
A quote in one day instead of five – an integrated order management system for GRUPA KRES
GRUPA KRES managed its orders across several disconnected tools, and customers waited an average of five days for a quote. We designed a single system covering the entire order lifecycle – from inquiry to installation – in which artificial intelligence prepares a preliminary quote. Today, quotes reach customers within one day, and every order remains fully under control.
20 employees, approx. 100 orders per month
14 weeks
Custom AI-powered system
Results
Measurable implementation results
1 day
from inquiry to quote (previously 5 days on average)
100
orders per month in a single system
0
lost orders since rollout
+6 pts
percentage-point increase in margin per order within six months
Challenge
Long quote turnaround and inconsistent pricing
GRUPA KRES is a twenty-person stoneworking company that handles around one hundred orders a month – from kitchen countertops to headstones. Each order passes through several stages: inquiry, on-site measurement, pricing, production and installation. Information about these stages, however, was scattered across reception notes, spreadsheets, a calendar and workshop records.
This had a direct impact on the customer experience. Preparing a quote took five days on average, as each inquiry had to reach the right person and then wait for measurement and costing. Some customers turned to competitors in the meantime, and every question about order status required a call to the workshop.
Pricing consistency was a further challenge. The same product could be priced differently depending on who prepared the quote – sometimes below the target margin, sometimes above what the customer was prepared to pay. The owner wanted standardised pricing without expanding the team.
What we did
One system for the entire order lifecycle
We began with interviews across every department – from reception to the installation crews – and an analysis of two hundred completed orders. This allowed us to map the process precisely and bring together, in one place, the material price list and costing rules that had previously existed only as individual know-how.
On this basis, we built a system in which every order has a single record, maintained from first contact through to the installation report. Artificial intelligence analyses each customer inquiry – whether received by phone, email, web form or messaging app – and prepares a preliminary quote based on the current price list and comparable past projects. An employee reviews the proposal and sends the customer a finished quote, while installation crews document their work in a mobile app.
The rollout was phased. In the first week, the existing and new ways of working ran in parallel, and every system-generated quote was reviewed. After three weeks, the team was working exclusively in the new system, and we incorporated feedback on an ongoing basis.
Business impact
Faster quotes, consistent pricing and higher margins
The time from inquiry to quote fell from an average of five days to one. Customers receive a measurement date almost immediately and a finished quote shortly after the visit. The company wins more contracts because it is the first to present a concrete proposal.
Quotes are consistent because the entire team works from a single, up-to-date price list. Within six months, the average margin per order rose by 6 percentage points.
Customers track their order status via a link sent by email. Relieved of progress inquiries, reception can devote more attention to building relationships and handling new orders. Customer satisfaction (NPS) rose by 28 points in the first quarter.
“The best thing about this system isn't that we handle more orders — we handle the same number. The best thing is that the same 20-person team now has time to talk to customers instead of hunting for a sheet of paper in a binder. We used to manage chaos. Now we manage a business.”
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Contact
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Within 48 hours, we will provide an initial assessment of how it can be improved – based on our experience with similar implementations.
