MKTG06074 2016 Web Analytics

General Details

Full Title
Web Analytics
Transcript Title
Web Analytics
N/A %
Subject Area
MKTG - Marketing
MKTS - Marketing, Tourism & Sport
06 - NFQ Level 6
05 - 05 Credits
Start Term
2016 - Full Academic Year 2016-17
End Term
9999 - The End of Time
Alan Kelly, Aine Doherty
Programme Membership
SG_BINTE_H08 201600 Bachelor of Business (Honours) in International Marketing and Languages SG_BMARK_C06 201600 Higher Certificate in Business in Marketing SG_BIMFR_H08 201900 Bachelor of Business (Honours) in Business in International Marketing with French SG_BIMGE_H08 201900 Bachelor of Business (Honours) in Business in International Marketing with German SG_BIMSP_H08 201900 Bachelor of Business (Honours) in Business in International Marketing with Spanish SG_BDIGI_B07 201900 Bachelor of Business in Digital Marketing SG_BSALE_B07 201900 Bachelor of Business in Business in Marketing and Sales

This module will help students to understand the role of data and analytics in contemporary marketing. Students will be introduced to a number of online platforms including Google Analytics, Facebook Insights, Twitter Analytics and LinkedIn Analytics. The module will enable students to comprehend key metrics that marketing executives require.

Learning Outcomes

On completion of this module the learner will/should be able to;


Engage with various analytical online tools and platforms to understand key marketing metrics.


Navigate the basics of the Google Analytics Platform.


Learn and use web analytical terminology and vocabulary.


Identify and understand key digital, financial and marketing metrics.


Identify the advantages of using web analytical software for marketing decision making.

Teaching and Learning Strategies

The student will engage with the content of the module through lectures, tutorials and computer labs. The student will develop and apply their learning via a number of online platforms using practical examples and exercises.

Module Assessment Strategies

Mid Term Online Exam 50%

Final Exam 50%

Repeat Assessments

Online Exam 50%

Final Exam 50%

Indicative Syllabus

Digital Analytics Fundamentals

Google Analytics Platform Principles

Ecommerce Analytics

Mobile App Analytics

Social Media Analytics (Facebook, Twitter and LinkedIn)

Coursework & Assessment Breakdown

Coursework & Continuous Assessment
50 %
End of Semester / Year Formal Exam
50 %

Coursework Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Online Exam Continuous Assessment Open Book Exam 50 % Week 9 1,2,3,4,5

End of Semester / Year Assessment

Title Type Form Percent Week Learning Outcomes Assessed
1 Final Exam Final Exam Closed Book Exam 50 % End of Semester 1,2,3,4,5

Full Time Mode Workload

Type Location Description Hours Frequency Avg Workload
Practical Computer Laboratory Practical Lecture 3 Weekly 3.00
Lecture Flat Classroom Theory Class 1 Weekly 1.00
Independent Learning Computer Laboratory Independent Learning 4 Weekly 4.00
Total Full Time Average Weekly Learner Contact Time 4.00 Hours

Required & Recommended Book List

Recommended Reading
2016-01-20 Creating Value with Big Data Analytics: Making Smarter Marketing Decisions Routledge
ISBN 1138837954 ISBN-13 9781138837959

Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics.

Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data.

By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management.

Module Resources