Text Analytics for Marketing
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Overview
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