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实例探究 > Quick Commerce Provider Automates Delivery Allocation and Scales On-Time Delivery Volumes

Quick Commerce Provider Automates Delivery Allocation and Scales On-Time Delivery Volumes

技术
  • 分析与建模 - 预测分析
  • 功能应用 - 远程监控系统
  • 功能应用 - 仓库管理系统 (WMS)
适用行业
  • 电子商务
  • 零售
适用功能
  • 物流运输
  • 仓库和库存管理
用例
  • 车队管理
  • 预测性维护
  • 实时定位系统 (RTLS)
  • 供应链可见性(SCV)
服务
  • 软件设计与工程服务
  • 系统集成
挑战
Rapid growth in demand for its grocery delivery presented the customer with scalability challenges. Other operational problems like manual processes, poor visibility, and difficulties in ensuring customer centricity were weighing down their delivery operations. The need to address end-user privacy, growing first-attempt delivery failures, poor customer experience, and delivery visibility, inability to scale operations based on market demands, inability to customize deliveries based on business needs, inefficient slot-based delivery management, and manual delivery allocation of drivers and routes were some of the critical challenges they had to address to sustain growth.
关于客户
The customer, an eCommerce major’s B2C delivery venture, is an online supermarket application for getting fruits, vegetables, dairy products, bakery items, and other daily essentials delivered to customers’ doorstep. Operating across 27 dark stores with more than 600 drivers, our customer manages and executes more than 2.5 lakh deliveries per month. The customer has established itself as a significant player in the quick commerce sector, focusing on providing a seamless and efficient delivery experience to its end-users.
解决方案
Our customer was looking for a delivery management partner who could empower them to generate valuable business outcomes across multiple stages of growth. Shipsy’s partnership approach, strong tech focus, accompanied by its flexible, agile, and automation-driven on-demand delivery management solution, was the natural choice for the quick commerce provider. Shipsy ensured that the solution was up and running within two weeks to ensure zero business disruptions and seamless technology migration. Key features of the solution include auto allocation of orders to drivers, geofence-based order allocation, multiple order clubbing, ensuring slot-based deliveries, real-time order tracking, unified customer communication, suspicious delivery alerts, call masking, analytics-powered dashboards, and device compatibility. These features collectively enhanced the customer’s delivery operations, ensuring faster delivery turnaround times, improved customer experiences, high levels of ETA adherence, and more.
运营影响
  • As much as 90% of orders are auto allocated.
  • On-time delivery volumes were scaled to 90%.
  • High levels of customer privacy driven by call masking.
数量效益
  • Average dispatch to delivery time reduced to 25 minutes.
  • Significant reduction in delivery attempts owing to advanced geocoding.

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