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Enhancing Delivery Efficiency with Custom Mapping Solution: A Case Study on a Top US-Based Food Delivery Company
Technology Category
- Analytics & Modeling - Machine Learning
- Networks & Connectivity - Gateways
Applicable Industries
- Food & Beverage
- Transportation
Applicable Functions
- Logistics & Transportation
Use Cases
- Building Automation & Control
- Last Mile Delivery
Services
- System Integration
The Challenge
The leading food delivery company in the US was facing challenges in keeping up with the growing demand and customer expectations. The company was striving to meet its ambitious growth goals without compromising on the quality of service. The existing mapping solutions were rigid and did not cater to the company's specific needs. The company required a more tailored mapping solution that would help them achieve more efficient and on-time deliveries, provide more accurate Estimated Time of Arrivals (ETAs), and reduce costs on Maps APIs.
About The Customer
The customer is a leading food delivery company based in the United States. As the food delivery vertical continues to grow, the company is striving to meet the increasing demand and high customer expectations. The company has ambitious growth goals and is committed to providing quality service. However, the company was facing challenges with its existing mapping solutions, which were rigid and not tailored to its specific needs. The company needed a more efficient mapping solution to ensure on-time deliveries, provide accurate ETAs, and reduce costs on Maps APIs.
The Solution
NextBillion.ai proposed a two-pronged approach to address the company's challenges. Firstly, they emphasized the importance of building and owning a mapping platform for driving business outcomes and competitive differentiation. Secondly, they identified key elements such as custom maps, proprietary first-party data, real-time data, delivery area, and hyperlocal nuances that would be crucial in building an effective custom solution to optimize delivery times. Based on these evaluations, NextBillion.ai developed an exclusive modular mapping stack powered by advanced machine learning algorithms. The solution included custom maps that could be refreshed, edited, and updated, customized and scalable ETA and Routing APIs, and a completely on-premise and cloud-agnostic deployment. This solution was designed to provide reliable ETAs, hassle-free routing, and cost efficiency.
Operational Impact
Quantitative Benefit
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