Over the last few years, social listening software has become increasingly popular for higher ed martech stacks. But something we hear often from our clients is that marketing teams struggle to get the full value from expensive software. Lack of time, training, and ability to pull readily usable data are common struggles.
Social listening may seem simple, especially if you’re getting a pitch from a software company. Just enter your search terms, and ta-da—social data. Unfortunately, that’s not how it works. Each software product collects data differently, and the data that’s returned may come with nuances that aren’t obvious to the casual user. Since social listening is all that we do, I’m sharing what we’ve learned working with millions of social mentions from about over a hundred institutions. Hopefully it will help you make an informed decision about how to approach social listening for your campus.
A savvy analyst can draw conclusions even when the data they’re presented with is limited in scope or volume. While these conclusions come with limitation disclaimers, they still offer a valuable point of consideration when you’re developing your campus strategy and identifying which problems are most in need of solutions. Research Manager Amber Sandall and Client Success Manager Beth Miller share what our analysts look for in social data when the answer to their research question isn’t always obvious at first glance as well as some specific ways that social data can inform campus decision making.
In the first part of this series, I shared our planning and query writing process—how our teams come together to plan each client project and the research that our analysts do in the beginning stage of each project. It was a lot! Now that you made it through part one, you'll sail through part two. Let's go!
Gear up for some Campus Sonar behind-the-scenes! I’m covering how the Research team at Campus Sonar conducts social listening research, start to finish, to pull back the curtain on what we do from project kickoff to presentation of findings and insights to the client.
What do you think of when you hear “artificial intelligence” or AI?