BMAN71641 : Social Media and Web Analytics

Credit rating 15
Teaching period(s) Semester 1
Aims

The aim of this course unit is to showcase the opportunities that exist today to leverage the power of the Web and social media; to develop students’ expertise in assessing social media web marketing initiatives, evaluating web optimisation efforts, and measuring user experience; and to equip students with skills to collect, analyse and derive actionable insights from web clickstream, social media chatter, and online testing.  A key feature of this course is the use of hands-on software tools for analysing web and social media interactions.

Objectives (Learning outcomes)

Academic knowledge

  • Be able to understand  social media, web and social media analytics, and  their potential impact
  • Be able to understand usability, user experience, and customer experience
  • Be able to understand the relationship between user experience and ROI

Intellectual skills

  • Be able to understand usability metrics, web and  social media metrics
  • Be able to identify the metrics and key performance indicators for a given goal
  • Be able to determine data relating to the metrics and key performance indicators
  • Be able to analyse and interpret the data generated from online testing and and collected from Web and social media tracking tools

Subject practical skills

  • Be able to design and conduct social media marketing campaigns
  • Be able to use various data sources and collect data relating to the metrics and key performance indicators
  • Be able to use ready-made web analytics tools (Google Analytics)  and social media
  • Be able to understand a statistical programming language (R) and use its graphical development environment (RStudio and Deduce) for data exploration and analysis

Transferable skills

  • Be able to demonstrate group working skills and academic writing skills
Assessment methods

Examination (60%): Multiple short questions (60%) plus an essay question (40%). Calculators not permitted

Coursework (40%): Group report on measuring a social media marketing campaign using both social media and web analytical methods

Information

Informal Contact Method

Office Hours

Online Learning Activities (running and managing group projects using a social media enhanced mobile groupware; performing social media marketing campaigns, using web and social media tracking tools)

Course unit overview
  1. Introduction
  • The Web and social media (Websites, web apps, mobile apps and social media)
  • Usability,  user experience, customer experience, customer sentiments, web marketing, conversion rates, ROI, brand reputation, competitive advantages
  • Web analytics and a Web analytics 2.0 framework (clickstream, multiple outcomes analysis, experimentation and testing, voice of customer, competitive intelligence, Insights)
  1. Background
  • Data (Structured data, unstructured data, metadata, Big Data and Linked Data)
  • Experiment design (selecting participants, within-subjects or between-subjects study, counterbalancing, independent and dependent variable; controlled experiments, online testing and A/B testing)
  • Data analysis basics (types of data, data types and common statistical methods, presenting data graphically)
  1. Measuring user experience
  • Usability metrics (performance metrics, issues-based metrics, self-reported metrics)
  • Planning and performing a usability study (goals, metrics and evaluation methods, participants, data collection, data analysis)
  • Typical types of usability studies and their corresponding metrics (comparing alternative designs, comparing with competition, completing a task or transaction, evaluating the impact of subtle changes)
  1. Web metrics and web analytics
  • Web metrics and Google Analytics
  • PULSE metrics (Page views, Uptime, Latency, Seven-day active users, Earnings) on business and technical data;
  • HEART metrics (Happiness, Engagement, Adoption, Retention, and Task success) on large-scale behavioural data; 
  • On-site web analytics, off-site web analytics
  • Goal-Signal-Metric process
  1. Social media analytics
  • Social media analytics (what and why)
  • Social media KPIs (reach and engagement)
  • Social media marketing campaigns
  • Performing social media analytics (business goal, KPIs, data gathering, analysis, measurement, and feedback)
  1. Data analysis language and tools
  • Ready-made tools for web and social media analytics (Google Analytics, and analytical tools within social media systems)
  • R programming language (data types, control flow, input and output, plotting)
  • R graphical development environment (RStudio and Deducer)
  • R for data extraction (through RFacebook and TwitteR), exploration and analysis (correlation, mean comparison, linear regression, word frequency, and sentiment analysis in R)
  1. Cases and examples
  • User experience measurement cases
  • Social media marketing cases
  • Social media analytics cases
  1. Group work and hands-on practice
  • Data analysis using software tools (Google Analytics, RStudio and Deducer)
  • R Programming practicing (practices in classroom and exercises after each lecture)
  • Social media marketing campaign planning and measurement (group coursework)
Teaching staff No available data to display.
Timetable Assessment written exam - 2 hours
Lectures - 30 hours
Seminars - 3 hours
Teaching and learning methods No available data to display.