Text Analytics for Marketing

Overview

Subject code

MKT

Course Number

4620

Description

Text analytics is a useful tool in the world of Digital Marketing and Analytics due to its usefulness in deriving business and strategy insights from content shared by consumers through reviews and recommendations (from websites like www.tripadvisor.com,www.amazon.com etc.) and consumer conversations (from social media websites like facebook.com, twitter.com etc.). Thus, text analytics methods and its applications are of great interest to companies, both big and small, and the demand for professionals with skill sets in various facets of text analytics has been on a steady rise. Note: Text Analytics is a “Hybrid” course that meets once a week on campus with the remaining work done asynchronouslyby students in the Blackboard LMS.This course approaches the world of Text Analytics from a business strategy perspective by introducing students to popular methods applied to analyze consumer conversations and content and by aiding students in understanding and interpreting the results obtained through such methods. The industry terminology around Text Analytics and Text Mining is decoded in this course, by preparing and analyzing unstructured textual information and demonstrating practical applications of Text Analytics methods to identify key themes and hidden meaning from unstructured data. At the end of the course students will demonstrate an understanding of how to develop powerful new marketing strategies to elevate customer experience, solidify brand value, and elevate reputation.This course is structured for current and future business professionals without expertise in statistics, math, and programming.

Career

Undergraduate

Credits

Value

3

Max

3

Min

3

Course Count

1

Number Of Credits

3

Number Of Repeats

1

Repeatable

No

Contact Use

Yes

Generate Attendance

No

Left Use

Yes

Present Use

Yes

Reason Use

Yes

Tardy Use

Yes

Template Override

No

Time Use

Yes

Attendance Type

Class Meeting

Auto Create

No

Code

LEC

Instructor Contact Hours

3

Default Section Size

35

Final Exam Type

Yes

Include in Dynamic Date Calc

No

Instruction Mode

In Person

LMS File Type

Blackboard CourseInfo 4

Name

Lecture

OEE Workload Hours

0

Optional Component

No

Preferred Room Features

Academic Scheduling

Workload Hours

3