In today's market, the ability to review prices in real time and at scale is becoming a decisive factor for companies that want to remain competitive. It is therefore critical to take full advantage of the opportunities offered by AI to build real-time pricing models that consider not only the prices of their competitors but also products, their availability, and customer behaviour. 
 
But how best to use AI and machine learning to optimize pricing strategies? How to choose (and achieve) revenue and/or profit targets? 
 
The aim of this meeting is to offer participants the chance to learn more about the challenges and opportunities of dynamic pricing, with a focus on how to make the most of the possibilities offered by new technological disruption. Thanks to the discussion with Santiago Gallino, professor at the Wharton School and a global reference on the topic, participants will be able to delve into how to set up or refine a dynamic pricing strategy capable of creating competitive advantages regardless of their industry.
  
In particular, the following topics will be discussed:

• build a successful pricing model: integrate data analysis, consumer decision models and price elasticity 
• choosing your focus (profits or revenues) and the best strategy to achieve it (sophistication Vs scalability) 
• successful applications in markets around the world.