You are here

Using Cutting Edge Digital Personalisation and Machine Learning Techniques to Enhance the Student Experience

Speaker
Mr. Piero Tintori

Terminal Four

Abstract
The expectations of digital natives engaging with a University has resulted in many of the traditional methods of communication being made redundant or at best very inefficient.

The proposed presentation will cover 5 cutting edge techniques that can be used to provide a more personalised digital engagement experience. Why should every student be treated the same
or in a similar way? Whether they are a potential student visiting the university website or an enrolled student engaging with online self service facilities, modern digital engagement, machine learning and personalisation techniques can have a significant positive on student experience. This can ultimately improve student recruitment, retention and alumni engagement levels.

The presentation will examine 5 digital engagement techniques that have a proven record of improving the student experience across a number of channels (website, portal, email, mobile and virtual learning environment).

The key discussion points are at what point certain cutting edge techniques used in commercial and ecommerce organisations can apply to a Higher Education institution.

The examples are based on dozens of real world projects with Universities and Colleges worldwide where I have been a significant measurable improvement in KPI results.

KPI improvements can include improvements in student recruitment lead generation results, faster self service capabilities, higher net promoter score results and a more engaged alumni community.

The techniques, which will be described in mostly non technical terms, are based on collecting user activity data as well as additional metadata on the specific person to deliver a highly personalised experience. An easy to understand example is where we examine website activity by a potential student. Based on this activity as well as additional data (location, previous touch points etc.) it is possible come set rules and machine learning algorithms to deliver a highly focused and personalised experience that will yield improved results (in this example, a higher level of student recruitment enquiries).

These techniques can be applied to other parts of the digital journey to increase student satisfaction and engagement.