Real-Time Pricing Calculator for U.S. Sales
How a 1–2 day quote turnaround was killing custom furniture conversions — and the internal tool that generated ₹1.5 crore in additional monthly revenue.
Company
Sierra Living Concepts
Timeline
Jun 2025 – Sep 2025
My Role
MT → Product Manager
Teams
US Sales · Pricing · IT
The quote flow, before → after
Customer requests custom quote
Pricing team calculates — 1–2 days
Sales enters config into calculator
Instant price, live on the call
~₹1.5Cr
Additional monthly revenue
~30%
Conversion rate improvement
1–2d→0
Quote turnaround eliminated
The Background
Sierra Living Concepts sells custom furniture to the U.S. market — pieces configurable by dimensions, materials, fabrics, and finishes. A significant portion of revenue comes from custom order requests handled by the U.S. customer support and sales team.
During my Management Trainee period, while coordinating with operations and finance teams, I noticed the U.S. sales team frequently flagged a recurring issue: custom quote requests were taking 1–2 days to close, and a meaningful percentage of customers didn't wait.
"A customer calls, excited about a custom sectional. We say 'we'll email you a quote tomorrow.' By tomorrow, they've bought from Article or Crate & Barrel."
Understanding the Root Cause
I mapped the entire custom quote process end-to-end by interviewing the sales team and pricing team. The problem had three layers:
Requirements Definition
I gathered requirements through structured sessions with the U.S. sales team and pricing team — understanding exactly how they calculated quotes manually, what variables were involved, and what edge cases existed:
| Requirement | Description | Priority |
|---|---|---|
| Real-Time Price Calculation | Sales agent enters config — calculator outputs exact price instantly, no pricing team dependency | High |
| All Custom Variables Supported | Cover all configurable parameters: dimensions, material, finish, quantity, delivery zone | High |
| Pricing Logic Accuracy | Output must match pricing team's manual methodology exactly — validated with 20+ test cases | High |
| Quote Generation | Calculator generates a shareable quote summary sendable to customer during or after the call | Medium |
| Sales Team Usability | Interface usable by sales agents during a live call — simple inputs, instant output, no training required | Medium |
| Pricing Update Mechanism | When material costs change, pricing logic updatable by pricing team without IT involvement | Low |
Sprint Planning & Execution
Sprint Goal: Fully document the pricing team's manual calculation methodology — every variable, every formula, every edge case — so IT can build it accurately.
Sprint Goal: Build the calculator tool with all required input variables and real-time price output. Sales team usability testing in the last 2 days of sprint.
Sprint Goal: Run all 20+ test cases, fix any pricing logic errors, get pricing team sign-off, train U.S. sales team, and deploy.
Project Timeline
Week 1–2
Problem Identification & Stakeholder Alignment
Mapped the full custom quote process, quantified delay impact, aligned US sales, pricing, and IT teams on the solution approach.
Week 3–4
Pricing Logic Documentation
Worked with pricing team to document all calculation formulas, variables, and edge cases. Compiled 20+ QA test cases with expected outputs.
Week 5–7
Build & Iteration
IT team built the calculator. Two rounds of logic corrections identified during internal testing. Sales team usability testing conducted in week 7.
Week 8
QA, Sign-off & Deployment
All 20+ test cases passed. Pricing team signed off on logic accuracy. US sales team trained. Tool deployed to production.
Month 2–3 Post-Launch
Impact Measurement
Custom order closures increased from ~110 to ~142/month. Pricing team no longer on the critical path for any custom quote.
Custom orders closed / month
+32 orders/month — ~30% close-rate improvement
Results
~₹1.5Cr
Additional monthly revenue (32 incremental orders × $5,500 AOV × ₹85)
↑ From baseline monthly revenue
~30%
Improvement in custom order close rate (110 → 142 orders/month)
32 additional closed orders/month
1–2d→0
Quote turnaround — now generated real-time during customer calls
Pricing team removed from quote critical path
100%
Custom quotes generated without pricing team dependency post-launch
Full sales team autonomy on custom pricing
What I Learned
The biggest conversion lever is often in the sales process, not the product UI.
We spent time optimizing PDPs and checkout — rightfully — but a broken sales ops process was losing premium customers at the very last mile. Internal tooling can have higher ROI than customer-facing features.
Requirements quality determines build quality.
The most important sprint was Sprint 1 — documenting the pricing logic. Every error found during QA traced back to an edge case not captured in documentation. Investing time upfront saves multiples in rework.
Speed is a feature for high-consideration purchases.
Premium furniture buyers have high intent but fragile attention. A competitor with a faster, more confident sales experience wins. Removing friction from the sales process is product work.