02.06.16

Event

Breakfast Briefing: Using Behavioural Science to Extract Value from Big Data to Further Power your Business

  • #Personalise the internet
  • #Big Data Analytics
  • #Behavioural science

See how Keyrus applies the University of Cambridge Psychometrics Centre’s API to aid HR, Marketing, Brand Positioning and Product Design.

   

Details

Date : 2nd June ‘16
Time : 8:00am – 10:00
Cost : Free 

Location : Eight Club Bank - http://www.eightclub.co.uk/bank

http://applymagicsauce.com/

more information – to link to : Keyrus event 06/02/2016

Agenda : 
Intro to Keyrus and University of Cambridge Psychometrics Centre Demonstrations

  •     HR use case
  •     Marketing use case
  •     Brand Positioning use case
  •     Product Design use case

In keeping with continuous innovation and research in the analytics field, Keyrus, and the University of Cambridge Psychometrics Centre are pleased to announce their joint partnership. This partnership will benefit any organization that would like to access and implement the Apply Magic Sauce API. As Big Data will only continue getting bigger and the demand for smarter tools can only increase, this partnership is a collaborative and timely step into the future of business analytics.

Cambridge Psychometrics Centre API is a uniquely powerful trait prediction engine, giving access to accurate and ethical prognoses of psycho-demographic variables at the level of the individual. By integrating this API with Keyrus’ delivery track record methodologies and the most advanced information technologies in the market, Keyrus can create value for its clients, helping them reveal the desires, personalities and motivations driving the diverse range of behaviour in their unstructured organisational data.

In this breakfast briefing we invite you to join us and see how Keyrus and the University of Cambridge Psychometrics Centre will make its clients’ Big Data more actionable, helping them to develop a more sophisticated and personal understanding of their customers.  We will illustrate, with examples, how Organisations will now be able to develop natural language processing and predictive machine-learning models to transform digital footprints into personality and behavioural analysis.