• MKAY9000
  • Digital Metrics & Analytics 1

  • Credits (ECTS): 5
  • Marketing

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as part of a programme.
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Module Description

Digital marketing is synonymous with measurability and the digital marketer of the future must not only be comfortable with managerial level analytics but rather demand and drive the diffusion and traction of such analytics both at the campaign and enterprise wide level. The ever-evolving repertoire of digital assets and channels allow for innumerable consumer insights and marketing intelligence. This also presents the concomitant challenge of strategically leveraging this data into actionable and timely intelligence as a prerequisite to optimizing and rationing valuable resources and budgets. Being acquainted with key metrics and performance indicators and applying analytical tools to digital contexts such as campaign analysis, customer value analysis, channel and segment analysis; allows for strategic, scientifically sound decisions to be made as well as scenario and sensitivity analysis being conducted incorporating risk and opportunity assessment. This module will traverse some analytically based treatments of key resource allocation decision contexts and ROI measurement; spanning the funnel journey from prospect to lead to engaged customer, with customer lifecycle and lifetime values being examined. The use of spreadsheet tools, optimization, sensitivity analysis, online tools will be engaged as needed to facilitate the analysis of actions undertaken or opportunities being assessed based on various metrics and performance measures. It is intended to be closely aligned to the issues and analyses appropriate to campaign and customer analysis and will be practically oriented. It is intended to imbue and impart to the learner a disposition towards quantitative assessment, analysis and reporting; being careful to achieve a balance between the necessary theory and application in a practical setting. It will be cognisant of and sensitive to diverse learner profiles and will generally emphasize an applied and example-driven approach with a view to communicating the results and decision implications to key stakeholders in the digital marketing scenarios examined. The general aim is that of developing marketing professionals who are analytically disposed and empowered; making use of available software tools and analytical techniques as needed.

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 typically be drawn from the following and other content as needed:

Introduction to the metrics and analytics imperative: The challenge of data, digital channels and tools audit, industry reports and future trends and challenges.
Introduction to and usage of key metrics: An examination, assessment and usage of key metrics. Over viewing of key digital, marketing and financial metrics. Understanding key metrics that marketing executives need and use with examples and homework tasks. Relating them to the customer lifecycle (acquisition, conversion, engagement, retention) and the marketing enterprise
The KPI process: Outlining the process of identifying, measuring and presenting context specific Key Performance Indicators. Developing and presenting management dashboards. Identifying appropriate actions accruing, communicating with management. Examples and homework tasks and case studies
Campaign economics and analytics: Examine some simple digital campaign contexts and conduct basic analyses: PPC, CPM, SEO, Email etc and present the key metrics such as return on investment (ROI) and present findings. Class examples and homework tasks, use of free online tools and calculators
Spreadsheet Analysis: Conduct simple and Multi-channel analyses using Excel spreadsheets.
Scenario and sensitivity analysis. Investigating the impact of changes to inputs. Optimization, capital budgeting and optimization techniques. Class examples and homework tasks
Software and Simulation: Engage with some online tools and software such as Simbound (team based simulation of digital marketing campaigns etc), online ROI tools etc.
Testing and experimentation: Understand the imperative of testing in a digital context and be familiar with the basic underpinning statistical concepts of AB and Multivariate tests. Sample size, margin of error, confidence levels and hypothesis testing. Case studies and practical examples. Vendor testing tools
Multi-criteria decision making: MCDM; evaluating decisions based on multiple and possibly conflicting options and associated metrics.


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.