It鈥檚 amazing what flailing about on the internet can lead to. Over the last few years, the library has conducted various User Experience (UX) exercises, collecting a large pool of qualitative data on user thoughts and experiences of using the library. These projects have provided the information and ideas needed to carry out various to our library spaces and discovery tools 鈥 but once these changes happened most feedback sits collecting dust in various shared drives.
Alongside this, we鈥檝e gathered quantitative data through a yearly survey of our students and via our enquiry management system; some of which has been collated, examined and analyzed. However, again, much of this historic data has sat unused.
A few months ago, we began considering how to better use this data to inform decision-making and service improvement. A project was started, looking at how to use all this information and ongoing feedback as part of a 鈥榝eedback loop鈥, where we would solicit feedback, examine the results, make changes, seek feedback on the changes and start the process again.
Then COVID-19 reared its head.
Here鈥檚 one for fans of under-statement: Remote working has presented a number of challenges. An important one in this context is that seeking feedback or carrying out UX with our students has become difficult and even undesirable. When they鈥檙e already under the additional stresses that lock-down and virtual study have caused, we really don鈥檛 want to be pestering students for feedback on how we鈥檙e doing.
As I had been quite heavily involved in developing and carrying out this kind of UX, I found myself at a loose end in this part of my role. The devil waits eagerly for idle hands and I found myself beginning to think about how to use the data we鈥檇 collected in interesting and useful ways. Hence the flailing about on the internet.
A series of increasingly esoteric Google searches led me to the idea of Personas within UX. As someone who loves creating characters, either when writing bad short stories or playing tabletop games, this immediately appealed to me.
The idea is that you take the information you know about your users, both quantitative and qualitative and use it to create a number of 鈥楶ersonas鈥, imaginary users who represent the experiences of real users of your services. You give them names, backgrounds, personal challenges and their own way of thinking. You assign them comments from real users as their own and give them as genuine a personality as possible.
Once you have your Personas, you create scenarios to throw them into; situations in which your Personas attempt to navigate your processes and services.
It鈥檚 essentially an in-depth role-playing exercise, designed to allow you to put yourself in the shoes of your users in a meaningful way, flagging up hidden barriers or frustrations.
It鈥檚 a technique originally created for web based businesses and the retail sector but the more I read about it the more convinced I was that it had real practical applications in the academic library sector. Change is a part of life within libraries and we often introduce new services to our users, expecting them to get on and use them, with varying levels of support.
Of course, we review and iterate as we go, but perhaps using these Personas could give us a head start, allowing us to make invisible problems visible. I mentioned what I鈥檇 read to a manager and soon I was heading up a project to create a bank of Personas for the library.
This was a little daunting. It hadn鈥檛 really occurred to me that anyone might be interested in this as anything other than a thought exercise, so I hadn鈥檛 really considered what creating a persona would entail in practice. As I started writing the proposal, it became clear that what would be required was a lot of data and a lot of interpretation of that data.
Luckily, I鈥檓 not working alone. My colleague Rhian has lots of experience working with qualitative and quantitative data as part of her academic studies and currently works in our Virtual Advisory Help team, so is familiar with the data from our enquiry management system. Her experience and skill in wrangling data, as well as her experience as a student, has proved to be invaluable.
The first thing we needed was data. We weren鈥檛 entirely sure what data was going to be useful, so we asked for it all. The results of the aforementioned library survey, NSS results, months鈥 worth of data from the enquiry management system, and thousands of comments from various UX projects are all being trawled through, the interpretations mulled over and the meaning for individual experience discussed. We鈥檝e tried to pull all this data together in our Personas to create meaningful representatives of our student body.
We started with the library survey, focussing our attention on groups showing lower satisfaction. Wanting to create a broadly representative group, we chose level of study as the main dividing point between the Personas, making sure we had a couple of UGs, PGTs, PGRs as well as Staff. Each of these were given one or more of the aspects that seemed to mark out those with lower satisfaction in our services.
Once we had this base to work from, we turned to the enquiry management system and looked at what questions the groups we were interested in were asking us, how they were doing so and in what kind of numbers.
This is still a work in progress and what we currently have are a number of what I鈥檓 calling, 鈥楶ersona skeletons鈥; that is, individuals who are mostly a series of data points drawn from quantitative data sources.
Our 1st year Engineering Undergraduate doesn鈥檛 think of themselves as using library resources but spends a lot of time in the Information Commons with friends and accesses reports and articles that appear on their reading lists on a regular basis. Our PGR has good Information Digital Literacy skills but doesn鈥檛 understand that having access to academic databases isn鈥檛 the same as having access to all the articles indexed there. The International student prefers to contact the library by email or chat because they lack confidence in their spoken English skills.
These bits of personality are not necessarily apparent in the raw data, but the point here is to create facsimiles of real people, with all the blind spots, likes and dislikes and personal challenges this involves. Although proof for these traits is not always possible, we hope to back up many of them in the next stage of the project, when we start incorporating qualitative data.
We are going through the UX comments (of which we have many) and enquiries (of which we have even more), and picking out those we think match the thought processes, opinions and preoccupations of our personas. We hope to build up an image of them as real people and make it as easy as possible for us to understand how they think and how they will react to new or changing services in the scenarios we鈥檒l eventually drop them into.
We鈥檙e aware that we鈥檙e approaching this from an Information Point perspective, as people who work as the first point of contact for users in the Library. We鈥檙e going to need the perspectives of colleagues who have a different relationship with our users; from our Faculty Engagement Team, to colleagues advising on Open Access and those engaged with researchers accessing our special collections. We鈥檙e keen to draw on staff experiences to create really strong, 3-dimensional individuals.
Going through our data has thrown up some interesting omissions. Although our library survey asks about gender identity, age and disability, it doesn鈥檛 include questions on race, something we know to be an important factor in people鈥檚 experience of using libraries. Although we know that people who identify as being of a non-binary gender have lower satisfaction ratings than the average, we don鈥檛 really know why from the quantitative data. Disability is included, but the question 鈥榙o you consider yourself to have a disability?鈥 is so broad as to be next to useless for our purposes.
These factors affect a person鈥檚 interactions with the library in wildly different ways and we should include as many as possible, in real and meaningful ways, within our project; the purpose of which is to view our services from different perspectives.
We hope to match our Personas with demographic data from University sources, to create models that are representative. But, unfortunately, this will only be surface-level data until we can start soliciting feedback from students again. I am not Black, Disabled, or Gender-non conforming. I cannot know how these factors affect a person when they interact with the library without asking them. Until we can speak to people for whom these factors are part of everyday life about how this affects their experience of our services, our personas will never be whole.
Fortunately, our student body is diverse and engaged, I hope that this part of the project can evolve as we settle into the 鈥榥ew normal鈥 and that we can solicit real insights into the unseen prejudices and barriers that affect users鈥 interactions with the library.
The Personas we are working on now are a first iteration, a proof of concept. The next stage will be the creation of scenarios to put them through, to see if they produce interesting results, flag things we may have missed or point to support that may be required.
The eventual aim is to produce a 鈥楶ersona toolkit鈥 which would include these personas and advice on creating scenarios to run them through. These could be used by colleagues across the library to stress test their systems, processes and spaces.
I鈥檓 hopeful that this will prove to be a practical and useful way to use all that data that we鈥檙e so good at gathering and to impact our services and spaces in meaningful ways, helping ensure that we are at the centre of the University experience for all students, not just those that we already serve well.
Stephen Mould 鈥 Library Services Manager
Rhian Whitehead-Wright 鈥 Information Advisory Services & Skills Co-ordinator
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