Omnichannel Lead Leakage
Leads arrived across calls, WhatsApp, the website, and referrals and roughly 35% went unanswered or were duplicated across reps' Excel sheets.
Featured Case Study
B2B Trading CRM: 100% Lead Conversion Increase
Custom B2B trading CRM unified lead capture, quoting, dispatch & collections eliminating leakage and boosting lead conversion by 100%.
Industry
B2B Trading & Distribution
Duration
14 Weeks
Year
2025-26
Project Overview
The client is a mid-sized B2B trading and distribution company supplying bulk industrial materials to dealers and factories across multiple Indian cities. With roughly 180 active monthly accounts and 400+ recurring buyers, the business had outgrown spreadsheet-based sales tracking. Inquiries arrived through calls, WhatsApp, website forms, and walk-in referrals but there was no single system of record.
We partnered with them on a custom CRM for B2B distribution built around real trading workflows: slab pricing, freight logic, credit limits, and dispatch coordination. The six-person Dezdok team built the platform on React, Node.js, and PostgreSQL with a WhatsApp Business API integration.
Business Objectives
The goal was to replace six disconnected Excel sheets with a single operational backbone that captures every inquiry, generates accurate quotes in under two minutes, gives the dispatch team real-time priority visibility, and turns collections from reactive into proactive without disrupting active trading days.
Target Audience
The system serves internal users at a B2B bulk-materials distributor: sales executives fielding dealer inquiries, the dispatch team coordinating transporter handoffs, accounts staff tracking credit-customer outstandings, and owners who need a single-pane view of the sales funnel.
Expected Impact
We targeted measurable gains in lead-to-order conversion, quotation turnaround, and receivables recovery. The business case assumed a doubling of monthly inquiry capacity without adding headcount, plus a 40%+ reduction in days-sales-outstanding through automated collections follow-ups and credit-limit enforcement.
Project Requirements
Core Requirements
The project required a unified lead and inquiry management platform capable of ingesting requests from four distinct channels website forms, WhatsApp Business conversations, inbound phone calls, and manual sales entries from field reps.
Each inquiry had to be auto-assigned by region and product category, stamped with a source tag, and routed to the correct sales executive with an SLA-based follow-up reminder. The interface needed to let a rep log a new dealer inquiry in under 20 seconds, because the team handles 60–90 inbound touchpoints on a busy day.
For the quotation engine, we needed a smart quotation builder that pulls the latest SKU pricing, applies quantity-slab discounts, layers in GST and state-wise tax rules, calculates freight based on transporter tariffs and destination, and exports a branded PDF in under 90 seconds. Quotes had to be shareable directly to WhatsApp, with approval workflows for any special-pricing exceptions above a configurable threshold. Old price lists being used by mistake was a recurring revenue leak the system needed hard-locked version control on pricing.
From a technical perspective, the platform was built using microservices architecture for B2B distribution, with separate services for lead capture, quotation, inventory, dispatch, and collections. We used React for the frontend, Node.js for the API layer, PostgreSQL for transactional data, and Redis for session and cache management. WhatsApp Business API integration enabled two-way customer conversations directly from the CRM. The system had to handle 50,000+ SKU variants with dealer-tier and region-based pricing.
Operationally, the system needed an order-to-dispatch tracker showing confirmed orders, procurement status, dispatch-ready items, transporter assignment, and delivery confirmation all on a single priority-sorted dashboard. The collections tracker required automated overdue alerts, logged payment promises, and credit-limit enforcement at the quotation stage so that sales reps couldn't close deals with customers over their credit ceiling.
Security requirements included role-based access control across six user roles, encrypted storage of customer KYC data, audit trails on every pricing change, and automated daily backups with point-in-time recovery. The analytics layer had to produce an owner dashboard showing daily inquiries, open quotations, won-lost deals, outstanding receivables, rep-wise performance, and top customers all refreshed in near real-time.
The Team Behind the Build
A dedicated team of experts assembled to ensure project success
Business Analyst / Project Lead
Shubham Channe
Led requirements discovery across sales, dispatch, and accounts functions. Mapped 40+ trading workflows into a unified CRM data model. Specializes in B2B distribution and trading-house operations.
Project Manager
Abhijit Biswas
Coordinated a 14-week rollout across six user roles without halting live trading. Ran parallel-run adoption workshops and managed phased data migration from legacy Excel sheets.
Lead Developer / Full-Stack Architect
Yash Kapadia
Architected the CRM backbone on React, Node.js, and PostgreSQL. Built the quotation engine with slab-pricing, GST, and freight logic. 10+ years in high-throughput B2B platforms.
UX/UI Designer
Sarthak Donga
Designed a trader-first interface optimized for rapid data entry inquiry capture in under 20 seconds and quote generation in three clicks. Built the mobile-friendly dispatch view.
DevOps Engineer
Yash Sathawara
Configured zero-downtime deployment, automated backups, and the WhatsApp Business API pipeline. Hardened the platform for peak-hour load with 99.9% uptime in the first 90 days.
QA Engineer
Priya Sharma
Ran 600+ test cases across pricing edge cases, tax rules, freight slabs, and credit-limit enforcement. Led UAT with the client's sales team and validated zero data loss during migration.
Core Challenges and How We Solved Them
Every ecommerce replatforming project has four or five failure modes. Here's how we handled the big ones on this engagement:
Challenge
Solution
Unified Inquiry Inbox
We built a unified inquiry inbox with WhatsApp Business API integration, auto-dedup logic, and SLA-based assignment. Result: lead leakage dropped to under 4% and response time fell from 4.5 hours to 14 minutes.
Challenge
Quotation Errors from Outdated Pricing
Sales reps routinely sent quotes using stale price lists from older Excel files, costing an estimated ₹4–6 lakh per month in under-priced deals and credibility-damaging revisions.
Solution
Version-Locked Quotation Builder
The quotation builder enforces version-locked pricing, applies slab logic automatically, and flags any manual override for manager approval. Result: quote errors fell to near zero and average quote turnaround dropped from 35 minutes to 90 seconds.
Challenge
Zero Dispatch Visibility for Customers
Customers called the sales team daily asking "where's my order" the dispatch team worked from a whiteboard, and there was no way to share status without a phone chain.
Solution
Order-to-Dispatch Tracker
We built a priority-sorted order-to-dispatch tracker with automated WhatsApp status updates at each stage. Result: inbound status-inquiry calls dropped 71%, freeing roughly 18 sales hours per week back to active selling.
Challenge
Reactive Collections and Unclear Outstandings
The accounts team chased payments after the fact with no overdue alerts, no credit-limit enforcement, and DSO creeping toward 62 days.
Solution
Automated Collections Engine
The collections engine automates overdue alerts by aging bucket, logs verbal payment promises against calendar reminders, and blocks new quotes for customers over their credit limit. Result: DSO dropped to 31 days and ₹1.8 Cr in aged receivables was recovered within 90 days.
Key Features We Shipped
The rebuild delivered six feature pillars that directly drive conversion and retention:
Omnichannel Lead Capture
Unified inbox ingesting website forms, WhatsApp messages, call logs, and manual entries with auto-assignment by region and product. Result: monthly inquiry capacity doubled from 1,400 to 2,850 without adding headcount.
Smart Quotation Builder
Generates PDF quotes in 90 seconds with live pricing, slab discounts, GST, and freight logic shareable directly to WhatsApp. Result: 94% of quotes now go out same-day, up from 11%.
Customer 360 Ledger View
Single screen showing past orders, rates given, pending payments, preferred SKUs, and full contact history. Result: reps cut customer-context lookup time from 6 minutes to 20 seconds.
Order-to-Dispatch Tracker
Live board showing confirmed, in-procurement, dispatch-ready, transporter-assigned, and delivered sorted by priority. Result: 71% fewer inbound status calls and 18 sales hours per week reclaimed.
Automated Collections Engine
Aging-bucket overdue alerts, logged payment promises, and credit-limit enforcement at the quote stage. Result: DSO cut in half (62 → 31 days) and ₹1.8 Cr recovered in 90 days.
Owner Command Dashboard
Near real-time view of daily inquiries, open quotes, won-lost deals, outstandings, rep performance, and top customers. Result: weekly management meeting time reduced by 60%.
Outstanding Results
Measurable impact and outcomes that exceeded expectations
100%
Lead-to-Order Conversion
Lift from 17% → 34%
96%
Faster Quotation Turnaround
From 35 minutes to 90 seconds
50%
DSO Reduction
From 62 to 31 days
71%
Drop in Status Calls
After dispatch visibility via WhatsApp
2x
Inquiry Capacity
From 1,400 to 2,850 monthly
99.9%
System Uptime
Across first 90 days with zero order loss
Let's Build Something Amazing
Ready to Scale Your
B2B Trading Operations?
If your distribution business is still running on Excel, WhatsApp screenshots, and manual follow-up lists, we know the fix. Our team has built CRM and operations platforms for trading houses, dealer networks, and distribution companies across India.
- 40+ Country Served
- 500+ Projects Delivered
- 98% Client Satisfaction
FAQs
A trading CRM is different from a generic sales CRM. It has to handle slab-based pricing, dealer tiers, GST and freight logic, credit limits, order-to-dispatch tracking, and collections not just contact management. We start with a two-week discovery across sales, dispatch, and accounts, map the real trading workflows, and build modular services (lead capture, quotation, inventory, dispatch, collections) on React, Node.js, and PostgreSQL. Typical rollout takes 12–16 weeks.
Off-the-shelf CRMs like Salesforce and HubSpot handle contacts well but struggle with slab pricing, freight logic, credit enforcement, and dispatch tracking. Most mid-sized trading companies end up with a custom CRM built around their actual pricing and logistics rules. The right platform depends on your SKU count, credit-customer ratio, and dispatch complexity not on brand names.
For a mid-sized distributor with 5,000–50,000 SKUs and six user roles, we target 12–16 weeks from kickoff to go-live. That includes requirements discovery, data migration from legacy Excel sheets, parallel-run testing, user training, and a phased rollout. The project in this case study went live in 14 weeks with zero trading-day downtime.
Yes the biggest lever is moving from reactive to proactive collections. A CRM with aging-bucket alerts, logged payment promises, and credit-limit enforcement at the quote stage typically cuts Days Sales Outstanding (DSO) by 40–55%. In this project, DSO dropped from 62 to 31 days within 90 days and ₹1.8 Cr in aged receivables was recovered.
The quotation engine stores SKU-level pricing with slab tiers (quantity bands), dealer-tier multipliers, and region-based adjustments. When a rep builds a quote, the system auto-applies the correct slab, layers in GST and freight, and flags any manual override above a configurable threshold for manager approval. Old price lists are version-locked so they can't be used by mistake.
Yes. Using the WhatsApp Business API, every incoming message becomes a trackable lead in the CRM inbox, with source tags, auto-assignment, and conversation history. Sales reps reply from inside the CRM so nothing lives in personal phone chats. Quote PDFs can be shared back to the customer on WhatsApp with one click.
For the client in this case study, the CRM paid back in under one quarter. The biggest gains were the ₹1.8 Cr in aged receivables recovered, a doubling of monthly inquiry capacity without added headcount, and a 100% lift in lead-to-order conversion. Most mid-sized distributors see payback in three to six months, with the collections and quotation modules driving the fastest impact.
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Gujarat, India.
Gujarat, India.
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