While most institutions are keenly aware of the impact student experience has on their retention and enrollment numbers, higher education leaders voice concern with the current state of communications and engagement efforts at their schools. Only 16% of the industry’s CIOs report students are getting the right personalized message at the right time. Why?
Due to the rapid and prolific growth of digital tools over the last decade, institutions are managing a complex, disparate set of applications. Add to that a growing list of communication channels available and it’s no surprise having a consistent, personalized and campuswide engagement strategy is a challenge.
While predictive analytics has already been in use by some institutions, much of the insights are still siloed by department or college and not shared across campus. When AI and predictive analytics are collectively applied to existing information, they are powerful tools that aid schools in addressing the complexities standing in the way of student communications. This combination enables the kind of student experiences that drive positive increases in enrollment, retention and overall student success.
Improving student experiences with personalized responses
One of the most dynamic aspects of AI is its ability to comb through large amounts of data and create human-like recommendations, specific to a given individual’s unique needs. For student communications, AI can help create more personalized engagements by automatically pulling in information from across campus systems to inform interactions.
Take, for example, a student inquiring about enrollment deadlines via a virtual assistant on a school’s website. Using AI and predictive analytics, schools can provide an automated answer based on the individual student’s profile. Not only will it communicate on deadline, but it will also suggest relevant follow-up content beyond the virtual assistant such as follow-up two-way text messaging, based on the individual student’s profile. Here’s another: Maybe they have an overdue tuition bill or need a reminder that housing registration is coming up. An integrated AI system has that information and can quickly pull it into current and future conversations.
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This kind of personal, human-like and cohesive engagement across multiple communication channels can enhance student experiences and keep them on track to success.
Equally as important as personalization, AI can also protect a student’s anonymity. Consider an individual inquiring about financial aid qualification or food security programs on campus. Today’s AI systems can leverage predictive analytics to understand when those questions are likely to come up—based on keywords, sentiment or past interactions—and offer students the option to stay anonymous throughout an engagement. This ensures they feel comfortable during a two-way text, virtual assistant or live chat interaction and also ups the chances of helping the student resolve or find support for whatever issue they are facing.
Enabling proactive communications based on student needs
When applied in a centralized way, AI solutions can bring together data from across campus systems to flag upcoming deadlines, tuition payments or financial aid opportunities. Schools can identify when a student may be at-risk and help identify any barriers they are facing early to mitigate negative outcomes.
Communication strategies can also benefit from AI and predictive analytics. By identifying how, where and what to communicate with students as well as alumni groups, families and prospects, AI can aid schools in bolstering engagement and delivering on brand promises from admissions to post-graduation.
Outcomes-based approach
Campuses across the nation are abuzz with the potential AI and predictive analytics can bring to higher education. And while that potential is broad, it’s critical for institutions to think about AI in the context of what problems it can realistically and cost-effectively solve. Its value is best realized when the underlying data is unified, domain-specific and accurate. In the case of student engagement, AI and predictive analytics can be applied to unify siloed information across systems, better understand student needs and automate support in a personalized, cross-channel way.
By blending the best in machine learning with staff expertise, schools can help get the right message to the right student at the right time to enhance experiences, improve enrollment and foster campuswide success.
