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Our client operates through diners and third-party delivery apps. The chain has recently expanded into three new locations, facilitating delivery operations through food delivery apps like Deliveroo, Just Eats, and Uber Eats. While this expansion increased their presence and popularity in Europe, it also increased the overall data load, making the need for a centralized data system more urgent.
The recent expansion generated more data that was yet to be integrated with existing records. Without this consolidated data on factors like order details, delivery routes, delivery time, and customer feedback, the client had little visibility into the performance of their food delivery operations..
To address these issues, they required a comprehensive data solution that would:
Integrate data (order details, delivery routes & times, and customer feedback) from multiple third-party food delivery apps into a unified system
Provide visual insights through performance dashboards and custom reports into KPIs like average delivery times, region-wise order volume, etc.
Keep data synchronized and up-to-date with near real-time updates and regular audits
Upon analyzing the client’s existing food-delivery framework, we identified two main challenges.
The data (like delivery time and customer feedback) was dispersed across their systems as well as multiple third-party food delivery apps (Deliveroo, Uber Eats, Just Eats), making it difficult to achieve a holistic view of order performance
Without timely reports and visual insights, the client lacked real-time visibility into key performance and inventory metrics (stock of popular menu items, ticket size, location-based uptime, average route time, wait time, etc.)
We proposed a comprehensive business intelligence (BI) solution focused on eCommerce data integration, visualization, and reporting.
Proactive data integration, visualization, and reporting enabled the client to examine finer details and identify workflow and delivery bottlenecks. The BI system was also able to handle growing data volumes from multiple sources, facilitating sustained growth in their food delivery operations.
30% reduction in average delivery times through real-time data visibility and optimized delivery routes
20% increase in on-time deliveries due to timely issue identification
Automating data collection and processing and minimizing manual effort also led to a 25% reduction in operational costs
Project initiation within 48 hours
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