Data Analytics For Student Enrollment: What to measure
Increasing student enrollment is one of the most critical aspects of any higher education institution’s success. One way to achieve this is by leveraging data analytics to improve the enrollment funnel, which encompasses the stages a prospective student goes through before becoming a full-fledged student. In this article, we will discuss the importance of analytics in higher education enrollment funnel, including the key performance indicators (KPIs) to measure and the enrollment funnel components.
Importance of Analytics in Enrollment Funnel
Analytics can help higher education institutions in the enrollment funnel by:
- Increasing Student Enrollment: Analytics can provide insights into the success of recruitment efforts and help identify ways to improve them. By analyzing data from various sources such as website traffic, social media engagement, and application rates, universities can tailor their marketing strategies to target the right prospective students and increase conversion rates.
- Improving Student Retention: Analytics can also help institutions improve student retention by identifying at-risk students and providing them with targeted interventions. By analyzing data from various sources such as learning management systems, student information systems, and surveys, universities can identify factors that contribute to student attrition and take action to improve student success.
- Increasing Transfer Rates: Analytics can also help institutions increase transfer rates by identifying transfer students’ needs and tailoring their marketing and support strategies to meet those needs. By analyzing data from various sources such as transfer application rates, transfer credit evaluations, and transfer student success rates, universities can identify barriers to transfer and develop strategies to overcome them.
- Improving Graduation Rates: Analytics can also help institutions improve graduation rates by identifying factors that contribute to student success and taking action to address them. By analyzing data from various sources such as course completion rates, credit accumulation rates, and time to degree, universities can identify students who are at risk of not graduating and provide them with targeted interventions to help them succeed.
Enrollment Funnel Stages & Data to Consider
The enrollment funnel is composed of several stages that students go through before becoming a full-fledged student. These components include:
- Awareness: This is the stage where prospective students become aware of the institution and its programs. This can be through marketing efforts, word of mouth, or referrals. Data such as engagement in campaigns is key.
- Interest: This is the stage where prospective students show interest in the institution and its programs. This can be through visiting the website, attending an information session, or speaking with an admissions counselor. Data such as website visits and time on site as well as information downloads are key as it establishes your pool of inquiries.
- Application: This is the stage where prospective students submit an application to the institution either through the common app or via the institution’s application system. Data such as number of applications submitted is key.
- Admittance: This is the stage where prospective students are admitted to the institution. This can be through an acceptance letter or an email. Data such as number of admitted students, admission acceptance rate are important.
- Enrollment: This is the stage where admitted students enroll in the institution. This can be through an enrollment deposit or a registration process. Data such as deposit conversion rates are indicative of your performance especially within your target market.
Key Performance Indicators (KPIs) to Measure
The following are some of the key performance indicators (KPIs) that higher education institutions should measure:
- Student Enrollment: The number of students enrolled in a program is an important KPI to measure as it determines the revenue generated by the institution. It also provides insights into the popularity of the program and the overall demand for higher education.
- Student Retention: The percentage of students who continue their studies after the first year is an important KPI to measure as it indicates the effectiveness of the institution’s support programs and the quality of the education provided.
- Graduation Rates: The percentage of students who graduate within the expected time frame is an important KPI to measure as it indicates the effectiveness of the institution’s academic programs and the overall success of the institution.
- Financial Sustainability: The revenue generated, expenses incurred, and net profit/loss are important KPIs to measure as they indicate the financial sustainability of the institution and its ability to provide high-quality education in the long run.
What Data and KPIs are Important
It is important to focus on the KPIs that are relevant to the institution’s goals and objectives. While all KPIs are important, some may be more relevant to a particular institution than others. For example, a research-focused university may prioritize faculty performance indicators such as research publications and grants awarded, while a teaching-focused institution may prioritize student retention and graduation rates.
It is also important to avoid focusing on KPIs that are not relevant to the institution’s goals and objectives. For example, measuring the number of social media followers may not be relevant to the success of an institution unless social media is a key component of the institution’s marketing strategy.
In conclusion, data analytics has become an important tool for higher education institutions to improve student outcomes, streamline operations, and ensure financial sustainability. By measuring the relevant KPIs and focusing on the goals and objectives of the institution, universities and colleges can use analytics to make data-driven decisions and achieve their mission of providing high-quality education to their students.
Additionally, tools like the 3E Enrollment Run Rate Scenario Simulator provide practical support in forecasting enrollment and revenue, enabling institutions to make informed decisions about their future.