AdsCult built QuoteNow as a custom quotation and estimate management system for a luxury furniture brand handling highly customised orders. The platform was designed to replace complex Excel-based workflows with a structured, data-driven system that supports speed, accuracy, and scale.
The client operates in the premium furniture space with thousands of configurable products and a strong focus on customisation. Their sales, studio, and factory teams required a shared system that could manage complexity without slowing down operations.
The client’s quotation process was heavily dependent on spreadsheets and manual coordination, which became increasingly difficult to manage at scale.
Estimates were created using large spreadsheets that were difficult to maintain and error-prone.
With over 20,000 SKUs, manual data handling slowed down quote preparation.
Customer-facing estimates and factory-level estimates required different levels of detail.
Tracking revisions and approvals across teams was inefficient.
There was no structured data to analyse customer visits, conversions, or trends.
Sales, studio, and factory teams operated on disconnected versions of the same data.
We focused on preserving the flexibility of Excel while removing manual effort and operational risk.
We studied the complete customer journey, from showroom visits to factory-level detailing, to understand how estimates were built and approved.
The platform was designed to feel familiar to Excel users while introducing structured inputs, validations, and version control.
A custom system was built to manage SKUs, estimate logic, revisions, and role-based access. Every stage of the quotation journey was connected to structured data.
The system was tested for accuracy, performance, and usability across large product datasets and real sales scenarios.
We selected technologies that support complex business logic, large datasets, and structured workflows.
Robust backend framework for complex quotation logic.
Handles pricing logic, validations, and data processing.
Relational database suited for structured and high-volume data.
Improves interactivity across estimation workflows.
Enables efficient data fetching for complex estimate structures.
Responsive UI framework for clean and consistent layouts.
A unified platform that mirrors natural workflows while automating every repetitive, manual step.
Studio visits and customer interactions are tracked to support footfall analysis and follow-ups.
Thousands of products can be uploaded and managed efficiently with structured configurations.
Estimates can be created, revised, and tracked with full version control across teams.
Customer-friendly estimates and detailed factory-level estimates are generated from the same data source.
Customer activity data feeds into dashboards for conversion tracking and remarketing.
Sales, studio, and factory teams access only what is relevant to their role.
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