This strategy focused on driving profitability for a loss-making instant retail platform operating across Tier 3–4 cities in China.
Through a structured diagnostic, we found that underperformance was not driven by insufficient demand, but by structural inefficiencies in the operating model — including low fulfillment density, heavy reliance on subsidies, and an unfavorable category mix. These factors resulted in a persistent unit economics gap of approximately ¥0.6 per order across most cities.
To address this, we developed a data-driven city portfolio strategy, segmenting 10 cities into three distinct tiers: Invest (density-ready markets), Optimize (operational turnaround opportunities), and Hold (structurally unviable markets). This allowed for focused capital allocation and avoided inefficient, broad-based expansion.
We then built a detailed unit economics model and identified four key operational levers — subsidy rationalization, delivery densification, AOV/category mix upgrade, and merchant monetization — which together can fully close a ~¥0.65 per order loss gap.
Finally, we translated the strategy into a 3-year execution roadmap with clear milestones and KPIs. The plan enables Invest cities to reach break-even by Year 2 and Optimize cities by Year 3, achieving overall portfolio profitability while reducing dependency on subsidy-driven growth.
This project demonstrates how combining market insights, operational analysis, and financial modeling can transform a high-growth but loss-making platform into a disciplined, profitability-focused business.
