It’s no secret that many institutions are facing enrollment challenges. It’s also no secret that these challenges are not temporary. Higher education has changed. The institutions who are aggressively re-evaluating their business model and prioritizing innovation above all else have a leg up on their competition.
However, investing in programming changes or an innovative website redesign cannot solve all your problems. As you look at prioritizing initiatives and investments for the upcoming fiscal year, what role does data play?
- Do you have the data you need to make investments that yield the best ROI?
- Do you have the data you need to reach and engage your most ideal prospective students?
- Do you have the data you need to prioritize touch points to convert prospects into enrollments?
If your answers are “no, no and no”, what are you doing about it? Like the higher education sector, there have been so many changes in the data and analytics landscape, making it more difficult to reach prospective students effectively and efficiently.
It’s also become more challenging to forecast enrollment or measure ROI. However, data-driven decision-making has never been more important. As you think about your budget for the next fiscal year or recruitment cycle, here are five strategies and topics to consider:
1. Artificial Intelligence: No surprise here—AI can be extremely beneficial to data and analytics functions and workflows. Simple use cases include automating reports to improve efficiencies or using a chatbot to fact-check or validate data to ensure accuracy. The real fun begins when you can leverage AI to better unlock data patterns and use it to fuel predictive analytics and enrollment forecasting.
To put you at ease, the need for personnel to ensure data quality and security is a must. Think of AI for data and analytics turbo-charging your team for greater efficiencies, greater insights, and greater impact.
2. Zero-Party and First-Party Data: Third-party cookies have been the crux of digital targeting and measurement for over a decade. The reliance on third-party cookies has been decreasing over the last few years and by the end of 2024, Google will have phased out third-party cookies from Chrome completely.
Marketers are now shifting to prioritize zero-party and first-party data to target and personalize their marketing. Zero-party data is information that a user shares voluntarily with an institution, whereas first-party data comes from user browsing activity on your website.
The good news: You own your zero-party and first-party data. It comes from your activities, it’s likely more accurate, and more valuable. The bad news–it takes time to collect. Creating valuable, SEO-focused content will be more important than ever for building up your audience data.
3. Augmented, Edge and Embedded Analytics: There’s a handful of new buzzwords in the analytics field that are worth becoming familiar with:
- Augmented analytics is an approach of analytics that is powered by artificial intelligence and machine learning to allow for more automation in analysis processes and allows a user to interact with data more seamlessly at a contextual level.
- Edge analytics also leverages AI to collect, analyze and create insights from real-time analytics but does it at a non-central point, helping those who need quick insights but have dispersed and decentralized data.
- Embedded analytics are simply the analytics and data visualization capabilities available directly in your software. Data analysis occurs directly within your workflow so there is less reliance on a third-party application for data and insights.
A deep understanding of these areas isn’t necessary, but as you evaluate marketing and analytics tools, partners and resources, it’s important to probe into these areas so you’re ensuring you’re getting the best return on your investment.
4. Data Observability: Data observability is an institution’s comprehensive understanding of the health and performance of its data within its various systems. And today, you’re only as good as your data.
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Data observability is made up of five pillars: freshness, quality, volume, schema and lineage. In summary, it’s how reliable your data is. And the reliance on quality data will become more important to institutions as they invest in AI solutions. AI is only as effective as the inputs and knowledge base it leverages.
5. Data and AI Literacy: Imagine if you or your team knew 25% more about the importance and the possibilities of data and AI. Employees know they need to advance their knowledge and skills in data and AI to stay competitive in today’s job market.
And similarly, employers need employees to be proficient in these areas to be the most effective in their roles. Institutions should prioritize investing in data and AI programs and training to empower their teams and better democratize data. If you take away one idea from this list, this is the one.
Outside of data and analytics, one big trend for 2024 and beyond is the focus ondoing more with less: Greater results, reduced spend; more impact, less resources. Data and analytics are key for working smarter, not harder in the enrollment realm.
