Salesforce, Pipedrive, HubSpot. These are great tools if you're running a software company or a consulting firm. But if you're running a machine shop, they're designed for a world that isn't yours.
We've seen job shops buy enterprise CRM software, use it for 6 months, then go back to Excel. Here's why—and how to avoid it.
What Generic CRM Gets Wrong
Obsession With Sales Stages
Pipedrive has "Lead," "Qualified," "Proposal," "Won." Salesforce has custom funnel stages. But in a machine shop, you don't have a sales funnel. You have customers, you have quotes pending, you have delivery dates.
When you force a job shop into a sales-funnel framework, half your data is wrong or misleading. A quote that's pending for 3 weeks isn't really "in the pipeline"—it's probably dead.
Wrong Activity Tracking
Generic CRM tracks phone calls, emails, meetings. In a machine shop, your real activities are: quote sent, quote revised, quote lost (and why), job completed on time, repeat customer ordered again.
You don't care that someone sent an email 3 weeks ago. You care that a quote has been pending for 21 days and you haven't followed up.
No Machine/Capacity Context
When you're quoting a job, you need to know: can we actually do this? Do we have the capability? Is the machine booked for the next 8 weeks?
Generic CRM doesn't know you have a 5-axis centre. It doesn't know it's booked solid through March. So you quote jobs you can't actually deliver on, or you quote too high because you're overbooked.
Supplier Management Is Missing
Your suppliers are as important as your customers. But generic CRM treats "supplier" as an afterthought (a category in the contacts section). Machine shops need:
- Supplier contact details and pricing
- Lead times for materials
- Historical pricing to track inflation
- Payment terms
None of these fit naturally into a sales-funnel CRM.
What CRM For Machine Shops Should Have Instead
Simple Customer Records
Store what matters: company name, contact person, phone, email, notes on their capabilities (5-axis work, aluminium specialist, etc.), last order date, repeat frequency.
That's it. No "Lead Score." No "Lifecycle Stage." Just data you actually use.
Quote Tracking (Not Sales Funnel)
Every quote ever sent. Date sent. Quote value. Status (pending, accepted, lost). If lost, why (too expensive, too slow, went elsewhere). Follow-up reminders when a quote goes stale (15+ days with no response).
Machine Allocation
See at a glance: which machines are booked when. Add a job to your quote. See if you have capacity. Know your real delivery date before you promise it.
Supplier Database
Centralised supplier contact info, pricing, lead times. When you need to check a supplier's lead time for stainless bar stock, you don't dig through old emails. You check the CRM.
Activity Log (Not Email Tracking)
Every interaction logged: quote sent, quote revised, customer called, job shipped, repeat order received.
But not as busy-work. Not "log every email." As operational facts: "Why did this customer order 3 times in 6 months? What's their pattern?" Or: "This customer keeps coming back with rush jobs. Should we charge extra or refuse?"
Why This Matters For Your Bottom Line
Quote follow-up: Machine shops with CRM systems focused on quoting follow up on stale bids 50% more often. That's an extra 3–5 jobs per year for a 10-person shop. At average margins, that's £15–30k additional revenue.
Capacity planning: When your lead person knows machines are booked solid, they quote higher or turn down work. But when they don't know capacity, they promise dates you can't hit. CRM with capacity visibility eliminates this.
Supplier management: How many times do you call a supplier without checking their lead time first? CRM with centralised supplier info eliminates those wasted calls.
The Implementation Trap
Here's where most shops fail: they buy generic CRM, try to shoehorn their data into it, give up after 2 months.
The solution isn't more training. It's CRM software built specifically for manufacturing workflows. CRM that understands your reality: complex machines, capacity constraints, supplier relationships, repeat customers.
Once you have that, adoption is natural. Because the software matches how you already work.