PhD Studentship: Identifying and Understanding Complex Behaviour from Transactional Data
The University of Nottingham
Nottingham, England
1d ago

PhD studentship with Nottingham University Business School’s N / LAB.

We are looking for an enthusiastic PhD student who will undertake original multi-disciplinary research in the fields of data science / machine learning and consumer / human behaviour.

Supervised by N / LAB’s experts in data science / machine learning this PhD studentship provides an opportunity for people interested in developing novel statistical measures and methods to quantify, understand and leverage complex consumer behavioral regularity.

Working with already acquired real world data (representing over 16 million regular customers) from N / LAB’s extensive group of collaborating industrial partners, the PhD provides an unparalleled opportunity to push forward research that will drive significant impact in predictive and descriptive analytical applications as well as contributing to knowledge regarding consumer / human behaviour.

Identifying and understanding regularity in consumer behaviour is a key component of business analytics. Examples range from customer / store segmentations (e.

g. frequency) to automated predictive systems (e.g. automated email targeting) and management key performance indicators (e.

g. repeat buying behaviour). However, regularity remains a tricky thing to measure. Traditional methods; such as average purchase frequency, repeat brand rate or statistics quantifying deviations from random interevent times are too coarse grained to adequately capture the true complexity of our regularity’.

This significantly reduces their utility as measures / features in end-use applications, such as customer segmentation / understanding (i.

e. within marketing campaign development or management strategy planning) or customer behaviour prediction (i.e. churn prediction).

Reasons for this failure can be roughly grouped into three categories :

  • the presences of mediating factors (e.g. promotions, lifestyle, emotion, and life stage),
  • incomplete observations and
  • non-stationary behaviour. When these are not taken into account, regularity measures report high irregularity.
  • However, in reality the behaviour is regular once these factors are taken into account.

    Recent advances in computational methods, and the systematic collection of consumer transactional data, now mean that the more complex measures of consumer behaviour regularity are within reach.

    The PhD will investigate :

  • The development and extension of frameworks for quantifying consumer behaviour regularity within the context of mass transactional datasets and
  • The development of novel statistical models.
  • Depending on the individual student, the developed methods are likely to deliver advances in one or more of the following application areas :

  • churn prediction with long prediction horizons,
  • consumer life stage identification and
  • prediction and / or understanding / predicting consumer variety seeking behaviour.
  • This funded PhDs will commence from 1st October 2019. A yearly stipend at current RCUK rates (£14,777), plus UK / EU student tuition fees (£4,350), is available to the successful applicant.

    Applicants should have :

  • A 2.1 or higher honours degree in a social science, and
  • A Master’s degree which includes a substantial research element, with a score of 65% or above in the taught modules and 65% or above in the dissertation.
  • Complete the . Your application must include a and should indicate the area in which the research will be conducted and the key issues that you want to examine in more detail.

    In addition, please also enclose the following with your application form :

  • Transcripts of all your academic qualifications. If you have not completed your Master’s degree yet, you should include a transcript of the marks received to date.
  • Any offer is conditional upon achieving the required standard.

  • 2 academic references.
  • English language test result, if English is not your first language.
  • Entry onto our PhD programme is very competitive. If you fulfil all of the admissions requirements it does not guarantee that you will be offered a place. We also consider :

  • The quality of your research proposal.
  • The fit of your research area with potential supervisors.
  • References.
  • Your personal statement.
  • Closing date : 23.59pm BST on 23rd January 2019 . Applications submitted after this time will not be considered.

    Shortlisted candidates will be called for interview to be held in Nottingham on Thursday 7th February 2019 . The successful candidates will be notified by Friday 15th February 2019.

    For further information, please contact :

  • Dr. Gavin Smith ()
  • PhD Open Day

    We are holding a PhD open day on Wednesday 12th December 2018 more details can be found

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