Product Review
Generate Maximum Economic Value from Leading-Edge Digital Analytics and Data Science.
- The complete business practitioner's guide to profiting from analytics on big data.
- Build a focused, highly effective, cross-functional, process-oriented analytics organization, backed by the right support from other teams, funded by management, and perceived as successful by business stakeholders.
- Learn and apply best practices for every task when executing digital analysis--from planning and strategy to optimization and demonstrating value creation.
Digital analytics can help you grow value in virtually any market or industry in any country. To make the most of it, however, you need to create a highly-effective digital analytics organization--and that's not easy. Self-service reports, relevant dashboards, and other tools and techniques can help.
But they're only the beginning.
This guide covers all you need to know to build a well-resourced digital analytics team, and then back it with cross-functional support and alignment from IT, marketing, finance, the executive team, and beyond...while successfully applying analytics across the business. You will learn what it means to be "doing analytics": creating analytical processes and managing teams; collecting and governing data; analyzing paid, owned, and earned media; performing competitive and qualitative analyses; testing and optimization; targeting and automating; integrating digital data; using predictive modeling and other data sciences; and much more.
But they're only the beginning.
This guide covers all you need to know to build a well-resourced digital analytics team, and then back it with cross-functional support and alignment from IT, marketing, finance, the executive team, and beyond...while successfully applying analytics across the business. You will learn what it means to be "doing analytics": creating analytical processes and managing teams; collecting and governing data; analyzing paid, owned, and earned media; performing competitive and qualitative analyses; testing and optimization; targeting and automating; integrating digital data; using predictive modeling and other data sciences; and much more.
Drawing on years as a pioneer in the field, Judah Phillips covers the business management, process, technical, and analytical work required to tell accurate "data stories" that answer crucial business questions.Â
