price and ask for it.

What data do I need?

The minimum viable set. Most of it is already in your ERP.

Field
Invoice line: customer, item, quantity, unit price, date
Customer segment or size band
Salesperson and branch

The initial check

Start with a small sample. Gathering the exports, agreements, or observations is separate from running the check; agree that work with the person who owns the records.

  1. 1Pick your top ten items by revenue.
  2. 2For each, list every customer who bought it in the last quarter with quantity and unit price.
  3. 3Group by customer size band. Within each band, note the highest and lowest price and the spread as a percentage of the median.
Spread % = (highest price − lowest price) ÷ median price, within one size band

Then ask one question: Can anyone explain the bottom three prices in each band? If the answer is “history,” that is the leak.

How much could it be costing us?

A conservative range, not a headline. The goal is a number management can trust enough to investigate.

Σ over below-band customers of (band floor price − actual price) × annual units × realistic recovery rate

Common root causes

Fixes fall into three layers. Not every problem needs software, and almost none needs AI first.

Process
No defined price bands by segment, so every price is negotiated from scratch.
Data
Customer segmentation is missing or stale, so “similar customers” cannot be identified in the system.
Technology
The quoting screen shows no reference to what comparable customers pay.

What should we do?

Start with the simplest intervention that could solve it. Move down the list only if the one above is not enough.

  1. Level 1

    Visibility

    A price-dispersion report for the top 100 items, by customer segment.

  2. Level 2

    Guardrails

    Published floor and target prices by segment, with approval required below the floor.

  3. Level 3

    Workflow

    Show comparable-customer prices inside the quote screen at the moment a price is entered.

Where AI helps

  • Clustering customers into segments when the master data does not carry a usable one.
  • Surfacing comparable transactions during quoting.

Where AI probably doesn’t

Defining what a fair price band is for each segment is a management decision, not a model output.

Before you call it a leak

  • Some spread is legitimate: service levels, payment terms, freight arrangements, and volume commitments differ. Normalize for those before calling a low price a leak.

Think this might be happening in your business?

Turn the finding into a next step.

If the numbers say there is something there, send us what you found and we will help you decide whether it is worth a full investigation. No transaction files needed for that conversation.

Talk through a workflow

Let’s start with one thing.

What would better performance look like?

Bring a result you want to improve, a symptom, or a workflow you already understand. You do not need to know the bottleneck yet. We’ll help choose what to investigate first.

No transaction files needed for the first conversation.