The process of finding out if you got into the university course of your dreams at your preferred educational establishment is a stressful time.
Fortunately for some students, the process just got a whole lot easier, thanks to the successful pilot of a cloud-based, artificial intelligence (AI) solution provided by Oracle to the University of Adelaide, implemented by Oracle Platinum Partner, Rubicon Red.
At the end of each academic year, the University, which is consistently ranked in the top 1 percent of the world’s universities and recognised globally as a leading research establishment, is overwhelmed by enquiries from potential students. In South Australia, Year 12 students need support when their ATAR score – the number used to gain entry to university – is released. Students rush to contact the universities to which they’ve applied, to find out if they are eligible to receive bonus points. These can boost their final adjusted ATAR and may be the difference between them securing a place on the course they want or missing out.
University of Adelaide’s Associate Director, Prospect Management, Catherine Cherry, said, “During such a stressful and anxious time, we don’t want applicants having to wait in long queues on the phone to speak to us. It’s important that they can get their adjusted ATAR score as quickly as possible and start discussing what their results mean for them with their families, their friends and university of choice. Our Adjusted ATAR chatbot meant students didn’t have to wait – in the busiest hour we had approximately one user every five seconds! The response has been fantastic, with more than 60 percent of users rating their interaction as ‘Awesome’.”
The chatbot is accessed via social media from the University’s own Facebook messenger page. It enables potential students to get the answers they want, in their own time – without having to hold in phone queues or wait for an emailed response. Having been trained on questions used in previous years to help determine a student’s adjusted score, around context and using deep learning-based natural language understanding (NLU), the bot provides natural, conversational and personalised responses, and can even include comments like congratulations on their results.
Powerful machine learning also helps the bot pick things up and learn as it goes along, making it more powerful as usage increases. It also remembers previous conversations and their context, making it very easy to use and its responses more accurate.
On just the first day, prospective students conducted an estimated 2,100 unique conversations with the chatbot, a number far greater than anticipated. This led to 40 percent reduction in calls to the University’s enquiry service on results day – and more impressively, a 47 percent drop in calls during the critical first three hours. In turn, this reduced the average wait time for queries made via telephone – from an average of 40 minutes down to about 90 seconds. In addition, staff in the University’s call centre were freed-up to address more complex queries and handle its backlog of emails.
Franco Ucci, Senior Director, Oracle, said, “Providing great customer service is essential in today’s world, but it can be hard to scale, leaving delivery gaps. Previously, the University’s incoming student call volumes with ATAR queries were so high, the customer call centre couldn’t field them all. Now they can and have time to turn their attention to other areas. After all, the University has a team of around six people nurturing around 70,000 students. It was a really satisfying experience to help it try something different and get such a great result.”
John Deeb, CEO, Rubicon Red, said, “In just four weeks we were able to gather the requirements, define the conversation flows and implement the solution in time for the ATAR score release before Christmas, meeting a critical, time-sensitive need for the University of Adelaide. Oracle Intelligent Bots solution made it easy to design, prototype, iterate and then roll into production to meet the compressed timelines.”