In a previous blog post on the diversity of student journeys, we started exploring the idea of using analytics to better understand the challenges and needs of a segment of students compared to the entire student population. The explosion of student journeys requires more than static student journey mapping. In this post, we propose a data-driven approach that builds the mapping from the ground up and allows it to be decomposed into segments.

We want to go further than a sigle-layer student journey mapping by taking advantage of the massive amount of data collected by all post-secondary institutions. Any student experience program that wants to improve the engagement and success of students will need to focus their attention on at-risk students and explore how their journey differs from all students.

Analytics is the process of providing the insights to spark a conversation within your team and guide you towards improved services to support and further engage targeted students.

Common Approach to Student Journey Mapping

Maybe the following is a familiar sight to you.

You were probably a dozen of representatives from every sector of your institution, sharing how you each served students and when. There were probably even a few students that represented their own perspective. It’s actually a very good exercise to brainstorm a common understanding of what the traditional journey is.

As anyone who has gone through the process of creating a customer journey map, this is a manual process that documents how someone goes from being a stranger to an institution to being a customer and finally a repeating and loyal customer and brand advocate. In the case of a post-secondary student, the process can be a lot more complex than the relation that a customer has with a company.

Students are involved in a journey that is not only academic, but also a journey of personal growth, socializing, gaining experiences for future employability, etc. Your institution is an ecosystem in which students grow, not only consume knowledge. And in that regards, the mapping of a typical student journey is similar to mapping what a human life is – you can capture the basic structure, but none of the nuances.

We are of the opinion that the common approach to student journey mapping should be the first layer of any investigation of what a student’s journey is. Just like no two human lives are the same, we believe that there isn’t any typical student journey. We could almost say that services planned after a single layer student journey mapping are basically preparing to serve a student that just doesn’t exitst. They come from employees’ own construct of what a journey is, and not from the students themselves.

3 Layers Approach

Using demo data that we’ve randomly generated, but mimics what can be found on any institutional CRM, let’s first compress a student journey mapping to the following graphical representation.

Automated Student Journey Mapping - 3 Layers Approach

This first layer represents all students within an institution. Based on that institution’s CRM, we’ve transformed the data so that we now see a journey map of their needs throughout the first few months of their academic year. So for example, a student that visits the Financial Aid centre for a loan request on September 15, 2015, that interaction would be mapped as a “Financial Needs” on the week of September 13, 2015. In aggregates, we can then see how needs are changing throughout the time.

That would equate to the common approach to student journey mapping we’ve seen above. Of course, we could explore that data in an even more fine-grained matter, but we’re only showing overarching categories for the sake of simplicity. For example, the category “Financial Needs” could then be broken down by loans, awards, payment of tuition fees, etc.

Now that we have that first layer of a student journey mapping, maybe we would be interested in seeing how that journey differs for international students.

Automated Student Journey Mapping - 3 Layers Approach - Second Layer

Even though this is randomly generated data, we can now easily see how a segment’s needs differs from the rest of the students. As the first layer was constructed from the bottom up, it is then easy to segment the mappings based on student attributes, such age, program of study, gender, first-semester results, etc.

Needless to say we can look at the building blocks of our journey, which are individual mappings, such as the one below.

Automated Student Journey Mapping - 3 Layers Approach - Third Layer

Insights to Ignite a Conversation

Of course, a data-driven student journey mapping approach does require coordination between an institution’s sectors. But that’s a great benefit of such an approach as it encourages cross-sectorial communication, sharing of ideas and better understanding how each sector plays a role in the overall experience of a student.

In terms of technical infrastructure, the good news is that a lot of service touchpoints across campus are already using some kind of data tracking system, such as CRM, a student card reader, a ticket distributor, etc. All of those data sources can be transformed to provide a unifying view of a student’s journey.

And as we’ve seen previously, in aggregates, those individual mappings become segments and then entire student populations. In that regard, the data-driven approach takes the completely opposite direction than the common approach. Instead of building our student journey mapping from the perspective of a few “biased” employees and students, we’re actually building the student journey mapping from the ground up. This is a much more robust approach to any group that wants to implement improvements based on facts.

The data-driven approach to student journey improvements is anchored on the aggregation, visualization and exploration of thousands of journeys. This feeds a very rich conversation between stakeholders, leading to real improvements to student journeys. It does not provide silver bullet solutions, for example against international student’s retention challenges. But it can point you to problem areas which are then further explored by your team.

How is your team feeding the conversation as to how to further improve the experience of your students, especially for at-risk segments such as first-year students?