Nextbillion.ai > Case Studies > Grassdoor Boosts Efficiency and Cuts Costs with NextBillion.ai’s Distance Matrix API

Grassdoor Boosts Efficiency and Cuts Costs with NextBillion.ai’s Distance Matrix API

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Technology Category
  • Sensors - Lidar & Lazer Scanners
Applicable Industries
  • Consumer Goods
  • Transportation
Applicable Functions
  • Logistics & Transportation
Use Cases
  • Last Mile Delivery
  • Time Sensitive Networking
Services
  • Cloud Planning, Design & Implementation Services
  • System Integration
About The Customer
Grassdoor, founded in 2018, is a cannabis delivery service operating across Los Angeles, Orange County, and Southern California. The company aims to be the 'Uber of Cannabis delivery', offering both on-demand and scheduled deliveries with a promise of same-day deliveries in under 45 minutes. With the increasing acceptance of cannabis and the surge in demand due to COVID-19, Grassdoor faced the challenge of maintaining customer satisfaction by providing accurate Estimated Time of Arrival (ETAs) and optimizing routes in complex urban environments. The company also needed to differentiate its customer experience in a market with increasing competition.
The Challenge
Grassdoor's primary challenge was to calculate accurate ETAs and optimize routes for last-mile and on-demand deliveries. The company needed a Distance Matrix API that could handle large API call volumes at scale, run at high throughput and low latency, and be cost-effective. The existing Distance Matrix APIs in the market had limitations, such as a matrix size limited to 25*25 elements, which was insufficient for optimizing a large number of deliveries for Grassdoor's large-scale operations. The cost of these existing APIs was also a concern as they proved expensive and the problem worsened as Grassdoor scaled up. The company was also looking for ways to improve operational efficiency in terms of increased throughput and reduced latency as they scaled.
The Solution
NextBillion.ai provided a proprietary Distance Matrix API that was engineered to overcome the limitations of existing APIs in the market. The API could support a matrix of up to 5000*5000 origins and destinations, enabling Grassdoor to predict exact travel times while accommodating for driver pit stops and other variables. This helped Grassdoor to consistently generate optimal routes and project accurate ETAs. The operational optimizations driven by the Distance Matrix API allowed Grassdoor to lower delivery times and the number of miles driven, and expand their service coverage with the same fleet. NextBillion.ai also offered flexible pricing models and costs that compared favorably against alternatives such as Google Maps and Mapbox. The API could be configured for on-premise and cloud-agnostic deployments, facilitating lower operational latency and increased throughput.
Operational Impact
  • The implementation of NextBillion.ai’s Distance Matrix API resulted in significant operational improvements for Grassdoor. The API's ability to support a large matrix size helped Grassdoor predict exact travel times, generate optimal routes, and maintain customer satisfaction by providing accurate ETAs. The operational optimizations driven by the API allowed Grassdoor to lower delivery times and the number of miles driven, and expand their service coverage with the same fleet. The flexible pricing models and competitive costs of the API improved Grassdoor’s unit economics. The ability to deploy the API within their own cloud environment facilitated lower operational latency and increased throughput, enabling Grassdoor to operate at scale with ease.
Quantitative Benefit
  • Reduced operational latency
  • Cut operational costs by almost 50%
  • Improved ETA accuracy

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