At Atomize, a Gothenburg startup of 2016, we are building an automatic revenue management platform for the hospitality industry. At the core is an automatic pricing engine, maximizing revenue while keeping manual work to the minimum.
The main question of dynamic pricing is what happens to the demand when the price changes. Historically, in practice, this question was answered with the help of macroeconomic models (price sensitivity/demand elasticity). This approach is straightforward to implement, but hard to justify in full. At Atomize, we are implementing a finer model of demand, allowing us to build simulations answering that main question directly.
In this talk, we will cover the basics of the optimal pricing problem, indicate the unique challenges and constraints of the hospitality industry and Atomize position in it, and give our vision of a real-time price optimization engine architecture.
Machine Learning Engineer @ Atomize
A mathematician with a PhD in statistics from the Chalmers University of Technology, Anton has been working with dynamic pricing for the last three and a half years. He is currently involved in developing a dynamic pricing and revenue forecasting engine for Atomize, an automatic revenue management platform for the hospitality industry and a 2016 startup based in Gothenburg. Anton will talk about some of the challenges unique to the hospitality industry's pricing problem, and applications of stochastic processes in modelling and forecasting demand.