Grassdoor 利用 NextBillion.ai 的距离矩阵 API 提高效率并降低成本
技术
- 传感器 - 激光雷达/激光扫描仪
适用行业
- 消费品
- 运输
适用功能
- 物流运输
用例
- 最后一英里交付
- 时间敏感网络
服务
- 云规划/设计/实施服务
- 系统集成
关于客户
Grassdoor 成立于 2018 年，是一家大麻送货服务公司，业务遍及洛杉矶、奥兰治县和南加州。该公司的目标是成为“大麻配送领域的 Uber”，提供按需和预约送货服务，并承诺在 45 分钟内当天送货。随着大麻的接受度不断提高以及 COVID-19 导致的需求激增，Grassdoor 面临着通过提供准确的预计到达时间 (ETA) 和优化复杂城市环境中的路线来保持客户满意度的挑战。该公司还需要在竞争日益激烈的市场中打造差异化的客户体验。
挑战
Grassdoor 的主要挑战是计算准确的预计到达时间并优化最后一英里和按需配送的路线。该公司需要一个距离矩阵 API，它可以大规模处理大量 API 调用，以高吞吐量和低延迟运行，并且具有成本效益。市场上现有的Distance Matrix API存在局限性，例如矩阵大小仅限于25*25元素，不足以优化Grassdoor大规模运营的大量交付。这些现有 API 的成本也是一个问题，因为事实证明它们价格昂贵，而且随着 Grassdoor 规模的扩大，问题变得更加严重。该公司还在扩展过程中寻找提高吞吐量和减少延迟方面的运营效率的方法。
解决方案
NextBillion.ai 提供了专有的距离矩阵 API，旨在克服市场上现有 API 的局限性。该 API 可以支持多达 5000*5000 个出发地和目的地的矩阵，使 Grassdoor 能够预测准确的行程时间，同时适应驾驶员进站和其他变量。这有助于 Grassdoor 持续生成最佳路线并预测准确的预计到达时间。由距离矩阵 API 驱动的运营优化使 Grassdoor 能够缩短交货时间和行驶里程数，并扩大同一车队的服务覆盖范围。 NextBillion.ai 还提供灵活的定价模式和成本，与 Google 地图和 Mapbox 等替代方案相比具有优势。该 API 可以针对本地部署和与云无关的部署进行配置，从而有助于降低操作延迟并提高吞吐量。
运营影响
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