- A higher education organization wanted to use their data to improve enrollment KPIs
- Aptitive build an end-to-end cloud based data solution to improve access and visibility of data
- The solution led to immediate insights and paved the way for advanced analytics solutions
Just the Headlines
Short on time? Here are the key facts.
How do you convert qualified prospective students into enrolled students? It’s a question that schools everywhere struggle to answer as they aim to improve their enrollment efforts. One global education company knew the answer lay in their data. The problem was efficiently accessing and analyzing their data.
This higher education company had over 90 disparate data sources at their disposal, all containing relevant, yet complicated data on prospective students. This company knew that a centralized source of information could improve their analysis and reporting around student enrollment. What they didn’t know was how to consolidate the unique source systems, business units, processes, and definitions of the 10+ managed institutions under their main umbrella.
Our client needed a strategic partner to maximize the analysis of their student journey and improve their enrollment rate. After reviewing their options, they chose to work with Aptitive for our ability to implement a reliable data integration strategy that aligned with their enrollment goals and vision. Along the way, we helped them implement a Modern Cloud Data Warehouse in Snowflake to centralize their data and enable their team to gain better visibility into prospective students and optimize outreach.
From the start, our team worked closely with the Marketing department to understand their typical student journey. For example, the client wanted to understand what happened from the initial point of inquiry to the point at which the student was enrolled, including:
- The average length of time from start to finish
- The average number of touchpoints required to boost enrollment
- The average cost of converting qualified prospective students to enrolled students
In order to do this, we first had to ingest data from several places such as Salesforce, Banner, and TM1. Although they were all different source types (ie. API-based, Oracle-based, etc.), we were able to utilize Alooma in conjunction with AWS Lambda functions to bring in all the data quickly and efficiently.
Once we brought the data in, we modeled the data into a Star Schema within Snowflake and created a dimensional layer that fed the Tableau dashboards. That way, the client’s users could use their cloud data warehouse to analyze an extensive range of sources with minimal effort, creating data visualizations that provided clear and actionable insight.
The Data Warehouse and dashboards empowered the Marketing department to run a wide range of crucial reports. Their new cloud data warehouse offered them visibility into the entire student journey and set the foundation for advanced analytics to come. These dashboards also shed light on major gaps and inconsistencies in their data and metric definitions that allowed for collaboration across institutions, and more unified, compelling reporting.
The next part of this project will be to implement an advanced analytics solution that will create a more customized student journey, increase qualified student applications, reduce the time from inquiry to enrollment, and even increase student satisfaction.
Understanding the recruiting pipeline metrics is just one of the benefits they gained from the centralized data and improved reporting. They now have a foundation that will enable them to find insights such as:
- An applicant’s likelihood to succeed as an enrolled student
- An enrolled student’s lifetime value
- The applicant pool’s overall qualifications (based on undergrad metrics, application information, test scores, etc.)
- The admission & recruiting team’s performance based on:
- General Conversion Rate
- Tuition Deposits Received