Data Scientist at Tryolabs
Maia Brenner is a passionate data scientist and economist with strong programming skills, a mathematical and statistical background, and work experience in consulting and the public sector.
As Data Scientist at Tryolabs, she combines her econometrics and social sciences knowledge with her python and ML skills. Maia’s experience in the consulting industry covers several projects related to demand forecasting, price optimization, customer segmentation, and natural language processing, among others.
She is also a professor at ORT University and enjoys working on initiatives of AI4SocialGood. She has helped in the application of Machine Learning to improve the Public Education sector and is involved in Gender Inequality research groups.
WATCH LIVE: November 17 @ 3:00PM – 3:30PM ET
Setting the right price for a good or service is an old problem in economic theory, marketing, and business practices. However, as companies have more data than ever about their business and their customers, the world is moving towards new data-driven pricing strategies.
Machine learning tools allow us to incorporate structured and unstructured data in order to get accurate demand forecasts. But most importantly, with Machine Learning tools we can learn, for example, the price elasticity of demand for each SKU on each location and day, and therefore understand the willingness to pay of each customer. With these demand curves estimation and optimization algorithms we can learn which is the right price to set at each moment in time. In addition, with explainable AI tools and with randomized control trial experiments we can get new business insights, and deliver high impact price recommendations.
In this presentation, we will focus on how Machine learning is reshaping price optimization and will show outstanding results obtained by leading retailers around the globe.
In particular, we will walk you through our Machine Learning approach, which helped a Luxury Retail Company boost its gross margin by 28%. We will share the algorithms, techniques, and data sources applied, which led our client to gain over half a million dollars during a 10-weeks price optimization experiment.