在Lyft的定价

Introduction

简介

Pricing forms the backbone of the Lyft’s marketplace system, which is core in the journey of improving people’s lives with the world’s best transportation. In general, the goal of price optimization is to find the price that balances supply and demand while covering the expenses necessary to provide an easy-to-use rideshare platform, where drivers have tremendous influence on the rider prices through their entry and exit on the platform. Specifically, we strive to find rideshare options and prices that are:

价格构成了Lyft市场系统的支柱，它是用世界上最好的交通工具改善人们生活的旅程中的核心。一般来说，价格优化的目标是找到平衡供应和需求的价格，同时支付必要的费用，以提供一个易于使用的乘车共享平台，司机通过他们在平台上的进入和退出对乘客的价格有巨大的影响。具体来说，我们努力寻找的乘车方案和价格是：。

Reliable: balance consistent prices and pickup times across repeated usage;
可靠：在反复使用中平衡一致的价格和提货时间。
Fair: any two riders see the same price for the same ride intent with a clear explanation otherwise (e.g. one rider has a Lyft Pink membership);
公平：任何两个骑手看到相同的价格，但有明确的解释（例如，一个骑手有一个Lyft Pink会员）。
Competitive: efficient pricing to remain competitive compared to other transportation options.
竞争力：高效的定价，与其他交通方式相比，保持竞争力。

In this blog post, we discuss the rideshare pricing system architectural design, modeling approaches and potential future iterations of Lyft’s pricing engine to illustrate how we tackle price optimization to achieve Lyft’s long-term mission.

在这篇博文中，我们讨论了乘车定价系统的架构设计、建模方法和Lyft定价引擎未来可能的迭代，以说明我们如何解决价格优化问题，以实现Lyft的长期使命。

System Design

系统设计

From the system design perspective, there are three layers of the stack:

从系统设计的角度来看，有三个层次的堆栈。

Pricing Orchestration: a configurable engineering platform with fast iterations for precise execution to support algorithms and operations;
定价协调：一个可配置的工程平台，具有快速迭代的精确执行，以支持算法和操作。
Pricing Operations: a process and supporting toolkit to ensure prices are competitive;
定价业务：一个确保价格具有竞争力的流程和支持工具包。
Algorithmic Pricing: a plug-in-play model library designed for consistent backtesting, experimentation, and productionization of automated data-driven decisions pursuing fair and reliable prices.
算法定价：一个即...