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Orion StavreOrion Stavre, Associate Director of Marketing Technology and Measurement at WPI, is one of the 12 presenters of the 2020 Higher Ed Analytics Conference.

In this 4-question interview, Orion tells us about higher ed analytics in 2020, a success story, a data analysis technique and what higher ed leaders really need to understand about analytics.

1) What’s next in 2020 for higher ed analytics?

Proving Value and ROI is becoming increasingly more important in the higher ed space, and things like MMM (marketing mix modeling) or MTA (multi-touch attribution) which have been common practice in other industries, are starting to be used in higher ed.

Having a clear view of customer journey through data systems is the most crucial way to clearly evaluate your marketing and sales activities/channels and understand what is working.

I think the biggest opportunity for analytics and measurement for 2020 will continue to remain data integration across the marketing and sales funnels, in order to be able to achieve a clearer view of the “customer” journey. At WPI, we will continue to break silos between various recruitment, fundraising and marketing business units. This will allow for more complete analytics and measurement across the “customer” experience enabled by better data and operational integration.

2020 Higher Ed Analytics Conference

2) Tell us about your biggest analytics success story!

The biggest win at my school has been the implementation of self-serve data dashboards.

Being in a STEM-focused University, not only the Faculty, but also the administration is very data driven. As I came on board and we started becoming more sophisticated on how we looked at our data, our team was inundated daily by requests for data and information. Additionally, we created a new website where the content is managed in a decentralized way. This allowed departments to make independent decisions on what content to use on their websites. But they all needed intelligence on how this content and their sites were performing. We were spending a large part of our time setting up to capture data, build reports, share and educate the team on how to consume the reports and then continually updating these reports.

With the introduction of Google Data Studio that all changed. We created data tracking across the website that could allow us to track all interactions across the website and then be able from the data to identify where the interaction happen. This way we were able to create a uniquely robust database of interactions and the used filters on data studio to build self-serve dashboards for each department. After a few training sessions most departments were able to understand and use their dashboard, and we were mostly focused on more specific ad hoc analyses, rather than just providing data.

3) What’s the data analysis technique (or trick) you’ve found the most helpful?

Always tracking the data at the purest form, and then aggregate as needed for reporting.

I know it sounds simple, but most presentations and trainings that digital analysts make suggest that the tracking is set up in a filtered aggregated form. I have found it very helpful to track data that mirrors elements of the site in a granular form, which allows for very robust tracking without the heavy (time consuming) management. On the reporting side, as long as you have a good basis on the tracked elements, it is still easy to aggregate the data and compile user friendly dashboards.

4) What are the top 3 points higher ed leaders should “get” about analytics?

  1. Define clear goals. I think this is the most important part that a senior leader can play in promoting measurement and analytics within an institution. More so than private entities, Higher Ed is a decentralized environment, where the focus and the goals of the institution are blurred from senior leader to the next. Promoting clearly defined goals, would help focus the institution and identify the appropriate metrics of success.
  2. Incorporate data in all positions and decisions. If the leadership themselves uses data to make the case for their decisions and require data to justify any proposals from other leaders within the organization, this will promote a data-driven culture across all levels.
  3. Support building data and analytics capabilities at the enterprise level. Data is more meaningful when it is integrated across the organization and it’s used by all levels of decision makers to make decisions, but unfortunately most lack technical skills to access these data. Implementing enterprise level tools that allow data to be used freely would be important to supporting a data-driven culture.

A conference focusing on higher ed analytics?

The 2020 Higher Ed Analytics Conference (#HEA20) is a must-attend event for higher ed marketing professionals and teams looking for inspiration, ideas and best practices to step up their analytics and measurement game in 2020

Read below what your higher ed colleagues who attended the past editions of the Higher Ed Analytics Conference said about their experience.

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