Joe Caserta presents a statistically-driven model to understanding the customer path to purchase, which combines online, offline and third-party data sources. He shows how customer data is fed to machine learning, which assigns weighted credit to customer interactions in order to give insight into what marketing activities truly matter.
Maxwell Goldbas discusses enabling a data science culture and the infrastructure required to do so. Data lakes and identity resolution empower data scientists to look at people, rather than channels, to accurately depict the customer and their needs.
Marc Lobree, Partner Engineering Solutions Architect at Databricks presents how Databricks enables the analytical tools and capabilities to create a data &analyticsc platform that supports valuable marketing objectives.