Scale Personalisation Across the Student Experience | Liferay
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How to Scale Personalisation Across the Entire Student Experience

Explore the value of personalisation as universities are looking to deliver a differentiated student experience.
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Universities across the globe are increasingly looking at the role student experience plays in creating a lasting competitive advantage. Equally, the need to deliver a differentiated experience has only increased off the back of the COVID-19 pandemic. The growth in online course delivery has opened new opportunities for students to study outside their immediate geographic location, creating a more competitive environment.

As universities increase their investment in delivering a differentiated student experience, the value of personalisation has equally risen. A personalised experience is not only one that is aware of the individual user, but also the context through which they are engaging with a product, service, or application. That is to say, it is one that is contextually aware of what the user is looking to achieve and adapts to deliver access to the information, services, or tools in a more streamlined and efficient manner.

How to scale that experience across 5,000, 20,000, or even 50,000 students is then often viewed as a challenge. But it doesn't have to be. In this article, we will look at how universities can scale personalisation across their entire student base.

The Individual is the Starting Point

To deliver a personalised experience, you need to start with an awareness of the individual. This provides the foundation from which you can segment and adapt the experiences you deliver to the student.

Student portals often act as the central gateway that unifies the disparate systems, resources, and information for that individual, and as a result, it needs to be aware of the individual traits that define who that person is. At a basic level, this should include:

  • What they are studying (courses and units)
  • Where they are studying (on-campus or online)
  • How long they have been studying (part-time/full-time and number of years they have completed to date) 

Often this information comes from one or more systems, such as a student information system (SIS) or CRM, across the university. Being able to bring this information together and leverage data points from multiple systems provides for a richer student experience.

A student portal armed with this knowledge of the user creates a wealth of options to optimise the end-user experience. Beyond understanding what the student is studying, information and access to resources and different student services can be personalised by their mode of study or experience as a student. For example, a student who has just commenced their studies remotely may be prompted to engage with different information or services compared to a 3rd year student who studies on campus. The end outcome of each engagement is the same, to support the student, but by being contextually aware, universities are able to deliver more timely information and support services that have a greater likelihood of providing value to the student.

The Value of Segmenting Students Based on Known Information

Segmentation of students can take two broad themes: 

  • Known information - These are largely static data fields that change over a longer period of time (i.e. at the end of each semester or even over the course of an entire academic year). Examples include the course a student is studying, the mode in which they study, or past academic results. 
  • Acquired information - This is information about a student that is acquired over time through the use of analytics, and is often more dynamic and changes more frequently. For example, analytics may inform you of the specific times a student logs into their student portal and how often they do so, or even predict likely academic outcomes for upcoming assessments. 

While the ultimate end goal of a university may be to deliver a personalised experience based on real-time data and predictive analytics, the value of what is already known should not be overlooked. Creating segments of students based on these known attributes allows a university to scale the personalised experience they provide across segments of students with multiple attributes in common. For example, a university could segment a group of students based on the following attributes:

  • Studying economics
  • Studying part-time and online
  • In their first year of study
  • Scored less than 60% in their most recent assessment

With this segment defined, the university can now deliver targeted content and messaging via their student portal and other marketing channels. Given they are studying online, perhaps they are prompted to attend an online video call to discuss additional support options that may be available to them. With this example, we can very clearly see how the known information we have about a student allows us to create an experience that feels unique to them, while still allowing the university to target students at scale.

What's more, this type of segmentation can be replicated with ease over numerous different situations or groups of students, with each segment gaining access to information, resources, and tools relevant to them at that particular time of their student journey.

Enhancing Personalisation Through Dynamic Segmentation

As the previous section alluded to, moving to dynamic segmentation of students based on real-time data of a student and their academic performance, interests, and engagement with tools and resources is often the end goal for many universities.

To achieve this, it is right that universities look to the value of advanced analytics and machine learning to accelerate the delivery of models that can segment students and predict outcomes. However, a challenge that often results shortly after this investment is navigating how to take all of the data and insights to actually deliver the experience that has been identified as valuable to the student based on the analysis?

In this situation, you really see the coming together of advanced analytics and digital experience platforms (DXPs). In many respects, the analytic capability can be viewed as the backend, feeding data and insight to the frontend or DXP that can then use these dynamically generated segments to change, update, or modify the student experience on the fly. For example, the moment an analytic model predicts that a student is likely to fail a particular course, their experience in the student portal is updated dynamically. Information around the course material, study preparation, and support resources is elevated to the home page. A chatbot is automatically opened on the next login with questions prompting the student for feedback and targeted messaging can be delivered across their preferred mode of communication.

What the above ultimately defines is a scaled approach universities can adopt to deliver a personalised student experience at scale. Beyond the theory, however, universities need to ensure they have the tools to empower staff to create these experiences without heavy IT involvement. One of the key benefits of personalisation is the value it provides to the student and the university. However, to deliver on that promise, marketing teams, student support teams, academics, and content creators need the ability to iterate and update messaging in low code and WYSIWYG-based interfaces. Ultimately, the ability to test, iterate, and improve is what will lead to the best student outcomes and deliver on the promise of personalisation. The ability to achieve that is restricted if the tools and applications supporting this endeavour are not designed to empower users across various departments and functions of a university.

Success Story - Enabling Meaningful Online Interactions for Remote Students

See how the University of London created streamlined and engaging experiences for 170,000 students by enhancing their student portal. As the oldest provider of distance education, the portal has allowed remote students to engage with the university in a meaningful way online, which has seen increased levels of engagement and satisfaction.

Originally published
March 9, 2022
 last updated
March 9, 2022
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