Unifying a Multi-Channel Driver Recruitment Funnel Into a Single, Measurable Pipeline

Growing a driver-partner base means sourcing leads through many parallel channels at once — inbound and outbound telecalling, an automated AI-dialer campaign type, driver referrals, performance marketing, in-house field sales staff, and third-party sourcing vendors — each feeding the same multi-step conversion funnel from first contact through vehicle allocation.

Without a unified way to measure this funnel, understanding which channels convert best, where leads drop off, and how the AI-dialer channel compares to human telecallers required manually stitching together data from a CRM system, a telephony platform, and multiple sourcing vendors — slow and error-prone at the scale of hundreds of thousands of leads.

TopN Analytics built a family of pipelines that replicate the CRM's core lead, call-history, and campaign data into the warehouse, then compute purpose-built funnel-stage fact tables walking every lead through the full journey: sourcing, call attempts/connects, expressed interest, scheduling, walk-in, deposit, and allocation.

These tables explicitly separate AI-dialer-driven calling activity from human-telecaller activity, classify each lead's channel against a maintained campaign taxonomy, and apply a consistent 'fresh vs. repeat lead' and 'new join / rejoin / resurrection' classification — the same driver-lifecycle logic used elsewhere across the business — so a lead sourced twice, or a driver returning after a gap, isn't double-counted or miscategorized.