7/26/2019 Digital Technologies for Marketing 2015-16

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Title BMAN72272 Digital technologies formarketing

Credit Rating 15Level PGSemester 2

Course Coordinator(s) Dr Babis TheodoulidisMethods of Delivery lectures, guest speaker presentations, case

discussions, BI software demonstrationsLecture Hours 20Seminar Hours 10Private Study Hours 120Total Study Hours 150Pre-requisites This module has a capacity of 70 and is offered

primarily to students on MSc CCRM, MScMarketing and MSc Analytics. Permission isrequired for MSc students from outside the

above programmes to enrol onto this module.Co-requisites N/ADependant Courses N/AAssessment Methods andRelative Weightings

50% group project; 50% individual assignment

AimsThis aim of this elective course unit is to review digital technologies used formarketing and assess their importance and implications through case studiesand practical assignments. The course unit will define Business Intelligenceand its technological components and how this is can be used for marketinginnovation. Business Intelligence (BI) is the gathering of vast amounts of data

in order to get insights that drive innovation. It encompasses a broad categoryof technologies that allow business users to gather, store, access and analysedata to improve the customer-centric information management capabilities.Business Intelligence consists of three integrated technological components:Data Warehousing, Data Mining and Analytical Reporting. The course unit willinvestigate all three of these aspects.Learning Outcomes

Understand the principles of business intelligence and its implications formarketing innovation.

Understand the different technological components of BI namely,data/text/web mining, data warehousing and analytical reporting.

Evaluate the impact of different BI technologies for marketinginnovation.

Understand how BI technologies are used in marketing. Critically appraise future technological developments and their

implications

Demonstrate the ability to carry out independent research and criticalanalysis.

Demonstrate the ability to use BI technologies to address marketingproblems

SyllabusCourse Content and Learning Resource Details

7/26/2019 Digital Technologies for Marketing 2015-16

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During the course we will collectively analyse a number of digital technologiesin the area of business intelligence and analyse their application andimplications for marketing processes in organisations. We expect to invitepractitioners with pre-eminent roles in marketing to share their experience andkey managerial insights. Among the developments which we aim to examine,

we highlight the following: Overview of digital technologies for marketing (BI, CRM, ECM, etc) Different sources of information: internal, external, customer data,

interaction data, etc

Data collection, aggregation and summarization; data quality;

Business Intelligence processo Define business problemo Build data collectiono Prepare data for modellingo Build model (different analysis techniques: association rules,

classification, clustering)o

Evaluate modelo Deploy model and resultso Discuss various case studies of application of Business Intelligence

to Marketing

Pedagogical MethodThe pedagogical method will involve a mix of lecturers, case studies, andexercises using BI software. We recommend that students form study groupsand meet to prepare for class discussion. During case study discussions, wewill analyze the case situation and address the problems and issues it presents.We will ask students to make recommendations based on the use of BI

technologies and will discuss the implementation of those recommendations.

Reading ListThis module will be mainly taught using material available for download fromBlackboard.

Recommended BooksMichael J.A. Berry and Gordon S. Linoff, Data Mining Techniques for Marketing,Sales and Customer Relationship Management, Third Edition, John Wiley, 2011

Margaret H. Durham,Data Mining: introductory and Advanced Topics, Prentice

Hall, 2002, ISBN-13: 9780130888921

Ralph Kimball, Margy Ross, Warren Thornthwaite, Joy Mundy, Bob Becker, TheData Warehouse Lifecycle Toolkit, John Wiley and Sons, 2007