How to Make Data-Driven Decisions in Higher Education Marketing

Data-driven decisions help businesses in the edtech industry make the most of their resources and connect with the right education professionals at the best possible time.

Data and analytics can inform everything from priorities, in terms of product development, to how to market a new or existing edtech offering to specific groups of clients. Businesses can and should leverage the power of data-driven decisions to clarify their goals and strategy for development. This can be especially important in the world of higher education, where data is vital for defining a marketing strategy and making it effective.

data decisions

Data-driven decision-making uses accurate information analysis to inform business action.

What is data-driven decision-making?

Data-driven decision-making draws on real, accurate information to make important business choices. While intuition and observation will always have a place in crafting strategy, informing decisions with data can lead to thoughtful, accurate and positive results.

Data-driven decision-making tools can cover a lot of ground, from providing intelligence that guides the high-level creation of a marketing campaign to influencing things at a more granular level, like generating a specific list of educators and administrators to contact. Effective use of data-driven decision-making means a business is more informed and confident – and for good reason.

Why should you use data-driven decision-making in higher education?

Professionals in the education space regularly move between roles and institutions, and the world of higher education, in particular, isn’t an exception. Class loads and educational focuses for professors can easily change, and administrators can move into a variety of roles as well as start working at a new college or university.

Data-driven decision-making can help your business market edtech systems in a relevant and targeted way. Ensuring you have accurate data around contact details and professional roles, for example, means the professionals included in a marketing campaign likely have a meaningful connection to the benefit your solution provides or the problem it’s built to solve.

When can you use data-driven decision-making in higher education?

Data-driven decision-making can influence everything from the development of new edtech solutions that support improvement in student learning outcomes to the marketing campaigns that raise awareness of them. Outreach efforts present a particularly clear case for the value of data-driven decision-making.

With an accurate and current list of potential contacts, your company can effectively tailor its marketing efforts to a specific, clearly defined group. That includes everything from creating optimized territories for sales staff to making sure every instance of initial outreach is targeted toward a relevant professional. Whether your solution focuses on providing insights into student retention or predictive analytics tied to academic performance, you won’t waste valuable time and effort on ineffectual outreach.

How can automation power learning and teaching?

Automation is a valuable tool for educators and students alike. Education professionals can use automation in applications ranging from software that helps manage course scheduling to budget and resource management concerns. They can also use it to assist in tracking student performance. Students increasingly use automation in majors like computer science and programming, among a variety of others.

Just as automation is important in its direct applications for institutions of higher education, it plays a critical role for edtech companies attempting to connect with these providers of post-secondary education. Agile helps edtech companies automate the management and use of critical third-party data like contact information, driving effective outreach. To learn more about how Agile can assist your company in automating and improving key steps in the marketing process, get in touch with us today.