5x More Qualified Leads per Sales Rep

B2B e-commerce platforms selling to retailers and distributors face a structural bottleneck in their sales operations: teams spend up to 70% of their time on research, data reconciliation, and manual lead evaluation — leaving only 30% for actual selling conversations. Recent industry analysis shows that AI-powered lead scoring algorithms achieve 40% higher qualification accuracy than static models. At the same time, studies reveal that companies responding to inquiries within one hour have a sevenfold higher conversion probability. The gap between the speed the market demands and the capacity of manual processes grows wider every month.

Data Integration & Enrichment

The platform connects CRM, ERP, and webshop data through standardized APIs into a unified data layer. Firmographic information, purchase histories, and behavioral data from the online store flow together automatically. A multi-stage enrichment process augments every lead across multiple data sources — following a waterfall principle where missing fields are sequentially filled from alternative providers. Supabase serves as the central data platform with row-level security for multi-tenant access.

AI Model & Scoring Logic

An LLM-powered scoring system evaluates each lead against the Ideal Customer Profile (ICP). The model analyzes not only structured data like company size and industry but also unstructured signals: current job postings, LinkedIn activity, and technology indicators on the company website. This produces a dynamic score that updates with every new piece of information. The outreach engine generates personalized email sequences and follow-ups — tailored to industry, role, and prior interactions. Python-based orchestration controls timing and channel selection for each contact.

Deployment & Monitoring

The Next.js dashboard displays pipeline status, response rates, and conversion metrics in real time. Sales team members see at a glance which leads deserve attention and which sequences perform best. When unusual patterns emerge — such as a sudden drop in open rates — the system automatically suggests adjustments. Structured alerts escalate critical pipeline bottlenecks to sales leadership.