The document discusses using data and analytics to drive business outcomes. It presents the W-model for data-driven learning which involves listening, interpreting, predicting, responding and monitoring data in cycles. It provides examples of different types of qualitative and quantitative data and metrics that can be gathered, such as conversion rates, social media metrics, search engine metrics and customer satisfaction scores. It advocates defining behaviors that drive soft key performance indicators, bundling predictors into impact factors, and using these to track company success over time. An overall "customer happiness impact factor" or CHIF is proposed as a way to measure how choices and projects impact customer satisfaction.