Marketing Analytics: Fundamental Data-Driven Marketing

Harvard Extension School

MGMT E-6750

Section 1

CRN 24774

View Course Details
This course introduces marketing analytics for non-technical audiences, including web analytics and data modeling. As big data moves into the mainstream, marketers are seeing the opportunity to make the profession more scientific and numbers-driven than ever before. Marketing analytics is one of the largest areas of marketing today. In addition, with measurement at the center of every marketing campaign, marketers have the opportunity to prove the return on investment of their programs with unprecedented accuracy. Yet, this wealth of data can be overwhelming. Every channel has its own metrics, every demographic group's behavior can be mined for targeting information. What are the numbers that matter? And what are they really telling us? How can we best leverage marketing analytics to optimize results? This course explores the growing role of data in marketing. Taking a two-fold approach, the course focuses on the data of marketing. Students learn how to use the two main categories of data available to marketers: internal, or what is called marketing analytics; and external, or big data. In this course, students learn web analytics fundamentals, creating data dashboards, and predictive analytics. This is a purely data-driven course; it does not teach programming. Using real-world examples and practical exercises, the course allows students to understand the interactions between both kinds of data, and how best to use analytics to improve marketing outcomes, demonstrate return on investment to the c-suite, and create increasingly effective marketing campaigns.

Instructor Info

Christina Inge, MS

Chief Executive Officer and Founder, Thoughtlight


Meeting Info

W 5:30pm - 7:30pm (1/27 - 5/17)

Participation Option: Online Synchronous

Deadlines

Last day to register: January 23, 2025

Prerequisites

MGMT E-6000, MGMT E-6615, or the equivalent.

Notes

This course meets via web conference. Students must attend and participate at the scheduled meeting time.

All Sections of this Course

CRN Section # Participation Option(s) Instructor Section Status Meets Term Dates
24774 1 Online Synchronous Christina Inge Open W 5:30pm - 7:30pm
Jan 27 to May 17