Using big data for customer centric marketing

This chapter deliberates on “big data” and provides a short overview of business intelligence and emerging analytics. It underlines the importance of data for customer-centricity in marketing. This contribution contends that businesses ought to engage in marketing automation tools and apply them to create relevant, targeted customer experiences. Today’s business increasingly rely on digital media and mobile technologies as on-demand, real-time marketing has become more personalised than ever. Therefore, companies and brands are striving to nurture fruitful and long lasting relationships with customers. In a nutshell, this chapter explains why companies should recognise the value of data analysis and mobile applications as tools that drive consumer insights and engagement. It suggests that a strategic approach to big data could drive consumer preferences and may also help to improve the organisational performance.peer-reviewe

Academic Plate Spinning: the Difficulties of Balancing Full Time Degree Study With a Part-Time Job

The study examined full-time students engaged in part-time work during term time. A qualitative approach was used to examine how students cope with simultaneously managing the two activities, and how part-time working affects their academic study. Semi-structured interviews were used to obtain data from a sample of 30 undergraduate business students. The findings confirm that students merely satisfice many aspects of their lives, with reading time and assignment preparation being key areas that suffer in order to allow students to engage with part-time work. Possible options available to HEIs to adapt to, and remedy, the situation are explored

Trumpet Initial Data for Boosted Black Holes

We describe a procedure for constructing initial data for boosted black holes in the moving-punctures approach to numerical relativity that endows the initial time slice from the outset with trumpet geometry within the black hole interiors. We then demonstrate the procedure in numerical simulations using an evolution code from the Einstein Toolkit that employs 1+log slicing. The Lorentz boost of a single black hole can be precisely specified and multiple, widely separated black holes can be treated approximately by superposition of single hole data. There is room within the scheme for later improvement to re-solve (iterate) the constraint equations in the multiple black hole case. The approach is shown to yield an initial trumpet slice for one black hole that is close to, and rapidly settles to, a stationary trumpet geometry. Initial data in this new approach is shown to contain initial transient (or "junk") radiation that is suppressed by as much as two orders of magnitude relative to that in comparable Bowen-York initial data.Comment: 18 pages, 18 figure