TopN AnalyticsMeasuring Genuine Driver-Supply Growth Through Uber Platform Data Reconciliation
A leading pan-India fleet management company supplying driver-partners to the Uber platform.
Where things stood
A fleet company supplying driver-partners to Uber needs to reconcile its own driver and vehicle records against Uber's own data — vehicle earnings and trip performance, driver onboarding/active status, and the subscription fees Uber deducts from drivers.
Strategically, it also wants to know whether it's genuinely growing the pool of drivers active on the Uber platform, or mostly re-recruiting drivers who were already driving for Uber through a different fleet operator.
What we built
Uber-sourced data (already landed in the operational database via an upstream process) feeds a PostgreSQL analytics warehouse — vehicle-performance sync, subscription-charge cost-center reconciliation, and driver-acquisition-quality classification tables.
How it works
TopN Analytics built reconciliation pipelines syncing Uber-sourced vehicle-performance and driver-status data into the analytics warehouse, plus a subscription-charge reconciliation that cascades through several fallback lookups (direct lease mapping, revenue-share mapping, team mapping) to attach the correct vehicle, team, and payment model to each Uber-deducted subscription fee.
Most distinctively, TopN built a 'New In Uber vs. Old In Uber' classification: comparing each driver's earliest-ever Uber trip against their first vehicle allocation with the company, to determine whether the company was that driver's entry point onto the Uber platform, or whether the driver had already been driving for Uber — likely through another fleet operator — before joining.
What we delivered and learned
The 'New In Uber vs. Old In Uber' metric is a genuinely strategic measure for a driver-supply business — it distinguishes growing the overall pool of Uber drivers from competing for the same pool of already-active Uber drivers against other fleet operators, very different growth stories with different implications for the company's relationship with Uber.
What it's built on
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