Pricing optimization can often capture more value than any other data science or analytics project or product for an organization. However, because of complexity, uncertainty, and risk aversion, many organizations are timid in their approach to apply machine learning to their pricing strategy. After walking through the foundational frameworks of pricing theory, we will apply standard machine learning models to optimize and inform our product's price.
Jacob is the Data Strategist at Data Formed, a consulting group and network of data science professionals. Jacob's primary projects at Data Formed involve customer behavior, price elasticity, and forecasting. Jacob is also a lecturer at Southern Utah University's Masters in Business Analytics program. His course responsibilities include project structuring and strategy.