PRK 3662 Insight-driven communication

PRK 3662 Insight-driven communication

Course code: 
PRK 3662
Department: 
Communication and Culture
Credits: 
7.5
Course coordinator: 
Håvard Huse
Product category: 
Bachelor
Portfolio: 
Bachelor of Communication Management - Programme Course
Semester: 
2020 Spring
Active status: 
Active
Teaching language: 
Norwegian
Course type: 
One semester
Introduction

Deriving insights is an increasingly important success factor in today's communication environment. Measuring, analyzing, and implementing data into decision-making processes create effective and efficient PR and marketing campaigns. With societal issues increasingly occupying management's agenda, communication departments are increasingly tasked to gather and develop insights into complex problems. On the agency side, value is increasingly created through creative and strategic planning, which itself is dependent on creating insights.

In this course, the general objective is to provide students studying PR and marketing communication the adequate competence to use these insight- and data-driven methods/tools. Data is collected from online sources such as social media, blogs, forums and websites. This will give students the ability to understand audiences, to become skilled in developing persuasive and customized messaging, to select the best communication channels for messages, and ultimately, to achieve optimal results. The emphasis of the class will be on application and interpretation of the results, providing input for making real life business and communication strategy decisions. We will focus less on the mathematical and statistical properties of the techniques used to produce these results, and more on the methods used in analysis of the data itself.

Learning outcomes - Knowledge
  • Students will obtain an understanding of the role of data in today's marketing and communication environment, and will get acquainted with modern methods used in planning and completing research tasks.
  • Participants will learn new approaches of gathering and extracting insights from data, ranging from visual presentations to network analysis of new online data from media such as Facebook, Twitter or Google.
Learning outcomes - Skills

Students will get to know effective ways to derive and present findings from data, ranging from visualization to insight-driven argumentation. In detail, students will learn to:

  • Use tools to analyze data from Google, Twitter and Facebook
  • Design appropriate visual presentations of data
  • Use data to define stakeholder personas
  • Build coherent arguments based on data
General Competence
  • Strong emphasis will be laid on methodological concerns and a fundamental understanding of the nature of data.
Course content

1. Introduction: Why Insights
This part of the course will introduce the importance of insights for communication strategies, and will showcase advances in small and big data generation and exploitation. Students will obtain insights into the applicability of such approaches for data-driven campaigns and will develop an understanding for the nature, opportunities and challenges of data.

2. Using Big Data for Business Challenges
Students will be provided with an in-depth introduction to the concept of big data, and ways of making the most of information and mining techniques that technology has enabled. These lessons will specifically look at the potential for such data for strategic insights as well as the design, implementation and measuring of marketing efforts.

3. Tools to generate insights
Students will work hands-on with various new media to learn ways to explore trending topics, discover what stakeholders are talking about, analyze fan pages, examine friendships and gain an understanding for web site traffic and networks.

4. Advanced topics
Students will learn about recently developed techniques for data analysis, as well as new technology which could play a part in communcation professions.

5. Presenting Insights
Participants will learn about presenting their insights to a wider audience, and will discuss the challenge of finding a fit between audience needs and proper data presentation. Both principles for structuring arguments, as well as data presentation tools, including reports, dashboards, visualizations, and key metrics will be explained.

Teaching and learning activities

The course will combine formal lectures with workshops. The course will consist of the following elements: 

- Formal lectures that aim to provide basic knowledge of the topics and a conceptual framework;
- Tutorials on using different software solutions for analyzing and visualizing insights
 

This is a course with continuous assessment (several exam components) and one final exam code. Each exam component is graded by using points on a scale from 0-100. The components will be weighted together according to the information in the course description in order to calculate the final letter grade for the examination code (course). Students who fail to participate in one/some/all exam elements will get a lower grade or may fail the course. You will find detailed information about the point system and the cut off points with reference to the letter grades when the course starts.

At re-sit all exam components must, as a main rule, be retaken during next scheduled course.

Software tools: 

The course will use Tableau and Gephi software.

Software tools
Gephi
Tableu
Qualifications

Higher Education Entrance Qualification.

Required prerequisite knowledge

Students are expected to have taken classes in statistics and have a working knowledge of MS Excel and JMP/SPSS. 

Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Submission
Form of assessment:
Written submission
Exam code:
PRK 36621
Grading scale:
Point scale
Grading rules:
Internal examiner with external supervisor
Resit:
All components must, as a main rule, be retaken during next scheduled course
40No 1 Semester(s)Group/Individual ( 1 - 3)Reflection paper based on the data students gathered for the poster presentation. In no more than 7 pages, students have to explain how they approached their data collection, what decisions they had to take, and the applicability of their data to a communication problem.
Exam category:
Activity
Form of assessment:
Presentation
Exam code:
PRK 36621
Grading scale:
Point scale
Grading rules:
Internal examiner with external supervisor
Resit:
All components must, as a main rule, be retaken during next scheduled course
60No20 Minute(s)Group/Individual (1 - 3)Poster presentation based on primary data. Students will gather primary data on the topic, relying on one of the approaches outlined in class. Students are expected to create a poster presentation based on this data, and to explain their findings and their applicability to a communications problem, (no longer than 20 minutes). Basis for evaluation is solely the quality of their findings and visualisations, not the presentation or language skills.
Exams:
Exam category:Submission
Form of assessment:Written submission
Weight:40
Invigilation:No
Grouping (size):Group/Individual (1-3)
Duration: 1 Semester(s)
Comment:Reflection paper based on the data students gathered for the poster presentation. In no more than 7 pages, students have to explain how they approached their data collection, what decisions they had to take, and the applicability of their data to a communication problem.
Exam code:PRK 36621
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Exam category:Activity
Form of assessment:Presentation
Weight:60
Invigilation:No
Grouping (size):Group/Individual (1-3)
Duration:20 Minute(s)
Comment:Poster presentation based on primary data. Students will gather primary data on the topic, relying on one of the approaches outlined in class. Students are expected to create a poster presentation based on this data, and to explain their findings and their applicability to a communications problem, (no longer than 20 minutes). Basis for evaluation is solely the quality of their findings and visualisations, not the presentation or language skills.
Exam code:PRK 36621
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Type of Assessment: 
Continuous assessment
Grading scale: 
ECTS
Total weight: 
100
Student workload
ActivityDurationComment
Teaching on Campus
39 Hour(s)
Prepare for teaching
60 Hour(s)
Student's own work with learning resources
45 Hour(s)
Submission(s)
56 Hour(s)
Sum workload: 
200

A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 7,5 ECTS credit corresponds to a workload of at least 200 hours.