Member-only story

DS in the Real World

How I Built a Dynamic Pricing System

The following is known to be true in business: High Price, Low Volumes. High Volumes, Low Price. Or is it?

Etienne Yuan
Towards Data Science
9 min readApr 14, 2020

--

Photo by Benjamin Sharpe on Unsplash

In this article, I share with you my experience in building a dynamic pricing system for a long-distance train company, and how we increased the number of seats sold without changing our timetables, nor lowering our average price per seat, by applying very basic principles of microeconomics.

This implementation also applies to any business in which the service it sells shares some characteristics with train seats, that is to say:

  • The cost of selling one additional unit, or marginal cost, is close to zero.
  • If a unit available is not sold by the time the service is rendered, (e.g. A train leaves the station), then it cannot be kept in stock, and its potential value is lost forever.

This would be the case of hotel rooms, airlines, long-haul bus tickets, cinema, theater, concerts, zoos, cruises, sporting events, etc.

In order to build the model, we first need to answer the following questions:

  • How much of a good or service do customers buy?
  • How much do customers pay?

--

--

Towards Data Science
Towards Data Science

Published in Towards Data Science

Your home for data science and AI. The world’s leading publication for data science, data analytics, data engineering, machine learning, and artificial intelligence professionals.

Etienne Yuan
Etienne Yuan

Written by Etienne Yuan

Innovation Consultant | Investor | Writer Wannabe | etienne@eyuan.org | @etienneyuan

Responses (6)