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Marketing Analysis – (M.Sc.)

Ghent University

Faculty of Economics and Business Administration
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Disciplines:
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Annual Tuition Fee: ≈ € 541
Location: Ghent / Belgium / View location on map ▾ Hide location on map ▴
Duration: 12 months Start Date: October
Educational Form:
  • Taught
Education Variants:
  • Parttime
  • Fulltime
Languages: English 
3.727601,51.045903

Location of Ghent University

The Master of Marketing Analysis is a one-year full-time study (or two-year part-time study) about predictive analytics for analytical Customer Relationship Management (CRM)/Business Intelligence topics in English covering data-mining techniques. More specifically, the study mainly focuses on: Analytical Customer Relationship Management/customer intelligence (i.e., using data-mining techniques to uncover Knowledge in Databases (KDD)), as well as market/marketing research. This high-quality degree is offered at the low price of 541 EUR (London, UK) upon completion of the project. During the academic year 2007-2008, again four MMA students wrote their master thesis about a project at DunnHumby Ltd.

The education of CRM specialists involves teaching students aspects from three disciplines: 1. Marketing & Marketing Research, 2. IT (databases), and 3. Statistics and Data Mining as shown in the figure below. What makes our advanced master program unique is the fusion of the technical aspects (IT, statistics & data mining) with the business knowledge and insights. This clearly differentiates our graduates from e.g. general MBA programs as well as master in statistics programs.


Contents

In an increasingly competitive world, just competing on superior product performance has become very tough. Therefore, companies have turned toward leveraging existing customer relationships. Actively managing customer relationships includes the following objectives:

1. Acquisition (identifying & attracting new customers)

2. Cross/up-selling (profitable usage stimulation)

3. Retention (identifying customers who intend to attrite/churn, and trying to keep profitable customers)

4. Recapturing lost customers

Each of these objectives can be supported by analytical tools powered by traditional statistical techniques or data mining algorithms. Hence, the field of analytical Customer Relationship Management (aCRM) has seen stellar growth.

This new approach to conducting business has been acknowledged by book authors such as Thomas Davenport & Jeanne Harris in 'Competing on Analytics' (2007) and Ian Ayres in 'Super Crunchers' (2007). The MMA program is not a master in marketing management, but it focuses on research and highlights mostly quantitative issues. The target group consists of both people with working experience and young graduates who feel the need for an in-depth education in marketing analysis. By bringing together a group of motivated students and teachers, and by dynamic and multimedia teaching methods, the Department of Marketing is striving to transfer in-depth knowledge of the marketing field.

Analytical Customer Relationship Management In analytical CRM, we try to capture customer dynamics, i.e. customer inflows as well as outflows. CRM analysts construct statistical/data mining models to better understand, as well as predict customers' future behavior. This makes customer intelligence very actionable, because we are able to quantify, e.g. the probability a customer is going to stop purchasing a firm's products/services in the coming year. This 'propensity to churn or attrite' can then be used to rank their entire customer base in order to prioritize which customers should receive special customer retention treatment. Using targeted marketing campaigns, analytical CRM empowers companies to learn from their campaigns, and finetune offers to different customer segments. Hence, businesses often turn to customer intelligence to increase their marketing ROI (return on investment). This enables marketing departments to become more accountable.

Many studies have shown that a good way to improve customer retention is to sell more products to the same customers, i.e. extend the portfolio of products or services bought from a given supplier. Of course, given a specific customer profile, companies would like to know what is the next most-likely product or service a customer is going to buy. In analytical CRM, we build cross-sell/up-sell models, also known as NPTB (next product to buy) models. These enable marketing analysts to target customers with the most appropriate product.

Customer intelligence goes beyond mere 'business intelligence', which is interpreted by software vendors as just report generation, and/or OLAP applications used to find reasons for deviations or above/below-average performance of businesses. While this approach is valuable, customer intelligence goes beyond reporting about the past. It empowers analysts to predict the most likely future events of individual customers.

In the Master of Marketing Analysis, we teach the analytics to build these analytical CRM models for retention, cross-sell, marketing optimization, ... . This gives our graduates a real advantage on the job market, because these are sought-after skills in today's competitive markets.

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Requirements

This advanced study is a program with an in-depth approach focussing on two groups.
On the one hand, the program is intended for people with some years of professional experience who feel the need for a serious in-depth training in customer relationship management, marketing analysis and communications. In particular, the program is focusing on people holding or aspiring a specialized marketing function within profit and non-profit organisations. These people are granted the opportunity to spread the program over two years. Consequently, courses are spread evenly over both years.
You need a 'second cycle' academic degree in a relevant discipline. This basically means you need 4 years of university education in a related discipline, a Bachelor's degree is generally not enough.
Also, you need proof of English proficiency.
Check the programme website for details.

Additional Requirements

Minimal degree required: Bachelor's degree
Minimal amount of work experience Not specified

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