Martin knows exactly who his biggest customer is.
Alpha Retail buys approximately:
€240,000 per year
No other customer comes close.
When Alpha calls, Martin’s team reacts quickly.
Special request?
They make it happen.
Urgent delivery?
They reorganize the schedule.
Additional discount?
Martin usually agrees.
After all, losing a customer worth €240,000 would be painful.
Then Martin’s accountant asks a simple question:
„How much do we actually earn from Alpha?“
Martin answers immediately:
„They’re our biggest customer.“
That was not the question.
💰 Revenue Measures Size, Not Customer Quality
Martin pulls the numbers.
Annual Alpha Retail revenue:
€240,000
Direct product cost:
€144,000
That leaves:
€96,000
At first glance, Alpha looks excellent.
A 40% amount remains after product cost.
But Alpha does not behave like an ordinary customer.
Its purchasing department negotiates aggressively.
It requires special packaging.
Orders frequently change after confirmation.
Invoices are paid slowly.
Its employees call Martin’s support team constantly.
Several deliveries each year need to be expedited.
None of those costs disappears simply because the sales report says:
€240,000
📊 Martin Builds the Customer P&L He Never Had
He starts adding costs that can reasonably be connected to Alpha.
| Alpha Retail | Annual amount |
|---|---|
| Revenue | €240,000 |
| Product/direct cost | -€144,000 |
| Special discounts/rebates | -€12,000 |
| Special packaging | -€5,400 |
| Expedited freight | -€7,200 |
| Returns/claims | -€4,800 |
| Dedicated support/admin time | -€13,500 |
| Remaining contribution | €53,100 |
Alpha still contributes money.
This is important.
Martin has not discovered that his largest customer is automatically bad.
He has discovered that the economic relationship is very different from:
€240,000 revenue → €96,000 contribution
After the additional customer-specific burden:
€53,100
remains.
That difference is:
€42,900
Large enough to change decisions.
🧮 Then Martin Compares Alpha With a Much Smaller Customer
Beta Manufacturing buys only:
€130,000 per year
Martin has always considered Beta a secondary account.
Its direct product cost is:
€78,000
Initial contribution:
€52,000
Less than Alpha’s €96,000.
But Beta behaves differently.
Orders are standardized.
Forecasts are reliable.
There are few changes.
Invoices are paid on time.
Support requirements are low.
Annual customer-specific costs:
| Beta Manufacturing | Annual amount |
|---|---|
| Revenue | €130,000 |
| Product/direct cost | -€78,000 |
| Special discounts/rebates | -€2,000 |
| Special packaging | -€800 |
| Expedited freight | -€600 |
| Returns/claims | -€900 |
| Dedicated support/admin time | -€3,200 |
| Remaining contribution | €44,500 |
Now Martin compares them.
Alpha:
€53,100
Beta:
€44,500
Alpha produces only:
€8,600 more
despite generating:
€110,000 more revenue
That is a completely different picture of the customer base.
⏱️ Revenue Per Customer Can Hide a Capacity Problem
Martin asks his team to estimate how much account-specific time the two customers consume.
Alpha:
620 hours per year
Beta:
145 hours
Now calculate contribution per customer-service/admin hour.
Alpha:
€53,100 ÷ 620 ≈ €85.65 per hour
Beta:
€44,500 ÷ 145 ≈ €306.90 per hour
Martin does not interpret those figures as employee wages.
They are a way of seeing how efficiently a scarce organizational resource is being used.
If the support and account-management team has plenty of spare capacity, Alpha’s workload may be manageable.
If the team is overloaded, the difference becomes strategically important.
🚨 „VIP Customer“ Can Become an Expensive Habit
Alpha has been a customer for eight years.
Over time, Martin’s company has created dozens of exceptions.
Alpha gets:
🔸 custom order forms,
🔸 special packaging,
🔸 different delivery windows,
🔸 manual monthly reports,
🔸 priority support,
🔸 individual invoicing requirements,
🔸 and several products at historic prices.
Nobody deliberately designed this package.
It accumulated.
One request seemed reasonable.
Then another.
Then another.
Each exception was too small to trigger a major discussion.
Together, they created a customer operating model.
This is how a valuable relationship can become expensive without anyone making one obviously bad decision.
📦 The Order Is Profitable — Until the Customer Changes It Three Times
Martin looks at one representative Alpha order.
Order value:
€18,000
Direct cost:
€10,800
Initial contribution:
€7,200
Looks strong.
Then the order changes.
Alpha changes quantities after production planning.
Two employees spend 90 minutes revising documentation.
The warehouse has already prepared part of the shipment.
Packaging is reopened.
A second change arrives the following day.
The delivery date moves forward.
Martin pays an express freight surcharge.
The final economics look different.
Example order
| Item | Amount |
|---|---|
| Initial contribution | €7,200 |
| Change handling | -€260 |
| Repacking/rework | -€310 |
| Express freight | -€680 |
| Additional administration | -€170 |
| Adjusted contribution | €5,780 |
The order is still profitable.
But:
€1,420
of its original contribution disappeared through customer-specific complexity.
That is almost:
20%
of the initial €7,200.
🧠 Martin Stops Calling Every Extra Request „Customer Service“
This is uncomfortable.
Martin prides himself on excellent service.
He does not want his employees to become rigid and unhelpful.
But there is a difference between:
🟢 service that creates customer value
and
🔴 unpriced complexity that consumes resources indefinitely
Suppose Alpha occasionally needs an emergency shipment because one of its own customers has a crisis.
Helping quickly may strengthen the relationship.
That can be excellent service.
But if nearly every order is marked urgent because Alpha knows Martin will always reorganize production for free, urgency has become part of the commercial arrangement.
It simply has no price attached to it.
🚚 One Customer Can Quietly Set the Rules for Everyone Else
Alpha’s urgent orders do not affect only Alpha.
When Martin moves Alpha to the front of the production schedule, another customer’s order moves backward.
When the warehouse handles an emergency shipment, planned work is interrupted.
When support spends two hours creating Alpha’s special report, those employees are unavailable for other customers.
This creates a second-order cost.
It is much harder to measure than freight or packaging.
But Martin can observe it.
During one month, Alpha creates:
11 urgent interventions
The operations manager estimates each interruption causes approximately:
35 minutes
of coordination across several people.
That is:
385 minutes
or:
6 hours 25 minutes
And that is only coordination time.
It excludes the actual additional work.
A customer’s complexity can spread through a company rather than remaining neatly inside one account.
💳 Then Martin Looks at Payment Terms
Alpha has negotiated:
60-day payment terms
Beta pays within:
14 days
Martin has always considered this an accounting detail.
It is actually a financing difference.
Suppose Alpha purchases approximately:
€20,000 per month
and Martin must pay suppliers much earlier.
At any given time, a meaningful amount of Alpha-related cash can be tied up in receivables.
A simplified comparison helps.
Alpha annual revenue:
€240,000
Average daily revenue:
€240,000 ÷ 365 ≈ €658
At 60 days:
€658 × 60 ≈ €39,480
Beta:
€130,000 ÷ 365 ≈ €356 per day
At 14 days:
€356 × 14 ≈ €4,984
These are simplified illustrations rather than exact receivables balances.
But the scale difference is obvious.
Alpha can require Martin to finance far more of the relationship.
💸 Payment Terms Have an Economic Cost
Suppose Martin’s effective cost of short-term business financing is:
7% annually
If approximately €39,480 is tied up because of the payment cycle, a simplified annual financing cost would be around:
€39,480 × 7% ≈ €2,764
That does not mean Martin should automatically add exactly €2,764 to Alpha’s invoice.
The calculation shows that:
„They always pay eventually“
is not the same as:
„Payment timing costs us nothing.“
Capital has a cost.
Cash tied up in Alpha cannot simultaneously fund inventory, payroll, equipment or growth elsewhere.
🟡 A Slow-Paying Customer Can Still Be Excellent
Martin avoids another simplistic rule.
A customer paying after 60 days is not automatically unattractive.
Suppose Alpha:
🟢 orders predictably,
🟢 generates excellent margins,
🟢 rarely complains,
🟢 requires little support,
🟢 and has extremely low credit risk.
Long payment terms may simply be part of a commercially attractive relationship.
Likewise, a customer paying immediately can still be terrible if every order creates losses.
Payment timing is one variable.
Martin is building a complete picture, not searching for a single number that replaces judgment.
📉 Discounts Become More Dangerous When They Attach to the Largest Customer
Alpha asks for another:
3% annual rebate
Martin’s first thought is:
„They buy €240,000. Three percent seems manageable.“
Three percent of revenue is:
€7,200
But Martin should compare that €7,200 with the economic amount that remains after variable and customer-specific costs.
Current adjusted contribution:
€53,100
After another €7,200 rebate:
€45,900
Reduction in adjusted contribution:
€7,200 ÷ €53,100 ≈ 13.6%
A 3% revenue concession reduces the measured contribution by roughly:
13.6%
under these assumptions.
That is why small percentage discounts can create large profit effects.
🔢 How Much More Would Alpha Need to Buy?
Martin considers accepting the rebate if Alpha increases volume.
But „we’ll buy more“ is not enough.
He calculates.
Suppose each additional €100 of sales creates €40 of contribution before the new rebate and other complexity.
A €7,200 concession needs substantial incremental contribution merely to recover the amount given away.
At €40 contribution per €100 of incremental sales:
€7,200 ÷ 40% = €18,000 additional revenue
And that assumes the extra volume does not create:
- additional support,
- overtime,
- expedited freight,
- inventory pressure,
- or another capacity step.
If Alpha’s growth creates those costs, the required additional revenue is higher.
🧑💼 Salespeople Can Be Rewarded for the Wrong Customer
Martin discovers another structural issue.
His sales team receives bonuses primarily for:
revenue won
That makes Alpha look fantastic.
A salesperson who signs a €250,000 account appears more successful than one who signs a €120,000 account.
But what if:
Customer X:
€250,000 revenue → €35,000 adjusted contribution
and
Customer Y:
€120,000 revenue → €48,000 adjusted contribution
The sales incentive and the business economics point in opposite directions.
This does not mean salespeople should be judged on an accounting model they cannot influence.
But if incentives reward revenue while ignoring discounts, payment quality and excessive customization, the company may systematically attract expensive growth.
🧮 Martin Calculates the Cost of Acquisition Too
A new customer can look profitable after the first order while still not having recovered what it cost to win them.
Suppose Martin spends:
€18,000
on a trade fair.
The event produces:
12 new customers
A simplistic acquisition cost would be:
€18,000 ÷ 12 = €1,500 per customer
But those customers are not identical.
Some generate €50,000 annually.
Others place one €800 order and disappear.
Martin therefore does not stop at:
customer acquired
He asks:
How much contribution has this customer generated after the cost of acquiring and serving them?
That makes acquisition economics part of customer profitability rather than a separate marketing vanity metric.
🔁 The First Order Can Be Weak and the Customer Still Valuable
Customer Gamma illustrates the opposite case.
First order revenue:
€3,000
Contribution after direct costs:
€900
Acquisition cost:
€1,200
On the first order:
€900 – €1,200 = -€300
If Martin judges Gamma immediately, the customer looks unprofitable.
But Gamma orders repeatedly.
Over the next twelve months:
Additional adjusted contribution:
€7,600
Now the acquisition cost looks entirely reasonable.
This is why customer profitability needs a time horizon.
The first transaction is not always the relationship.
⚠️ Lifetime Value Can Become Fantasy Very Quickly
Martin’s marketing software displays:
Estimated Customer Lifetime Value: €18,400
That number looks wonderfully precise.
He asks how it was calculated.
The model assumes:
- a five-year relationship,
- stable repeat purchasing,
- constant margin,
- no major increase in service costs,
- and low customer churn.
Those assumptions may be reasonable.
Or they may not.
Martin prefers observed customer cohorts.
If customers acquired three years ago actually show how purchasing, contribution and retention developed over time, he has evidence.
If a brand-new customer is assigned an enormous lifetime value because a formula assumes years of future behavior, Martin treats the number as a scenario rather than cash already earned.
📊 Revenue Ranking vs Profitability Ranking
Martin finally ranks several customers two ways.
| Revenue rank | Customer | Revenue | Adjusted contribution |
|---|---|---|---|
| 1 | Alpha | €240,000 | €53,100 |
| 2 | Delta | €180,000 | €31,000 |
| 3 | Beta | €130,000 | €44,500 |
| 4 | Gamma | €105,000 | €39,000 |
| 5 | Epsilon | €90,000 | €41,000 |
By revenue:
Alpha → Delta → Beta → Gamma → Epsilon
By adjusted contribution:
Alpha → Beta → Epsilon → Gamma → Delta
Epsilon is the smallest customer in the table.
Yet it produces more adjusted contribution than Delta, which generates twice the revenue.
That is the moment Martin realizes his customer leaderboard has been measuring the wrong competition.
🚦 The Question Is Not Which Customers to Fire
Martin does not print the table and call every low-ranked customer.
That would be reckless.
Customer profitability analysis is not a firing list.
A weak result can indicate several different actions.
🔧 simplify the process,
💶 change pricing,
📦 standardize packaging,
🚚 charge for exceptional freight,
⏱️ reduce manual administration,
💳 renegotiate payment terms,
📈 increase minimum order sizes,
or
🤝 deliberately accept lower profitability because the relationship has strategic value.
The purpose is to see the economics clearly enough to make those choices consciously.
Martin’s biggest discovery is not that Alpha is a bad customer.
Alpha isn’t.
It still contributes more money than any other account in his first analysis.
The discovery is that €240,000 of revenue does not entitle Alpha to unlimited complexity for free.
And that changes the next negotiation completely.
📋 ABC Customer Analysis Is Not Enough
Martin’s company already has an ABC customer classification.
It looks professional.
A customers: highest revenue
B customers: medium revenue
C customers: lower revenue
Alpha is obviously an A customer.
Epsilon is classified as C.
But Martin now knows that this ranking answers only:
„Who buys the most?“
It does not answer:
„Who creates the most economic value?“
Consider the two customers again.
| Alpha | Epsilon | |
|---|---|---|
| Revenue | €240,000 | €90,000 |
| Adjusted contribution | €53,100 | €41,000 |
| Contribution / revenue | 22.1% | 45.6% |
| Service complexity | High | Low |
| Payment behavior | 60 days | 14 days |
| Operational disruption | High | Low |
Alpha still produces €12,100 more adjusted contribution.
But it needs €150,000 more revenue to do it.
Calling Alpha „A“ and Epsilon „C“ hides that difference.
Martin keeps his revenue classification because it remains useful for understanding account size.
He simply stops confusing size with quality.
🎯 Strategic Customers Need Their Own Category
Then Martin encounters an account that breaks the profitability ranking in another direction.
Omega Systems generates:
€160,000 revenue
Adjusted annual contribution:
€27,000
That looks weak.
Why keep it?
Because Omega is one of the most respected companies in an industry Martin wants to enter.
The relationship has helped his sales team win three additional customers.
Omega also provides useful product feedback and is willing to participate in case studies.
Martin cannot assign every one of those benefits a precise euro value.
He does not need to pretend he can.
Instead, he labels Omega:
🟡 Strategically important — deliberately lower profitability
The important word is:
deliberately
A company can rationally accept a lower margin from a strategically valuable customer.
The danger begins when every difficult customer is described as „strategic“ simply because nobody wants to confront the economics.
Martin therefore asks:
What specific strategic benefit are we receiving, and is there evidence that it actually occurs?
„Big logo on our customer list“ is not automatically enough.
🏭 The €500,000 Customer That Blocks the Factory
Martin then models a more extreme case.
Imagine a customer generating:
€500,000 annual revenue
Adjusted contribution before capacity effects:
€85,000
That sounds valuable.
But the customer’s customized production occupies:
1,600 hours of a specialized machine
The machine is Martin’s bottleneck.
Other products could use those hours.
Suppose alternative orders generate approximately:
€90 contribution per machine hour
Potential contribution from 1,600 hours:
1,600 × €90 = €144,000
The €500,000 customer generates only:
€85,000
from the same constrained resource.
Difference:
€59,000
Now Martin sees the opportunity cost.
If the machine would otherwise sit idle, the calculation is irrelevant.
There is no €144,000 opportunity waiting outside.
But when Martin has more profitable orders than machine capacity, allocating scarce hours to the wrong customer has a real consequence.
This is why customer profitability becomes especially important when a business is close to capacity.
⏱️ Contribution Per Scarce Resource Changes the Ranking
Martin creates another comparison.
| Customer | Adjusted contribution | Bottleneck hours | Contribution per bottleneck hour |
|---|---|---|---|
| Customer A | €85,000 | 1,600 | €53.13 |
| Customer B | €62,000 | 500 | €124.00 |
| Customer C | €48,000 | 280 | €171.43 |
If machine time is scarce, Customer C suddenly looks extremely attractive.
It produces less total contribution than A.
But each bottleneck hour creates more than three times as much contribution.
This does not mean Martin immediately replaces A with C.
It tells him where pricing or process redesign may be necessary.
💶 Complexity Can Have a Price
Martin returns to Alpha.
For years, the company has absorbed nearly every special request.
He considers a different approach.
Instead of telling Alpha:
„You are too difficult.“
he identifies the activities that create measurable additional cost.
For example:
Standard delivery:
included
Same-day expedited handling:
€95 service charge
Standard packaging:
included
Custom labeling and packaging:
€180 per batch
Standard monthly reporting:
included
Custom reporting format:
€250 per month
Late order changes after production release:
charged according to rework
The objective is not to punish Alpha.
It is to make the commercial model reflect the service model.
If Alpha genuinely values those services, it may happily pay for them.
If it does not value them enough to pay, some unnecessary complexity may disappear.
Both outcomes improve the relationship.
📦 Minimum Order Values Can Solve a Different Problem
Another customer repeatedly places tiny orders.
Average order:
€85
Contribution before processing:
€28
But every order requires:
- order administration,
- picking,
- packing,
- invoicing,
- payment processing,
- and shipment preparation.
Suppose the minimum operational handling burden averages:
€19 per order
Now only:
€9
remains.
Martin does not necessarily need to increase every product price.
He could introduce:
Minimum order value: €150
or:
Small-order handling fee: €12
This targets the actual problem.
The customer is not inherently unprofitable.
The order pattern is.
🧮 Martin Tests the Minimum Order Effect
Suppose a customer currently places:
20 orders × €85 = €1,700 revenue
Operational handling:
20 × €19 = €380
If the same annual demand could realistically be consolidated into:
10 orders × €170
revenue remains:
€1,700
but handling becomes:
10 × €19 = €190
Capacity recovered:
€190 of measured handling cost
plus the time associated with ten avoided order-processing cycles.
Of course, customers may not behave exactly as Martin hopes.
Some may order less.
Some may leave.
That is why he tests the economics rather than assuming every new rule is automatically beneficial.
🤝 Service Levels Make Expectations Visible
Martin’s team has another problem.
Every customer receives roughly the same informal promise:
„We’ll do our best.“
That sounds friendly.
Operationally, it is vague.
A €5,000 annual customer can expect the same emergency response as a €250,000 account because nobody has defined otherwise.
Martin introduces clearer service levels.
Example
| Service | Standard | Priority |
|---|---|---|
| 📩 Response target | Next business day | Within 4 business hours |
| 🚚 Urgent processing | Paid when available | Included allocation |
| 📊 Custom reporting | Extra charge | Selected reports included |
| 👤 Account contact | Shared team | Named contact |
| 🔧 Custom requests | Quoted separately | Defined allowance |
Priority service is not necessarily free.
It can be part of a higher-value commercial agreement.
This does something important:
customer profitability and customer experience stop fighting each other.
The customer knows what is included.
The team knows what it has promised.
📈 Repricing Does Not Require a Dramatic Increase
Martin initially imagines telling Alpha:
„Prices are going up 15%.“
That would be a difficult conversation.
Then he realizes the problem is more targeted.
Alpha’s standard orders are reasonably profitable.
The biggest losses come from:
🔸 historic discounts,
🔸 emergency freight,
🔸 custom packaging,
🔸 order changes,
🔸 and unusually long payment terms.
So he models several smaller changes.
Current adjusted contribution
€53,100
Possible annual improvements:
| Change | Estimated improvement |
|---|---|
| Reduce one historic rebate | +€4,000 |
| Charge part of custom packaging | +€3,200 |
| Recover some expedited freight | +€4,500 |
| Reduce manual reporting | +€2,400 |
| Improve order-change process | +€3,000 |
| Potential improvement | €17,100 |
New illustrative contribution:
€53,100 + €17,100 = €70,200
Revenue barely needs to change.
The economics do.
🔧 Sometimes the Customer Is Not the Problem — Your Process Is
Martin notices something uncomfortable.
His company blames Alpha for dozens of manual tasks.
But several exist because Martin’s own systems are poor.
Alpha sends a spreadsheet.
An employee manually re-enters the data.
Another employee checks it.
A third person converts it into the production system.
Everyone calls Alpha „high maintenance.“
But if an import tool could automate most of that process, the customer may suddenly become much more attractive.
Suppose automation costs:
€8,000
and saves:
18 hours per month
At an internal labor cost of €30 per hour:
18 × €30 × 12 = €6,480 per year
Simple payback:
€8,000 ÷ €6,480 ≈ 1.23 years
After that, the process continues creating capacity.
The correct action was not:
fire Alpha
or even:
charge Alpha more
It was:
fix the process.
🚦 Martin Creates a Customer Profitability Matrix
He now places major accounts into four groups.
| Economically strong | Economically weak | |
|---|---|---|
| Strategically valuable | 🟢 KEEP & GROW | 🟡 FIX / REPRICE |
| Low strategic value | 🟢 KEEP EFFICIENT | 🔴 REPRICE / EXIT |
This creates four different conversations.
🟢 KEEP & GROW
Profitable customers with strong strategic fit.
Martin asks:
How can we serve them even better and responsibly grow the relationship?
🟢 KEEP EFFICIENT
Good economic customers that do not require extensive strategic investment.
Martin protects the relationship without adding unnecessary complexity.
🟡 FIX / REPRICE
Important customers whose economics are weak.
Martin investigates:
pricing,
process,
service scope,
order behavior,
payment terms,
and operational complexity.
These customers deserve repair before rejection.
🔴 REPRICE / EXIT
Weak economics.
High complexity.
Little strategic value.
No convincing path to improvement.
These are the relationships Martin challenges most aggressively.
⚠️ „Exit“ Is the Last Step, Not the First
Martin is cautious with the red category.
Customers are not spreadsheet rows that can be deleted without consequences.
A customer may employ people Martin knows personally.
It may refer business.
It may buy other products through related companies.
Contracts may contain obligations.
Capacity may become empty after the account leaves.
Fixed costs do not disappear automatically.
There may also be reputational consequences.
So Martin asks what happens after the customer leaves.
Suppose a customer contributes:
€25,000
after attributable costs.
The relationship is irritating but still economically positive.
If Martin terminates it and cannot replace the volume, the company may simply lose €25,000.
„Below average profitability“ is not the same as:
„We are better off without this revenue.“
🧮 The Replacement Test
Martin therefore performs a replacement calculation.
Customer Red:
Adjusted contribution:
€30,000
Capacity consumed:
800 hours
Potential replacement business:
€55 contribution per hour
If all 800 hours can realistically be filled:
800 × €55 = €44,000
Potential improvement:
€14,000
That supports an exit discussion.
But suppose Martin can realistically replace only:
200 hours
Replacement contribution:
200 × €55 = €11,000
Losing Red removes €30,000 and replaces only €11,000.
Short-term result:
€19,000 worse
The theoretical opportunity was not real.
Capacity has value only when there is something valuable to do with it.
📊 The Monthly Customer Dashboard Martin Actually Uses
Martin finally creates a dashboard that fits on one page.
| Measure | Question |
|---|---|
| 💰 Revenue | How large is the relationship? |
| 📈 Adjusted contribution | What economic value remains? |
| %️⃣ Contribution rate | How efficiently does revenue convert? |
| ⏱️ Service hours | How much internal capacity is consumed? |
| 📦 Operational complexity | How many exceptions are required? |
| 💳 Payment behavior | How much cash is tied up? |
| ↩️ Claims/returns | What happens after delivery? |
| 🔁 Retention | Does the relationship continue? |
| 🤝 Strategic value | What measurable benefits exist beyond margin? |
| 🚦 Action | Keep / Fix / Reprice / Exit |
Not every customer needs this analysis.
Martin does not calculate the support minutes of someone who buys €80 once per year.
He focuses on:
large accounts, unusually demanding accounts, rapidly growing customers and relationships whose profitability is unclear.
That is where better information can change a meaningful decision.
⏱️ The 10-Minute Customer Check
When Martin reviews an important account, he now asks:
1. 💰 What is the revenue?
Useful — but only the beginning.
2. 📉 What remains after direct costs and customer-specific concessions?
Discounts, rebates, freight, packaging and claims matter.
3. ⏱️ How much unusual work does the customer create?
Support, administration, changes and emergency requests consume capacity.
4. 💳 How does the customer pay?
Payment terms and reliability affect cash.
5. 🏭 Does the account consume a scarce resource?
Machine time, specialist labor or warehouse capacity may change the economics.
6. 🔁 What happens over time?
Repeat purchasing and acquisition cost belong in the relationship calculation.
7. 🤝 Is there genuine strategic value?
Name it.
Do not hide weak economics behind an undefined „strategic“ label.
8. 🔧 Can the problem be fixed?
Process improvement may be better than repricing.
9. 💶 Should complexity be priced?
Exceptional service does not automatically need to be free.
10. 🚦 What action follows?
Keep. Fix. Reprice. Exit.
An analysis that produces no possible action is just another report.
🟢 KEEP
Martin keeps and protects customers that create healthy economic value without consuming disproportionate resources.
For the strongest relationships, he looks for responsible opportunities to grow.
🔧 FIX
The customer is valuable, but the operating model is inefficient.
Martin improves:
processes,
automation,
ordering,
service scope,
or internal workflows.
💶 REPRICE
The customer genuinely requires more resources than the standard commercial model supports.
Martin changes:
prices,
discounts,
minimum orders,
fees,
service levels,
or payment terms.
🔴 EXIT
Only after the previous options fail does Martin seriously consider whether capacity would be better used elsewhere.
And even then, he verifies that the alternative business actually exists.
💼 Alpha Is Still Martin’s Biggest Customer
After all the analysis, something surprising happens.
Martin does not fire Alpha.
Alpha remains his largest customer.
The relationship still creates substantial contribution.
What changes is the next annual negotiation.
Alpha asks for another discount.
Previously, Martin would have looked at:
€240,000 annual revenue
and worried about upsetting such an important account.
Now he brings a different picture to the discussion.
The relationship includes significant custom packaging.
Urgent freight.
Long payment terms.
Manual reporting.
Order changes.
Priority service.
Martin does not accuse Alpha of being a bad customer.
He explains that the current service package and the current commercial terms no longer match.
Some services are simplified.
Some are priced.
One old rebate disappears.
The order-change process is redesigned.
Alpha accepts most of the changes because several of those services genuinely matter to them.
The relationship survives.
Its revenue barely changes.
Its profitability improves.
And Martin learns the lesson hidden inside his customer ranking:
The customer who buys the most is not automatically the customer who deserves the most concessions.
Revenue tells Martin how big the account is.
Customer profitability tells him what the relationship gives back.
A strong business needs to know both.