We often think of digital analytics as simply counting website visitors, visits and pageviews.
However, this guest post by Jim Williams, a product analyst at GDS, and Tony Duarte, service manager on the Prison visit booking exemplar shows how teams can use innovative digital analytics to track user behaviour in the early stages of development, in order to improve a service for users.
About the service
Currently different prisons book visits in different ways. Visit bookings are mostly done by telephone or email and often requires family members to spend a long time making calls at inconvenient times and waiting several days for their booking to be confirmed. The digital service makes the process easier for families and friends with loved ones in prison and the aim is to encourage frequent visits from a range of people, whilst maintaining security.
Importantly, with the digital service visitors can select three alternative booking slots to increase the likelihood that a visit can be booked.
Submissions result in an automatic notification email being received by the visitor, and an email with all the relevant details being received by prison visits booking staff in the prison social visits mailbox. Her Majesty's Prison Service staff then make a booking in the backend system and reply to the visitor's request with booking confirmation details.
The service meets the needs of prison visitors to book social visits easily and at their convenience. Unlike telephone booking lines, the online service is not reliant on the working hours of prison staff - it’s accessible 24/7 and the process of booking is far quicker. It also meets the needs of prisoners by supporting rehabilitation through increased social visits as staff can process a greater number of requests for visits more quickly.
Capturing slots booked using digital analytics
We anticipated that allowing visitors to select three alternative booking slots would increase the likelihood that their preferred slot would be available and would make the best use of prison visiting facilities, ensuring that visiting times would be well attended. It was therefore important that the project team could track how many booking slots visitors were selecting.
The first innovative way the prison visit booking team used their digital analytics to improve the service design was by uploading the number of slots selected to their digital analytics tool using whats called a custom metric. Each time a user completed a booking the number of slots selected for that booking was recorded against their visit. Collecting this information for every booking allowed the calculation of the average number of slots selected per booking.
The figures showed that people using the early beta design of the slot picker (below) selected an average of 1.4 slots per booking:
Our user research confirmed what the analytics was showing, and this finding led us to redesign the layout of the slot picker (below). The new design was simpler, placed the slots to the right hand side of the screen, and communicated more clearly to users that they could select up to three slots.
This new design changed the way users engaged with the page and produced an average of 2 slots per booking. Using digital analytics in this way enabled our team to rapidly improve the service. Although user testing has shown that some visitors will simply not be able to select more than 1 or 2 convenient dates, we plan to release further improvements to the slot picker design that should drive average slots per booking even higher for those who can make use of this flexible way of booking.
Booking requests completed
The second innovative way the team used digital analytics to inform service design was to track the number prison visit bookings made by each prison in the pilot. This was done by setting up custom dimensions and completion goals. Dimensions are characteristics of a visit such as referral source, mobile device or country, but in this example the prison name associated with the booking was uploaded to the digital analytics tool. Bookings which were tracked as goal completions could then be compared across the different prisons in the pilot.
The chart below shows the number of prison visits booked online:
Cardiff was generating around 40% of the bookings in comparison to Rochester and Durham. On investigation, we discovered that Cardiff were slower to replace the non-digital paper form process and had not considered updating their telephone messaging system to promote the digital service. As soon as these things changed, booking increased rapidly.
This data could have been accessed directly from the prison service. But, in uploading the data to the digital analytics solution, the data was made available centrally and in near real time, without placing a demand on prison staff resources. This allowed us to monitor the performance of the pilot and quickly make changes to maximise success.