How a global manufacturer of decorative lighting cut the time it takes to prepare a quote from weeks to seconds.
About the client
The client designs and delivers decorative lighting installations, and almost every project is one of a kind — different in size, materials and finish. A standard price list simply doesn’t work here: the cost depends on the specifics of each order.
As a result, every enquiry went to the production team, who prepared each quote by hand. The process could take up to two weeks — and all that time, the customer had no idea whether the project would fit their budget.
The client received a steady stream of enquiries for decorative lighting projects. Even a rough quote required input from the production team and a manual trawl through past proposals – whether or not the enquiry was ever likely to turn into an order.
Reliance on productionEvery single quote needed input from the production team.
Manual analysisThe team searched through similar past quotes by hand.
Low-potential enquiriesTime and resources went into enquiries with no real chance of becoming a sale.
Long waitsCustomers waited ages for the most basic answer: ‘Can I afford this project?’
Every enquiry followed the same route: from the sales rep to production, through a manual search of the quote archive, and back to the customer. The process was identical for a major order and for an enquiry that never stood a chance.
The knowledge needed for fast quoting was already there – locked away in historical quotes.
AutomationAutomate the preparation of preliminary quotes.
SpeedCut the wait for a first estimate.
Knowledge baseTurn historical quotes into a knowledge base.
Free up productionTake low-potential enquiries off the production team’s plate.
The tool analyses thousands of the client’s past quotes and uses them to produce an estimate for each new project.
The system draws on every past project and what it actually cost.
Each new enquiry is matched against similar projects delivered in the past.
Prices from previous years are automatically brought up to today’s costs.
The customer receives an indicative price range — not a final offer, but a quick answer to the question: “Can I afford this?”
The tool runs as a Pimcore plugin, within the environment the client was already using.
That’s all it takes to prepare an initial quote.
AI draws on historical data to deliver accurate estimates.
The system accounts for inflation and changing costs over time.
Production only gets involved in projects with real potential.
A preliminary quote that once took up to 2 weeks is now ready in a matter of seconds – and production only gets involved where a project has real potential.
The project grew out of Omega Code’s ongoing work with the client on maintaining and developing their Pimcore environment.
With an in-depth understanding of the client’s processes, the Omega Code team proposed and delivered an AI-powered solution that cut the time customers wait for a quote.
If pricing your products calls for a case-by-case analysis and ties your team up with enquiries that go nowhere — let’s talk about how AI could change that.
Let’s discuss your project