City, University of London share how they transformed their Clearing process using the Gecko platform
Can you imagine Clearing without the phones ringing off the hook on A-Level results day? It’s an image that’s pretty synonymous with Clearing, but it’s not necessarily the future. City, University of London have always been ahead of the curve when it comes to their Clearing process.
In 2020, they were one of only four UK universities that didn’t have a telephone number on their website during Clearing. Instead, they used Gecko technology to swap phone calls for a chatbot to create a real competitive advantage during Clearing.
City, University of London has been using Gecko since May 2020. They wanted to use Gecko specifically for Clearing and were interested in how the chatbot module could support it. Dominic explained how the reason for that change in approach was threefold…
“We know 18-year-olds expect more immediate customer service. We know that they’re less patient than they used to be, and we were seeing that in all of our interactions. Enabling a chatbot where someone could get an immediate response to a question aligns with current expectations of students, which are changing and quickening over time.”
“We’re an international university. We have students here from 150 different countries, and therefore a number of those prospective students that are asking questions are asking them outside of office hours. Around 40% of the conversations that we were having on a chatbot last year about Clearing were outside of nine to five working hours. They’re questions that couldn’t have been answered as quickly or as effectively without the chatbot.”
“We receive around 25,000 inquiries a year via email. Our Clearing operation in 2020 was, for the first time, completely remote, and so we had to find a way to use technology to mitigate the fact that there were resourcing challenges. Before we had 150 temporary members of staff who answered telephone calls in Clearing, and they would triage the information they gathered during those calls to the relevant people. But that model doesn’t really work if everyone’s from home and you don’t have 150 ambassadors on hand.
City, University of London set up their Clearing process using an AI form that assesses qualifications and information and makes automated decisions. The Gecko chatbot complemented that process by handling a high volume of enquiries coming in, with members of the team assigned responsibility for the chatbot on the day.
Dominic explains, “That that first day of Clearing is almost everything, right? The likelihood that a student will convert if you make them an offer at 10 o’clock on that first day is really high, but it just goes down after that. An offer that you make four days later is worth 10% of an offer that’s made on that first morning, so you have to get it right.
“The chatbot was the first point in that user journey during the day. We run online chat sessions with humans, using a different product, which enables prospective students to have conversations online. We use the bot to handle the frontline of those questions during Clearing, before handing off to a human if the person requested that.
“We now have the chatbot in two places; we have it on the Clearing page, we also have it on the university’s main inquiries page. And that’s to reduce the number of people who actually make an inquiry via CRM because that’s just more work for people to do.
Clearing can be a really stressful time for universities. There aren’t many other industries where so much of your income is reliant on a short period of time. That pressure can be felt throughout the build-up – for staff as well as prospective students. That’s why, as we already mentioned, one of the really interesting things that City, University of London did, removed one of the most traditional methods of communication – the phone line!
“In 2019 our Clearing strategy was very much around, ‘Here’s our telephone number, call us.’ However, in 2020, we were one of four universities in the country that didn’t have a phone number to call during Clearing. We didn’t feel we needed it because we had this triage system with the AI form, the Gecko chatbot, and online sessions.
“We felt prospective students didn’t need to call us because there are other, better, methods of communication on the day, and actually, we probably don’t want them to call, because we can’t manage 8,000 people calling at the same time. We were much more effective in the handling of our inquiries in 2020 than we were the year before when we didn’t have that system, and the Gecko chatbot is absolutely part of that success.”
City, University of London got their chatbot up and running in a matter of weeks and this meant that they were able to have it ready in time for Clearing. Dominic explains…
“The implementation is really good. It’s intense, but it’s very quick from out-the-box to getting the bot up and running. Johnny, who is Head of Customer Success at Gecko, is fantastic. Everybody loves Johnny, and so that really helped our implementation.”
1) Decide who you want to be involved in the implementation process. We went with the view that to try and get buy-in of university staff we had to get as many of them involved as possible. And so we had between 20 and 30 people that were part of the implementation week. Our learning was that that probably wasn’t necessary.
2) Pump your bot full of the most frequently asked questions and answers. For this, I think you really only need a handful of people to do this. You need people who know what kinds of questions are asked and what answers should be given, and then people with a logical mind, supported by or facilitated by Johnny.
3) Train your bot by asking it additional questions. We made a decision to spam – or train – the bot even further in order to prepare for Clearing. We paid 20 or so student ambassadors to spend three hours just asking the chatbot questions. Once we’d done that we got it up and running for it to organically get better.
4) Decide whether the bot answers questions or you just drop a link. When you go through the implementation process you have to decide whether you use the chatbot to direct users to the website and say, ‘You can find the answer to that question here or whether you use the chatbot to answer those questions within the conversation. On the whole, we did the latter because I think that’s what people expect when they’re talking to a chatbot. They don’t expect to just be fired off to a web link, they expect to get an answer. But you do have that choice.
5) Think about where your chatbot will sit on your university website. From a Clearing point of view, if your bot sits on your Clearing homepage, it’s fairly straightforward because the questions you’re most likely to get will be about Clearing. When you put it on the university’s home page, it could be asked about literally anything. And so that would take a much longer period to become fully effective.
