Analytics is a term that refers to mathematical techniques’ tools, Machine Learning and predictive analysis to understand a great amount of data to find patterns.In this way, Insight Analytics is the ability to use all the data available in your EI’ to find ideas, opportunities and make decisions based on facts and analysis.
Insight Analytics is being enhanced by the combination of generative artificial intelligence, predictive analytics, and data unification. Tools like Adobe LLM Optimizer help brands monitor engagement in AI interfaces and adapt content in real time, optimizing campaigns for each stage of the student journey.
In addition, the adoption of Data Clean Rooms and compliance frameworks like LGPD/GDPR ensure advanced analytics with respect for privacy. These advances strengthen data-driven decision-making, delivering more effective and secure campaigns.
Next, we’re going to talk about the main strategies that can be used to have an Insight Analytics. Check it out!
1. CX Analytics
The first data gathering process in Educational Marketing is Customer Experience (CX) imput. The EI needs to understand how people see its brand and how they relate to it.
This can be seen between the EI and the persona, in the way people interact in the EI’s social media, in questions sent by form and even compliments and complaints can generate important information about your brand positioning.
An EI should consider all this data, once it can be decisive to attract or to back out new enrollments.
2. Business’s KPIs tracking
One of the main tendencies in Marketing is the KPIs tracking.
Before any operation starts, the EI determines the targets and the guides to identify if the decisions that are being made are leading to the previously chosen paths.
These guides don’t show only the success of a certain choice. They also point to events that reflect the students’ buying journey.
When the team does the data collection, they notice that they reached the enrollment goal, but the conversion rate was lower than the expected, and, as a consequence, the investment per student was higher than the projected.
What that means is: there are some failures in the students’ buying journey, mainly in the conversion stages (tests and enrollments), once people are reaching your EI but they are not finishing the purchase.
3. Marketing Automation
Marketing Automation, by its own, can generate a great amount of information that can be used by your EI at any moment. For example, with e-mail marketing you can have data about who opened the email, how many people clicked on it, reading average time, unsubscription, and so on.
If we connect this information with the sent content, we can have a more precise overview about the conversion strategies and which ones are ignored or devalued.
Add this to all marketing automation offered, as social media control, tracking of website performance, chatbots, online campaigns management...
The idea of Insight Analytics is to organize all of this information that comes for different sources and use the pattern to identify opportunities in Marketing Automation all the data is already a little bit filtered for the team to work on it.
Automation with generative AI and hyper-personalization allows the system to learn from individual behavior, such as email reading patterns, clicks, and social interactions, and deliver personalized content in real time, significantly increasing conversion rates.
Studies show that this personalization increases engagement and conversion by up to 30%. In this way, automated strategies stop being just data collectors and become orchestrators of individual experiences that captivate the student.
4. Enrollment Withdrawal
The connection between the buyer’s journey and the withdrawal stage (when talking about EI, it’s enrollment withdrawal) has always been important.
When you see a lead getting to the end of their buyer’s journey without purchasing, your team has to turn on the red light.
If someone is really engaged with the enrollment process, but something happens and changes their mind, it’s essential to understand what happened. There can be many elements that can influence a student’s final decision and each one of them needs to be processed by your company.
Enrollment withdrawal data are crucial to understand what has been decisive in the process. Maybe people have questions at some stage, maybe the website was out during the registration, maybe the enrollment process spends more time on the internet and there’s more withdrawal by mobile access…
Each one of this information will direct your team’s action.
5. Predictive analysis
Predictive Analysis is the name for a statistical technique that contains data gathering and machine learning to analyse past and present context and predictions of some scenarios.
It uses the students’ buying journey background and present elements that can determine a new enrollment. Then, the predictive analysis relates the information and identifies the main problems and opportunities that can influence positively or negatively the students’ buying journey.
This tool is also recommend to help on students retention, once a EI’s buying journey is a cyclical process and your company has to acquire the students every semester.
Caption: The image highlights the use of dashboards and interactive graphics as an essential tool for mapping consumer behavior and guiding actions during the purchasing journey.
6. Buyer’s journey dynamic mapping
Another Insight Analytics strategy is dynamic mapping. Mkt4edu uses one of the models by Hans Rosling.
Dynamic mapping consists in a detailed tracking of the buyer’s journey of every student that is already enrolled in your EI. Through this tool it’s possible to identify movements, time between the first website access and the final enrollment and even the Marketing actions impact.
This is one of the best Insight Analytics tools nowadays and uses lots of the resources we mentioned in this blog post.
Integrating Insight Analytics with immersive technologies such as AR/VR and omnichannel strategies becomes a differentiator. Interactive virtual tours, for example, increase lead engagement even before enrollment.
In addition, omnichannel models connect data from websites, mobile, chatbots and social networks, ensuring fluid and consistent communication throughout the future student's journey. This mix of innovation and integrated experience provides the Educational Institution with exclusivity in the market and greater effectiveness in attracting and retaining students.
Summary: Insight Analytics combines data, AI, and automation to improve educational marketing. Using CX analysis, KPIs, enrollment abandonment, and student journey tracking, institutions can predict dropouts, personalize strategies, and boost enrollment. Tools like AR/VR and omnichannel enhance engagement and retention.
If you want to learn more about the dynamic mapping to understand better the students capture, we recommend the reading of our blog post about Technology and the students’ buying journey: understand this connection!
How to apply Insight Analytics to transform student enrollment
What is Insight Analytics and how does it support educational marketing?
Insight Analytics is the ability to turn large volumes of data into strategic decisions, combining artificial intelligence, predictive analytics, and unified data. It helps institutions identify behavioral patterns, anticipate issues, and optimize campaigns in real time based on factual evidence.
How does CX Analytics support student enrollment?
CX Analytics maps how students perceive the institution through contact points like social media, support channels, and forms. These data uncover strengths and weaknesses in the consumer journey, crucial for attracting new enrollments and improving the user experience.
Why is KPI monitoring essential for campaign success?
KPIs help evaluate each stage of the student journey, showing whether conversion rates and cost per enrollment meet the goals. They also reveal bottlenecks, like issues in the registration process, guiding quick strategic adjustments.
What kind of data comes from marketing automation strategies?
Automation provides insights into email, social media, chatbot, and website interactions. With generative AI and real-time personalization, content can be tailored to each student's behavior, increasing engagement and conversion by up to 30%.
How should enrollment abandonment data be interpreted?
Abandonment reflects critical points of failure in the enrollment journey. Analyzing this data helps identify issues like slow pages, unanswered questions, or mobile access problems, enabling targeted solutions to reduce dropout rates.
What makes predictive analytics stand out?
Predictive analytics forecasts behaviors based on past and current data, anticipating dropout risks or pain points. It's also a retention tool that identifies at-risk students, enabling proactive and customized interventions.
What is the role of dynamic journey mapping?
Dynamic mapping tracks the student's entire buying journey, from the first website visit to enrollment. It enables optimization of conversion time and highlights the most influential points in the institution’s marketing strategy.
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