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Big Data & Marketing Technology

Introduction

Modern digital marketing practice is as much dependent on a suite of technologies and information systems, as it is on strategies and marketing technique. Commonly these include a mixture of digital and data technologies that underpin each stage of the marketing lifecycle, from initial research through to campaign analysis and customer retention. Inevitably, any discussion of marketing technology in today's market, also necessitates a focus on big data and the associated analytics methods. The utilisation of such data and techniques has become an essential toolkit for implementing and optimising modern digital marketing strategy.

The module aims to expose participants to the latest in marketing and big data technologies, and apply them to a range of digital marketing scenarios. To do this module seeks to provide digital marketing students with an overview and first-hand experience of a range of these technologies, including:

  • data visualisation,
  • customer analytics tools,
  • social media analytics,
  • marketing automation,
  • artificial intelligence,
  • cloud computing,
  • mobility,
  • internet of things.

Objectives

Upon successful completion participants will be able to:

  • Demonstrate a comprehensive understanding of the uses of big data and marketing technologies in modern business
  • Critically analyse the systematic and operational risk associated with a business’ information architecture, and develop appropriate mitigation and management strategies
  • Critically evaluate a range of real-world marketing technology solutions, and determine their applicability and suitability to a range of different use cases
  • Interpret complex business requirements and develop appropriate, higher-level solutions and designs

Syllabus

1) What is marketing technology?

  • Marketing technology fundamentals
  • Information architecture
  • Marketing automation

2) Big data

  • Data architecture for marketing
  • Social media, internet of things and APIs
  • Artificial intelligence and machine learning

3) Analytics

  • Marketing analytics
  • Data visualisation & dashboards
  • Customer segmentation technologies
  • Social media analytics

4) Marketing automation & mobility

  • Mobile technology and location marketing
  • Multivariate and A/B testing
  • Chatbots and personalisation
  • Automation technologies

5) Cloud computing

  • Cloud fundamentals
  • Cloud migration
  • Cloud native computing

6) A practical simulation of the above topics

Assessment

  • Technology Presentation (30%)
  • 4,000 words Post Module Assignment (70%)

Duration

2 weeks including 21 hours of lectures and 18 hours of seminars