Can an API Reveal Who Your Most Profitable Customer Really Is?

For years, Managed Print Services (MPS) providers have relied on metrics such as monthly revenue, page volume, and cost per page to measure the success of a contract. And it makes sense: these figures are easy to obtain and allow companies to compare customers quickly.

But there is a problem. None of these metrics, on their own, answer the most important question for any business:

How much money does this customer actually contribute to the bottom line?

Imagine three MPS contracts. All three generate exactly $8,500 per month.

At first glance, they might appear to be customers of similar value. However, once we factor in consumables, technical service, parts, logistics, equipment, and other contract-related costs, three completely different realities emerge.

All three generate exactly the same revenue, yet their financial results are dramatically different. Customer A delivers an operating profit of $5,500 and a 64.7% margin. Customer B generates $3,350 and a 39.4% margin, while Customer C retains only $1,100 and a 12.9% margin.

The KPIs reveal the difference from another perspective. Profit per device drops from $114.58 for Customer A to just $24.44 for Customer C. On a volume basis, profit per 1,000 pages falls from $29.57 to $5.56.

Revenue tells us how much money comes in. Profitability requires understanding how much money is left.

The Problem Is Not a Lack of Data

Most MPS providers have access to enormous amounts of information. Every day, their platforms receive data on meters, consumables, alerts, devices, service incidents, replacements, and printing behavior.

At the same time, other business systems contain equally important information. The ERP holds contracts, billing, inventory costs, products, parts, labor, and logistics. The help desk may track the time spent on each service incident. Finance knows the revenue and costs. Operations knows the devices.

Each system knows one part of the story.

The problem begins when no one can see the complete picture.

From Monitoring Devices to Monitoring Profitability

An MPS platform can tell us that a device printed 10,000 pages, used a certain percentage of toner, and generated three service incidents during the month. But those data points take on a completely different meaning when they are connected to financial information.

If we also know the revenue generated by those pages, average print coverage, actual toner consumption cost, parts used, technician hours, travel expenses, and equipment-related costs, those same 10,000 pages begin to tell a financial story.

We can then calculate a much more important metric:

Cost-to-Serve: how much it actually costs to maintain and support a contract.

In simplified terms:

Contract Revenue − Cost-to-Serve = Operating Profit

This is precisely where integrating operational and financial information begins to change the way an MPS business is managed.

Where Is the Margin Going?

Let’s return to Customer C. Its $8,500 in monthly revenue comes from equipment rental, B&W printing, color printing, and other services. But behind that revenue is a considerable cost structure.

The analysis shows that toner, consumables, and on-site technical service alone account for $4,100 per month, more than half of the total cost of supporting the contract.

This allows us to turn a financial question — why do we have only a 12.9% margin? — into much more specific operational questions: Why is this customer consuming so much toner? Why does it require so many on-site service visits? Is a particular group of devices driving the variance? Does the contract pricing still reflect the actual behavior of the fleet?

This is where device-generated data begins to deliver real financial value.

The Hidden Cost of Consumables

Page volume remains one of the fundamental metrics in MPS. But two customers with similar print volumes do not necessarily have similar costs.

Customer A prints 186,000 pages per month, while Customer C prints 198,000. The difference is only 12,000 pages. Yet monthly consumables cost increases from $920 to $2,450, approximately 166%.

One variable worth examining is average color coverage. In this scenario, it increases from 6.2% for Customer A to 18.7% for Customer C. Print coverage is not the only factor that determines toner consumption, but it can become an important variable when investigating variances between expected yield and the actual cost of a contract.

We also see differences in other operational metrics. Customer C records 37 toner replacements and nine premature replacements, compared with 14 and one, respectively, for Customer A. This is why meter data alone cannot provide a complete understanding of a contract’s financial performance.

From Expected Cost to Actual Cost

Suppose that when Customer C’s contract was priced, monthly consumables costs were projected at $1,400, but the actual cost reached $2,450.

The variance would be:

+$1,050 per month / +75% above expected cost

If that variance continued for twelve months, it would represent $12,600 in additional unplanned costs.

A device should not only tell us how much it printed. We need to understand how it printed and how much those pages actually cost to produce.

Not Every Service Call Costs the Same

There is another factor that can quietly erode profitability: technical service. Simply counting service incidents is not enough.

An issue resolved remotely in 15 minutes does not have the same financial impact as dispatching a technician, using replacement parts, and spending several hours on travel and repair.

The three contracts once again show significant differences. Customer A records only two on-site visits and a service cost of $8.96 per device. Customer C requires 21 on-site visits and reaches a service cost of $52 per device.

In total, Customer C generates 29 incidents, accumulates 42 technician hours, and incurs $750 in parts and $690 in travel costs. Its total monthly service cost reaches $2,340.

There is another important difference: Customer A resolves 75% of its incidents remotely, while Customer C achieves only 28%. From a technical perspective, these metrics describe service activity; from a financial perspective, they describe completely different cost structures.

This is why it is useful to incorporate KPIs such as average cost per incident, service cost per device, technician hours per device, remote resolution rate, repeat incidents, Mean Time to Repair (MTTR), parts costs, and travel expenses.

The objective is no longer simply to know how many service calls a customer generates. The objective is to understand how much those calls cost to resolve.

From Contract Profitability to Device Profitability

The same analysis can be taken to an even more granular level. A contract may be profitable overall while still containing individual devices that operate at a loss.

Imagine, for example, a device that generates $390 in monthly revenue but incurs $170 in consumables, $220 in service, and another $80 in associated costs. The result is a monthly loss of $80 and a -21% margin.

The device generates revenue. But it also generates losses.

That discovery allows us to investigate much more specific questions: Is the device handling too much volume for its model? Is its coverage higher than expected? Is toner being replaced prematurely? Does it generate too many service incidents? Should it be replaced? Should some of its volume be redirected to another device? Is the established cost per page still appropriate?

Integration therefore begins to produce something far more important than data.

It produces decisions.

From Analyzing One Contract to Analyzing the Entire Portfolio

Now let’s expand the analysis. Instead of looking at only three customers, we can compare all contracts using two basic metrics:

X-axis: Monthly Revenue

Y-axis: Operating Margin

This type of analysis allows contracts to be classified according to their financial performance. Strategic accounts combine high revenue with healthy margins, while efficient accounts generate less revenue but maintain strong profitability.

At the other end of the spectrum are contracts that require review or renegotiation. And there is one category that deserves special attention:

High-Revenue, Low-Margin Accounts

These are customers that may appear among the organization’s most important accounts when ranked solely by revenue, but whose operating costs consume a significant portion of that revenue.

For example, a contract generating $15,000 per month at a 10% margin produces $1,500 in profit. Another contract generating $7,000 at a 40% margin produces $2,800.

The second contract generates less than half the revenue, yet produces $1,300 more in monthly profit.

The customer that generates the most revenue is not necessarily the customer that creates the most value.

An API Does More Than Connect Systems. It Connects Decisions.

At this point, the role of a REST API takes on a different meaning. It is not simply about allowing two applications to exchange information. It is about combining data that, on its own, tells only part of the story.

An MPS platform such as Princity can provide operational information related to:

Devices → Meters → Consumables → Coverage → Alerts → Events

Through its REST API, this information can be integrated with an ERP such as Odoo or other business platforms that contain:

Customers → Contracts → Billing → Inventory → Costs → Products → Logistics

A Business Intelligence or analytics layer can combine these sources to calculate metrics such as:

Cost-to-Serve → Margin → Profit per Device → Cost per 1,000 Pages → Consumables Efficiency → Service Cost → Profitability Trend

Those metrics can ultimately drive actions:

Review Pricing → Replace Equipment → Optimize Consumables → Investigate Incidents → Improve Remote Support → Renegotiate Contracts

Princity knows what is happening across the fleet. The ERP knows what is happening financially.

Integration allows the organization to understand what is happening with the business.

Integration Does Not Mean Replacing Everything

Connecting an MPS platform to an ERP does not necessarily mean starting with a large-scale project. An integration strategy can be developed progressively.

Phase One: Customer → Contract → Device → Meters

Phase Two: Consumables → Incidents → Inventory → Service

Phase Three: Costs → Automation → KPIs → Profitability

This approach allows organizations to achieve results gradually and expand the integration as business requirements evolve. Not every organization needs to begin by calculating dozens of metrics.

In many cases, starting with Cost-to-Serve, margin by contract, consumables cost, and service cost can uncover opportunities that were previously hidden.

Security Is Also Part of Integration

Moving information between systems requires more than connectivity. A modern architecture should consider authentication, authorization, encryption, identity management, access control, and transaction traceability.

APIs are part of an organization’s technology infrastructure and should be protected accordingly. Integration is not simply about moving data; it must also ensure that the data remains protected.

Knowing Current Profitability Is Not Enough

There is one final dimension to consider. A contract may be profitable today while its profitability is gradually deteriorating.

Imagine a customer whose monthly revenue remains around $8,500. In January, the contract generates $8,300 in revenue and $4,900 in costs, resulting in a 41% margin. Seven months later, revenue remains virtually unchanged at $8,500. But costs have increased to $7,400, reducing the margin to only 12.9%.

If we look only at revenue, the contract appears stable. Financially, something very different is happening.

Integration therefore allows us to move from asking “Is this contract profitable?” to a much more strategic question:

Is its profitability increasing or decreasing, and what is driving the change?

The Future of MPS Is About Understanding the Entire Operation

Meters, toner levels, and alerts remain essential, but they represent only part of the information required to manage a service business.

When operational information can be connected to financial data, new perspectives emerge around contract profitability, device profitability, Cost-to-Serve, consumables efficiency, print coverage, service cost, SLA performance, and margin trends.

Monitoring was the beginning.

Integration turns operational data into business intelligence.

Conclusion: Seeing the Complete Picture

Let’s return one last time to our three customers. All three generated exactly $8,500 per month, but after their costs were factored in, the results were completely different:

Customer A → $5,500 Profit → 64.7% Margin

Customer B → $3,350 Profit → 39.4% Margin

Customer C → $1,100 Profit → 12.9% Margin

From a revenue perspective, they appeared almost identical. From a profitability perspective, they were completely different businesses.

Identifying that difference requires more than knowing how many pages were printed. It requires connecting device data with consumables, coverage, service, inventory, logistics, contracts, and financial information.

In that context, a REST API is no longer simply a technical resource. It becomes the bridge between print operations and business intelligence.

Because the real competitive advantage is not in collecting more data.

It is in seeing the complete picture and turning that information into better decisions.

The customers, contracts, financial figures, and KPIs used in this article are illustrative scenarios created to demonstrate potential profitability analysis models within an MPS operation.