Marketing Analytics in Digital Era (MKT-575-01W)
 
Search Engin optimization SEO
 
End-of-Course Reflection Paper
 
Objective: Write a reflection paper of 2-3 pages, using 12-point font size and 1.5 line spacing, following APA style guidelines.
 
In this reflection paper, you are encouraged to choose any content you wish to reflect upon. However, ensure that your paper includes the following steps:
 
Step 1: Identify and explain 3-4 theories or concepts that intrigued you the most during the course. Provide your interpretation of these theories or concepts to showcase your understanding of the material.
 
Step 2: Share your feelings regarding the theories and concepts introduced in the course. Analyze them by applying them to real-life experiences, if possible. For instance, discuss any changes in your perceptions or attitudes towards a subject after completing the course.
 
Step 3: Provide feedback on the course material, including both the textbook and simulations. Your comments and suggestions may be reported to the Stukent publisher for further consideration.
 
Ensure that your reflection paper is well-organized, coherent, and reflective of your learning journey throughout the course.
 
This course examines the strategic use of search engine optimization in marketing in order to
 
build profitable customer relationships. Topics in the course will include consumer search
 
behavior, search engines and algorithms, website user-experience, on- and off-page SEO, and
 
strategies for conducting SEO campaigns for traditional and niche search engines. The course is
 
designed to teach the fundamentals of SEO as well as provide practice with analysis and skills
 
associated with doing SEO for a business or organization.
 
Student Learning Outcomes
 
1. Understand the primary business function of SEO.
 
2. Perform appropriate analysis in preparation for conducting a successful SEO campaign.
 
3. Accomplish key tasks associated with SEO for websites and other media
 
4. Measure and report on SEO outcomes and make adjustments based on performance data.
 
Late assignments will be accepted up to 24 hours after the original deadline but will only be
 
awarded 80% of the assignment score.
 
Under exceptional conditions, a late assignment maybe accepted with the permission from the
 
professor.
 
However, under no circumstances will an assignment be accepted more than one week late.