Prioritization is one of the toughest aspects of software product-development. In these days of being agile and running lean, we don't want to prioritize our backlog by fiat, politics, or gut-feel. Teams need to be aligned to accomplish core business objectives and need tight feedback loops with the customer and stakeholders in order to achieve those objectices. To accomplish this level of cross-functional product development maturity, we must combine data from a number of sources to quantitatively optimize development. 

In this talk, I will outline an approach we are using at Neo to help our clients integrate business metics and probabilistic modeling into their prioritization process. Leveraging data from business KPIs, the product development team's own performance metics, and feedback from in-production experiments and A/B tests, I'll illustrate a straightforward yet rigorously quantitative method of prioritizing feature development to focus on achieving business and product outcomes, not simply producing technology outputs.