work distribution
We built a flexible, rules-based lead distribution engine to overcome CRM limitations, enabling faster response times, better agent performance alignment, and improved conversion tracking.
Case Study: Intelligent Lead Distribution System
Industry: Financial Services / Lending
Client Type: U.S.-based Lender / Fintech
Platform: Web-based CRM Infrastructure
The client’s CRM system had built-in lead assignment tools, but they were too rigid for the scale and complexity of their operation. Distribution logic couldn’t account for agent performance, time zones, lead quality, or dynamic team availability.
This resulted in:
Delays in lead follow-up due to uneven distribution
High-value leads routed to underperforming or unavailable agents
Inability to test or iterate on distribution strategies
Lost revenue opportunities from mismatched lead-agent assignments
We developed a flexible lead distribution engine layered on top of the existing CRM. It dynamically assigned leads using configurable business logic, giving full control over how, when, and to whom leads were routed.
Key features:
Real-time assignment triggered on lead creation
Rule-based prioritization using parameters like lead source, credit score, geography, loan size
Load balancing across agent teams based on capacity, availability, and time zone
Admin interface for managing distribution logic without engineering support
A/B testing capability for experimenting with routing logic
Full audit logs for compliance and QA review
34% faster average lead response time
17% increase in funded loans within 90 days
Over 40% reduction in leads that went unanswered
Better conversion tracking from marketing to sales
Node.js backend with real-time event listeners
MongoDB for rule storage and lead tracking
Redis for queuing and lock management
Custom rule evaluation engine built in-house
Integrated with Salesforce API and Twilio call/SMS flows
Mamble is committed to working with partners to build remarkable projects with excellent marketing solutions and services.