About the Episode
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About the Episode:
Jaime Hunt welcomes back data strategist and higher ed consultant Joshua Dodson for a candid and practical discussion on data analytics in higher education. From redefining what makes data “good” to debunking common misinterpretations in marketing reports, this episode is a must-listen for anyone looking to better leverage data for enrollment and institutional strategy. The duo also explores the democratizing power of AI in data analysis, offering actionable tips on how even resource-constrained teams can get smarter with their data starting today.
Key Takeaways
- Good data isn’t perfect — it’s consistent and actionable. Start with what you can measure reliably and tie it directly to institutional outcomes like enrollment or retention.
- Correlation is not causation. Avoid the common pitfall of assuming your marketing activity alone drove results without considering outside variables.
- Build stronger bridges between marketing and admissions. Data silos undermine your ability to act nimbly—open communication and shared language is key.
- AI tools can radically simplify data analysis. Platforms like ChatGPT and Copilot can turn qualitative surveys and spreadsheets into strategic insights—no data science degree required.
- Invest in data upskilling and strategy. Tools like Google Analytics, Looker Studio, and training platforms like Dodson Academy can empower your team to turn information into informed action.
- Stop creating reports for reporting’s sake. Instead, focus on dashboards and visualizations that help you connect data to decisions.
- Marketing mix modeling is no longer just for the Fortune 500. Tools like Robyn, Meridian, and PyMC make it accessible for higher ed marketers.
- In the next 3-5 years, personalization powered by AI will be the norm. If your website isn’t adapting in real time, you’ll be left behind.
Episode Summary
What is “good data” in higher education marketing?
Joshua Dodson makes it clear: good data isn’t perfect—it’s consistent and connected to outcomes. In higher ed, this means tying marketing efforts directly to enrollments, donations, or event participation. Good data allows marketers to take strategic action with confidence, even when it's not flawless.
How can data help institutions make tough decisions?
Jaime and Joshua discuss how institutions can use data not just to justify wins but to make tough calls—like identifying underperforming programs that might need to sunset. When data is connected to ROI, it gives marketing and admissions leaders credibility in resource conversations with boards and CFOs.
What’s the most common mistake institutions make with data?
Assuming correlation equals causation. Just because applications increased after a campaign launch doesn’t mean the campaign caused it. Joshua illustrates this with the classic “ice cream and shark attacks” analogy: both increase in summer, but one doesn’t cause the other. Marketers must account for environmental variables and blind spots.
How can marketing and admissions teams collaborate more effectively around data?
Siloed data is a widespread issue in higher ed. Joshua emphasizes the need for shared language and intentional data requests. Instead of asking for a generic report, frame the ask in a way admissions can fulfill using their tools (like Slate). Building trust and aligning around shared goals is key.
What should smaller teams or resource-constrained institutions do to get started with data?
Start small. Get your basics in place: GA4, Google Tag Manager, and Microsoft Clarity. Then lean into AI to help you analyze and interpret results. Tools like ChatGPT can summarize complex reports or extract insights from unstructured data like open-ended survey responses—saving time and expanding capacity.
What is marketing mix modeling, and how can it help higher ed marketers?
Joshua introduces the power of marketing mix modeling (MMM), a method long used by big brands to determine which marketing channels truly drive results. Thanks to open-source tools like Robyn (Meta), Meridian (Google), and PyMC (Python), MMM is now accessible to higher ed teams, especially when paired with AI for interpretation and execution.
What should we stop doing with data?
Stop creating vanity reports just to report numbers. Impressions and followers are fine, but only if they’re contextualized within broader goals. Joshua encourages marketers to treat data like a GPS—not a rearview mirror. Use it to guide decisions, not just prove activity.
What tools and platforms does Joshua recommend for leveling up in data?
- Google Analytics 4 (GA4) and Google Tag Manager: For foundational website tracking
- Looker Studio: To create dashboards combining marketing and admissions data
- Microsoft Clarity: For heat maps and user behavior analysis
- ChatGPT, Claude, Copilot: To analyze, summarize, and strategize with raw data
- Cursor: A powerful AI assistant that integrates with your computer for file-based tasks
- Dodson Academy: Joshua’s own education platform that helps higher ed teams build skills in marketing mix modeling, analytics, and more
What’s coming next for data in higher ed marketing?
The future is personalized, predictive, and powered by AI. Joshua predicts that in 3–5 years, higher ed websites will need to function like virtual admissions counselors—adapting content in real time to the individual user. Institutions that embrace AI and unify enrollment and marketing will have a clear edge in navigating what's next.
Connect With Our Host:
Jaime Hunt
https://twitter.com/JaimeHuntIMC
About The Enrollify Podcast Network:
Confessions of a Higher Ed CMO is a part of the Enrollify Podcast Network. If you like this podcast, chances are you’ll like other Enrollify shows too!
Some of our favorites include Talking Tactics and Higher Ed Pulse.
Enrollify is produced by Element451 — the next-generation AI student engagement platform helping institutions create meaningful and personalized interactions with students. Learn more at element451.com.
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