The Challenge
One of India’s largest quick commerce platforms sources last-mile delivery riders through a complex mix of channels running in parallel, including organic and digital funnels, rider referrals, multiple hiring agencies, and partner networks. At the scale of lakhs of monthly onboardings, this multi-channel model created a costly measurement problem.
Without a deterministic way to credit each hire, the same rider could be claimed by more than one channel. Attribution was inferred after the fact rather than declared at source, leading to disputed hires, inflated claims, and payout reconciliation that consumed time and eroded trust. The client couldn’t cleanly answer the questions that mattered most to its unit economics: which hires were genuinely unique, which channel drove each activation, and whether each channel was paid accurately for the value it delivered.
The Vahan.ai Solution
To fix this, the client rolled out a referral-code (RC) based attribution system: a unique code captured at onboarding that hard-links every rider to a single source channel. But the system was only as good as its adoption. Across dispersed, high-volume, digitally less-fluent cohorts, the client’s largest supply channels struggled to make it stick. The client needed its partners to drive RC adoption to near-ceiling levels, fast, without sacrificing volume.
As the client’s largest external hiring channel, Vahan re-engineered its onboarding flow to make referral-code capture near-universal, while sustaining month-on-month volume growth:
• Network-wide adoption discipline: Vahan aligned its entire partner network, including hundreds of recruitment leaders and their tele calling teams, around RC capture, tracked at the individual partner level.
• Volume and compliance held together: Adoption scaled without pulling back on placements. Discipline and scale aren’t a trade-off when the flow is engineered right.
The Impact
With Vahan’s re-engineered flow live across the client’s network, the platform achieved a step-change in attribution quality: referral-code adoption climbed to 98% of onboardings via Vahan, giving the client a near-complete, deterministic dataset at one of its largest external agencies.
Duplicate and disputed hires were eliminated, letting the client settle payouts against a hard record rather than negotiated claims, all while placements grew month-on-month.
