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16 September 2019

How we’re using smart question suggestions to engage your prospects

What was the challenge? 

We’re always interested in how prospective students use the Unibuddy widget. We want to see if they find it intuitive, simple and helpful. To test this, we collect data on usage, we conduct surveys, and we go into schools to see first-hand how prospective students use Unibuddy, what sort of questions and challenges they face, and how we could make it better. 

The data showed us that many students were having long, engaging conversations with student ambassadors. But lots were leaving after just one question. When we dove deeper into this trend, prospective students told us why: they didn’t always know what else to ask. 

The transition to university can sometimes be so overwhelming and unknown for prospective students that actually coming up with questions to ask is a challenge in itself! In fact, almost half of prospective students we asked said that the platform would be better if it suggested questions to them. 

So, we built a new tool to give them just that: the Question Suggestion System, or QSS! It was not straightforward to develop and required a huge effort from all different teams: including Machine Learning, Customer Success and Engineering. 

What is it? 

After a prospective student signs up and asks their first questions, QSS pops up to suggest 4 additional questions they might like to ask. The prospective student can select a question, edit it (if they wish) and send. They can access QSS anytime from their inbox – so if ever they are stumped for a question, it is there to lend a hand. 

How does it work? 

The Question Suggestion System is more than just random ideas for questions, though. We use a pool of over 400 questions, individually written (and sometimes rewritten!) by our team. They cover almost 100 different topics.

But we don’t just display them randomly. QSS is intelligent, and was built by our machine learning team. It uses our extensive understanding of our users to display topics and questions that a prospective student is likely to be interested in based on data points Unibuddy processes. 

Plus, QSS is learning and evolving. The data it collects about the impact different questions and topics have on a conversation will help develop the tool further. 

What is the value?

We put a lot of work into QSS and making sure it is effective for your prospective students, and that’s because we feel it is valuable to all of our users: prospectives, ambassadors and universities. 

QSS will help to engage and inform harder-to-reach groups who may not have any university context. You can promote the platform to a more diverse cohort who may be unsure what questions to ask – perhaps because they are the first in their family to go to university, or are from a low participation area. It’ll help all students continue their conversations, even if they might be shy or concerned about pestering the ambassador. 

The tool encourages prospective students to deepen their interactions with an ambassador. From speaking to ambassadors, we know that longer conversations are the most engaging for them. 

Plus, these longer conversations and more engaged prospectives will create a greater connection with your institution – which will have an impact on your conversion

Has it worked?

We rolled out the Question Suggestion System a month ago, and the results are already clear: it has a significant impact on a prospective student’s engagement with Unibuddy.

Conversations are, on average, 40% longer when QSS is used compared to when it isn’t. Prospective students are using the tool to inspire their conversations, and branch out into new topics. 

70% of uses are for the second or third message in a conversation: which are key moments when conversations would usually fade out or die. Instead, the QSS is encouraging prospective students to keep it going.


 

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