Use case in production
Deploying an automated pricing model in a two-sided market
CEO, Dedalus WIP
Luke was the 2021 Practitioner in Residence at MIT's Governance Lab, and before that was a serial technical founder after working at McKinsey and the World Bank. He has built and deployed models to personalize behavioral nudges in financial products, to predict defaults in bonds and project performance in development aid, and to conduct automated pricing in marketplaces. Merging his strategy, product and technical background, he helps teams on the end-to-end creation of value from data, from first idea to production deployment.
A pricing strategy aims to establish the best price for a product/service while considering the market, profit margins and consumer demand. To fully automate a pricing strategy in production, you have to avoid prices being set at extreme highs or lows, by creating pricing safeguards. This session presents insights into deploying an automated pricing model in a two-sided market, combining ML and safeguard strategies, leading to immediate revenue improvement.