Monash Uni takes student loan requests via Apple Business Chat

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Monash Uni takes student loan requests via Apple Business Chat

Also creates new group to uplift chatbots across institution.

Monash University is using Apple Business Chat to make applying for financial assistance less confronting for students.

Digital transformation group manager Josh Teichman told the recent Salesforce World Tour in Sydney that the university is the “first organisation to have launched Apple Business Chat on the Salesforce platform”.

Apple Business Chat launched in Australia in October last year, though it is still officially in beta.

It allows companies to communicate directly with customers via iMessage.

In order to use it, companies must login via a customer service platform, with Salesforce among those supported.

Teichman said the university’s first Apple Business Chat experience was launched to students in March.

“All students can now engage with us over a native iMessage conversation for iOS users,” he said.

“We've picked a use case that can be quite confronting for students.

“This is a student who, for example, needs a loan and needs financial assistance, so they can now request that financial assistance through the iMessage platform.”

Teichman said that Business Chat meant that students did not need to physically attend the university to apply in-person and provide paperwork.

“It can be quite a confronting ask that they bring in paperwork,” Teichman said.

“They can do all of that now through the chat platform straightaway. It means that they're doing it in the privacy and security of their own device.”

Teichman said that although the service was initially just for iOS users, “we'll be rolling this out across non-iOS users as well soon.”

Chatbot uplift

Teichman also revealed that Monash University has spun up a new internal “experimentation group” to perform “high velocity experiments” to raise its digital capabilities.

He said the group is initially targeting capability improvements for chatbots, of which the university currently has around 10.

Those improvements could be to “handoffs to a live agent, identity verification, [or to] sharing knowledge articles”, Teichman sad.

“There's a range of different things,” he said.

“Each experiment lasts about a week or two. We prove out the technical feasibility of that experiment, and then we industrialise it - we turn it into something that we can then deploy across the range of chatbots across the organisation.”

Teichman said chatbots and digital channels generally had proliferated at the university because it was how students wanted to engage.

“At Monash, we don't have a choice [on digital],” he said.

“Our target customers are millennials. They're not going to come in and walk in anymore, they're not going to pick up the phone to us. They want service straightaway on any channel.

“Whether it's about their exams, whether it's that they need counseling support, or for students that live on campus, they want access to support 24x7, so we have to evolve.”

Teichman said the university’s first foray into chatbots was to provide Q&A to students following the release of exam results.

“When students do their exams and the University releases all of the results, we get a very high spike in inquiries: ‘I failed, what do I do?’, ‘who do I talk to?’, ‘I need special consideration’, ‘what do these grades mean?’,” Teichman said.

“We really targeted that use case. We went back through all of our historical data in Salesforce, pulled out what the top 20 questions were, piloted it and refined it.

“The second time we ran it, we saw about an 85-90 percent success rate. It was amazing.”

Teichman said that the university’s chatbots are evolving to go “deeper, reaching into the systems of record, pulling out [things like] student grades” and generally making the bots “more intelligent and more useful”.

He also said the university is standardising the natural language processing (NLP) engine it uses to backend its chatbots on Salesforce’s Einstein Bots product.

“It's OK to have multiple [NLP] engines, but you just need to understand which one is going to be used for which use case in the organisation,” Teichman said.

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