Bayes Centre

Introduction to Big Data and Analytics in Marketing

This online course aims to introduce participants to fundamental aspects of the use of big data in marketing to harness the power of digital and connected technologies.

Course Summary

Big data is changing the way marketers understand customers and create marketing solutions. The internet and other digital technologies create increasingly large amounts of customer-centric data, which can be systematically extracted and analysed to inform marketing decisions. This introductory level course will provide participants with a basic understanding of the use of big data and analytics when applied to the marketing domain. An emphasis on recent industry examples will allow learners to engage with contemporary best practice. The course is intended for those who have some prior work experience in marketing and those who wish to reskill in this area. 

Participants will be introduced to professional practice concepts such as customer analytics, which allows for a more efficient targeting of different types of existing and potential customers (‘micro segmentation’). Topics covered may also include automated or optimized pricing based on machine learning, and the use of artificial intelligence in digital social media. Possible practical activities on the course will include simulating an online sale of a product or service and comparing customer analytics using a dashboard software (such as Google Analytics or Facebook Audience Insight). In addition to these practical activities, learners will explore legal and ethical considerations of such contemporary approaches in marketing.

The course will be taught through online sessions consisting of lectures and practical workshops. In addition to attending weekly teaching sessions, learners will be expected to engage with supplementary materials such as video recordings, audio podcasts and introductory readings. 

On completion of this course, learners will be able to:

1. demonstrate a critical understanding of big data and its uses in marketing;

2. identify and apply knowledge of analytics to practical contexts within marketing;

3. reflect on current professional practice in this area.

 

There is no essential reading. The recommended books below may be of interest in preparing for the course.

Sathi, A., 2014. Engaging Customers Using Big Data: How Marketing Analytics Are Transforming Business. New York: Palgrave Macmillan.

Verhoef, P., Kooge, E., and Walk, N., 2016. Creating Value with Big Data Analytics: Making Smarter Marketing Decisions. Abingdon: Routledge.

Course Delivery Information

This course will be offered twice in the 21/22 academic session:

Start Date (1): 2nd - 30th October 2021    
Course Duration: 5 weeks    
Total Hours: 15 contact hours across 5 weeks, with one session every Saturday (10.00-13.00)    
       
Start Date (2):  14th - 18th March 2022    
Course Duration: 5 days    
Total Hours:  15 contact hours across 5 days, with one session every weekday (10.00 - 13.00)    
       
Method of Assessment: No formal assessment but participants will have the opportunity to reflect on their professional experiences through team work and self-assess their learning through online quizzes.    
Level:  University foundation level (SCQF Level 7). The course is of an introductory nature and no prior experience of university study is required.    

Entry Requirements

There are no entry requirements for this course. Participants should be 16 years or older at the course start date.

In order to participate in this course, students will need access to a computer with the ability to play video materials, and an internet connection. Students will need to be able to confidently use videoconferencing software and be comfortable with using websites.

English Language Requirements

You must be comfortable studying and learning in English if it is not your first language.

Course Fees and Funding

Course fees for 21/22 are £350, but funded places are available for people employed, unemployed or furloughed in Scotland who meet Scottish Funding Council eligibility criteria.

Determining eligibility for a funded place for upskilling takes a number of things into account, including fee status, but also location of employer. SFC provide guidance specifically for upskilling courses:

“Courses/provision is open to all Scottish-domiciled/’home fee’ students, which is consistent with SFC’s policy for core funded student places. Students from the rest of the UK (rUK) are not normally considered eligible for SFC funding. If however a university is working with a Scottish/UK employer which has a physical presence or operating in Scotland, rUK employees of that employer would be eligible.”

Organisations like UKCISA, and the University, provide guidance on how to determine your fee status:

If your fee status is Scotland Fee Rate, RUK Fee Rate, or EU-EEA Pre/Settled Scotland Fee rate, you may be eligible for a funded upskilling place. To determine this we will look at your fee status, residency information and, where relevant, details of your employer, to confirm whether the employer is based in, or has a significant presence, in Scotland.

Funding eligibility will be assessed at the point of each application for each course; you may be asked to provide further information if you do not meet the general residence conditions. Please email us at bayes-training@ed.ac.uk if you would like to discuss your funding eligibility before applying.

Please note that full-time students (including full-time PhD students) are not eligible for funding.

 

Apply Now

Applications for March 2022 are now open.

In order to verify that you meet the eligibility criteria for this course, please complete the application form at the link below:

​​​​If you have any questions about the application form or the course in general please email bayes-training@ed.ac.uk

Once complete, your application will be processed in 1-2 weeks. Applications will be processed on a first come, first served basis with priority given to applicants who meet the criteria for a funded place. We aim to email all applicants within 2 weeks of submission regardless of the outcome of their application.

Cohort 1: 2nd October.  Applications are now closed. 

Cohort 2: 14st March 2022.  Applications close 6th March 2022 at 4pm. APPLY HERE