• MKAY9003
  • Digital Metrics & Analytics 2

  • Credits (ECTS): 10
  • Marketing

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Module Description

Digital marketing is a data rich environment and deploying effective and sophisticated analysis tools to customer data ranging from the acquisition process to conversion to value generation is part of the remit of the modern digital marketing analyst. Being conversant with, amenable to and comfortable with the usage of analytics to extract insight and drive decisions is going to ensure the strategic fit and role of the digital marketer in the modern organization. Being able to bridge the gap between technical analyst and the traditional marketer confers a differentiating advantage to the learner. The module continues the theme of key metrics and performance indicators as developed in the first module and applies these and other analytical tools to digital contexts such as testing and experimentation, customer lifetime value analysis, segmentation analysis etc. It is intended to be closely aligned to the issues and analyses appropriate to campaign and customer analysis and link to and integrate with other modules of the course such as campaign planning and budgeting. It. will be practically oriented with a view to engaging the learner towards marshalling and mastering various analytical tools towards an in-depth group project and presentation. Following on from the initial module it is intended to further engage the learner with analytics pertinent to the digital marketing context and more specifically to analyse aspects of the customer engagement and conversion. This will be facilitated through carefully chosen examples and contexts and to utilize case study examples to illustrate the applications. The learner will have the opportunity to transfer the learning (facilitated and self-directed) into a tangible format through a major group based project where a management level report is generated based on a digital marketing scenario.

Indicative Syllabus

Given the dynamic nature of the digital analytics arena it is envisaged that likewise the content will evolve and adapt. Course content will be drawn from the following and other content as needed may be made available:

Software and Simulation: Possibly engage further with some online tools and software such as Simbound (team based simulation of digital marketing campaigns etc), online ROI tools etc.

Segmentation Analysis:
- Introduction, segmentation tools appropriate to the digital context.
- Basic clustering analysis,
- Using transactional data-RFM analysis etc

Customer value analysis:
- customer lead-generation analytics &ROI,
lifetime value analytics CLTV
- Churn and segment analysis.
- Applying and developing spreadsheet templates to the contexts described above.
- Scenario analysis. Examples and homework tasks and case studies
- Use of neural networks to score and segment customers

Synthesis: Synthesis and review of the various analytical elements covered towards extracting value and insight from marketing data and actions.

ISCED:342: DO NOT USE - ARCHIVE HEA 2014
Total Contact Teaching Hours:47

Please note that the catalogue is provided as a guide to modules in DIT. Not all modules listed will necessarily be offered every year and new modules may also be added. Information subject to change. For detail on specific programmes/modules please contact the relevant School directly.