One of the first phrases I heard as a higher education marketer was the importance of data-driven decisions.
With so much data available these days, I wanted to help the next generation of MarComm leaders better understand what data should be considered and when.
This list was originally shared in a pre-conference workshop Melissa Farmer Richards and I co-presented at AMA last fall.
Several attendees said it was incredibly beneficial to help them avoid being paralyzed by the data, so I wanted to share it with you as well.
Performance Data – Outputs
I consider performance data to be outputs because they are measures of what your team is doing. These pieces of data should be reviewed monthly to understand overall trends that exist. We also try to review this data with leadership once a quarter.
While this data should be reviewed monthly, there may be times you want to look at this data more granularly. Much can be learned looking at how a single social media post or a single email performed. However, I wouldn’t make strategy decisions on just one individual email analysis.
Website analytics – This includes page views, bounce rates, time on site and link clicks. This data can help you to understand what content is important to your audience and when. Understanding which pages are most viewed allows for informed decisions on content and strategy, ensuring alignment with the interests of prospective students and alumni.
Social media metrics – Looking at engagement rates on social media content can help you understand what content performs well. This can also help you hone in on whether certain platforms better for certain types of content, and it can also help you assess which medium works best for which type of content. Finally, metrics in social media can provide insight on when to post and how often to maximize engagement. Because social media is highly audience-specific, it is critical to look analyze the data within your own channels.
Conversion rates – If your institution is enrollment-driven, conversion rates are incredibly important. Each university has different conversions but my guess is some likely conversions include people signing up for a tour, submitting an RFI form, and applying for admission. If you’re in the development space, it could also be signing up for a newsletter, registering for an event, or making a first gift. These conversions are an early sign of engagement, and can provide key context into a longer relationship. When tracking this data, it’s important to recognize that much of it is cyclical, so having historical numbers can put cyclical changes into perspective.
Email open rates – Chances are many of those you are targeting are part of an email marketing campaign. Understanding the email open rates can help you understand key messages and what is relevant to your audience. If your emails are event based, email open rates can also help you garner interest in the event and engagement with your audience. Tracking email open rates over time allows you to refine your messaging, optimize send times, and ultimately improve engagement with your audience.
Other Thoughts
There is one final part of data that I’ll share more insights about in a future post. I hope this data primer is helpful and one that you find valuable.
What other output data should we be looking at each month?
And Carrie On 