The challenge
An Indian group of companies distributes scientific and analytical instruments for overseas manufacturers. Its single sales team needed a CRM for scientific instrument distributors: one place to take each inquiry through to an order and, after that, a service contract.
The work was more tangled than ordinary B2B sales. The same team quoted under several group companies and for many overseas principals. Customers ranged from university departments to research institutes and multinational plants, and each had several contacts.
Pricing added another layer. Instruments were priced in foreign currency, and a quote had to carry import duty, freight and insurance before it made sense in rupees. Inquiries, quotations, follow-ups, maintenance contracts and targets were hard to track together.
What we built: a CRM for scientific instrument distributors
The group handed us a detailed requirement sheet, and we built a web CRM from it, module by module, on Node.js and MongoDB.
Masters. Locations, currencies, units, sources, item groups and items each have a master. Items carry model and catalog numbers, HSN code, GST, import duty, freight and insurance. When an admin changes an exchange rate, rupee prices update. Principal records hold catalogs, price lists, certificates and competitor information.
Customers. Customers sit under groups, such as departments under a university, and each has several contact persons. That mirrors how institutional buyers are actually organized.
The sales path. An inquiry converts to a quotation, pulling contact details from the customer record. The quote is issued under the chosen group company and can then become a sales order.
Follow-ups on every inquiry and quote, each with a next date, type, owner and status.
Sales projection built from each quote's chance of closing and expected month.
Annual maintenance contracts, sales tours with feedback, and tasks with overdue alerts on the dashboard.
Targets, compared with achieved sales, plus bulk email to customer contacts.
How it works day to day
Picture a sales executive opening a new inquiry from a university department. The department already exists under its university's group, so the right contact is a click away. The inquiry becomes a quotation with the contact details filled in, and the executive picks which group company it goes out under.
The quoted item already carries its duty, freight, insurance and tax details, and its rupee price reflects the latest exchange rate an admin entered. The executive sets a follow-up with a date and an owner, then records how likely the quote is to close and in which month.
When the order comes through, the quote becomes a sales order. Later, the instrument's annual maintenance contract is tracked in its own module, so the account stays in view long after the instrument is delivered.
The result
The sales team now follows a sale from first inquiry to service contract in one system. Every follow-up has an owner and a date, and overdue tasks surface on the dashboard.
Managers forecast sales from quotation probability and compare targets with achieved sales. Roles control who can view, edit or delete in each module, and exports to Excel or PDF carry the user's name, date and time.
What the research says
CRM data is often unreliable. In a 2025 survey of 602 CRM users and administrators by data-quality vendor Validity, 76% said less than half of their organization's CRM data was correct and complete, and 37% said poor data had cost them revenue (Validity State of CRM Data Management 2025). Here, items, principals, customers and contacts each live in one master, so a quote starts from the same record every time.
Too many tools wear sales teams down. CRM vendor HubSpot surveyed more than 1,400 sales professionals and found 45% felt overwhelmed by the number of tools in their tech stack (HubSpot 2024 Sales Trends Report). This CRM keeps inquiries, quotes, orders, follow-ups and maintenance contracts in one system instead of several.
Admin eats selling time. A survey by CRM vendor Salesforce of 7,775 sales professionals found that reps spend just 28% of their time selling (Salesforce State of Sales). Pulling contacts and prices into a quote automatically gives some of that time back.
Where AI fits next
The CRM has no AI yet; these are sensible next steps. AI could draft a quotation cover note from the inquiry and the principal's catalog, for the salesperson to edit. It could suggest a closing probability based on how similar quotes turned out, and turn overdue follow-ups into a short daily list for each salesperson.
Planning something similar?
Before you build a CRM for instrument or equipment distribution, it helps to answer four questions:
Do you quote under more than one company, and how should each quote show it?
Which costs sit between a foreign price and a rupee quote, and who updates them?
Does the relationship continue after the sale through service or maintenance contracts?
What do managers need to forecast, and from which numbers?
Comparing a packaged CRM with a custom one? Our guide to custom software versus off-the-shelf sets out the trade-offs. You can also read how we work on custom software and web-based sales tools.
See how we approach software for operations and logistics teams.
