A machinery customer’s ordering habits are not the same as regular ecommerce habits. What they buy next depends on the machine: its maintenance intervals, its consumables consumption, and whether it is still under warranty, rather than pure browsing or emotional behaviour. Any revenue calculation in industrial sector has to start from the machine, not from the customer. That’s why we are always focusing on the install base (all the base of machines that you’ve already sold) instead of purely customers and their behaviours.
If you manufacture or distribute machinery and don’t know what your installed base should be earning you in parts, consumables and service revenue, this is the calculation that we recommend going through.
We explained why installed base percentage is the main indicator to judge after-sales performance in previous article: After-Sales Performance Metrics: 3 Ways to Measure It.
We didn’t give you the method to calculate it though. Below we show you the real example from a client: machinery distribution company, using three exports most companies already have: the customer list, the machinery list, and the invoice data. Service logs make it even more precise if you have them, but that’s not required at this stage. No platform required, an excel is enough to get the numbers and start thinking on how to improve after-sales in general.
Step 1: Total value of your installed base
Add up the original purchase price of every machine you’ve ever sold that is still in use, active customer or not.
This distributor: 58 machines, 10,57M Eur combined.
Step 2: Your current after-sales performance
Total after-sales spend over the last 12 months, parts, consumables and service labour combined, divided by the installed base value from step 1.
This distributor’s last 12 months: 108 066 Eur
108K / 10,57M = 1,02%.
Checking that spend against company revenue only shows how after-sales-heavy the business is overall. Checking it against installed base value shows how much of the machinery you sold is being really monetized, independent of how new-machine sales performed that year.
Step 3: Your realistic potential, from your own data
The industry benchmark is around 3-5% of initial machine value earned back in after-sales revenue per year. Useful as a first check, but it doesn’t include your product mix or your customers actual buying habits.
To build your own percentage: split after-sales spend by type - parts, consumables, service labour.
For each type, find the median number of orders per customer per year, and the average order value. Round each median up to a whole order. Multiply the rounded median by the average order value for each type, add the three together, then divide by the average machine value.
This distributors example:
- Consumables: median 2,5 orders/yr, rounded to 3.
Average order 415,81 x 3 = 1 247,44 Eur/yr- Parts: median 0,51 orders/yr, rounded to 1.
Average order 709,82 x 1 = 709,82 Eur/yr- Service (maintenance visits): median 0,65 orders/yr, rounded to 1.
Average order 857,28 x 1 = 857,28 Eur/yrTotal: 2 814,54 Eur per machine per year.
Average machine value is 182 238 Eur
We end up with 2 814,54 / 182 238 = 1,54%.
This percentage undercounts on purpose. Rounding up from a low median to a full order is already generous. And it can’t include what a customer bought from a third party instead of you, because that never reaches your invoices. Treat it as a starting point, not a maximum.
The number you will eventually would like to know is your wallet share. Every machine you sold has a total yearly cost of keeping it running: parts, consumables, maintenance labour, repairs. Your wallet share is the part of that spend that ends up on your invoices instead of on a local service provider or supplier. The percentage from step 3 is only the share you can see today, because your invoice data has no record of what the customer bought somewhere else. Let’s continue calculations keeping that in mind.
For this distributor the full after-sales potential considering only his own wallet-share is 10,57M x 1,54% = 163 243 Eur.
Step 4: The real gap
163 243 Eur (step 3) - 108 066 Eur (step 2) = 55 177 Eur gap.
That total is not the number to fully count on. It nets every customer against each other in one sum, so the accounts already spending above 1,54% are covering the accounts spending well below it. The real potential could be found by summing only the positive gaps, one by one. Drop everyone already at or above 1,54%, and add up just the ones that are still below it.
Two more things to narrow it further. Machines under 1-2 years old are still in warranty and haven’t reached a normal ordering pattern, so exclude them from the potential, not only from the actual.
And this distributor’s 58 machines belonged to 48 customers, so several customers owned more than one machine, at different ages and configurations. Two machines from the same customer can be at completely different points in their own maintenance schedule, and a customer-level percentage hides that. Once your installed base is no longer one machine per customer, run steps 1 to 4 machine by machine.
This method’s limitations
It only sees revenue that reached your own invoices. Anything a customer bought from a third party or a grey-market supplier is invisible here, which makes the gap really conservative yet precise starting point.
It is an excel snapshot. Every new invoice, every machine sold, every warranty expiring means joining the three exports by hand again and re-running steps 1 to 4 to keep the number current. Past a couple hundred machines that gets slow enough that most people stop updating it after the first pass.
How to turn that into actionable indicator
Most importantly, it gives you the size of the potential gap and which machines/customers its related but it does not tell you which customer to call first.
Some of those customers stopped ordering after warranty, some have a maintenance visit overdue by a year, some got used to discounted pricing and order almost nothing. Each one needs a different message from your team.
In the next guide we go through the checks that turn this gap into a customer-by-customer list your after-sales people can work from.
If the bottleneck is just getting the first number, the three exports above and a few hours are enough. If you want it live, refreshed with every new invoice and machine sold, and broken down machine by machine instead of rebuilt by hand each time, let’s have a conversation about it and we’ll show you how that might look like.
