04-19, 12:25–12:55 (Europe/Berlin), B05-B06
In the talk we give a brief overview of how we use Dynamic Pricing to tune the prices for rides based on demand, time of purchase, unexpected events strike etc., and other criteria to fulfil our business requirements.
Dynamic pricing is more challenging in Flixbus compared to other travel companies as we do not discriminate prices based on various categories such as business, economy classes, which are often used in trains and airlines. In the talk, we describe the challenges faced and discuss how we designed innovative solutions to solve these challenges.
The main topic I want to present is how we implemented a real time pipeline to calculate the prices based on current demand. At the same time, how it’s so reactive to changes for example, booking, route changes, etc. I will also present some of the efficient data structures we use to apply the changes very fast and efficient.
Intermediate
Expected audience expertise: Python –Intermediate
Abstract as a tweet –How Flixbus designed dynamic pricing strategy according to market demands
My name is Amit Verma, I have been working for Flixbus as Senior Data Engineer. I designed the dynamic pricing architecture which is currently being used in approximately 80% of market share. Before joining Flixbus, I worked in Cliqz: a Germany based search engine that was focused on user data privacy. Currently, this is used in brave search.