AI in Education: Enhancing Student Retention and Experience

A few years ago, it might not have been possible to imagine that the future of educational marketing would be linked to machines. But nowadays, with technological advances, the use of Artificial Intelligence is not only a reality in the educational scenario, but is also essential for an effective student retention and a good customer experience.

In times of great evasion, with countless students dropping out of the course halfway through, AI has become the secret for educational institutions to reverse the situation, improve marketing strategies and improve the consumer experience.

But, in practice, how is this done? That's what we're going to talk about in today's post! Continue with us and discover how AI can help retain your educational institution.

How AI strengthens student retention in practice

Artificial intelligence in educational marketing makes it possible to automate processes, analyze data at scale and anticipate dropout behavior. By identifying disengaged students, assigning risk scores and guiding new actions, AI helps build more assertive retention strategies. It also personalizes communication, supports copywriting, powers 24/7 chatbots and connects all this to key student experience metrics such as NPS, CES and CSAT, while respecting data processing rules defined by the LGPD and related guidelines.

• • Anticipate dropout risk with predictive analytics and machine learning models.

  • Personalize content and communication based on student behavior.

  • Use chatbots to deliver agile and always-on support.

  • Track NPS, CES and CSAT to understand satisfaction, effort and overall perception.

  • Handle student data responsibly, in line with LGPD requirements.

What you will see in today’s content

• How artificial intelligence supports student retention in the educational context.

• Use of predictive analytics and machine learning models to anticipate dropout risk.

• Personalization of communication and content based on student behavior.

• The role of chatbots in the student journey and 24/7 support.

• The importance of monitoring the student experience throughout the entire journey.

• How the Net Promoter Score (NPS) works to assess loyalty.

• How the Customer Effort Score (CES) measures the effort students make to solve issues.

• How the Customer Satisfaction Score (CSAT) evaluates satisfaction with services and courses.

• Key LGPD considerations and responsible student data handling in AI retention projects.

Let 's go reading!

How can AI help with retention?

If you are a regular reader of our blog, you must have read about Artificial Intelligence here! The fact is that the future has arrived for educational institutions and, if you haven't implemented it at your university yet, it's time to rethink the subject.

In short, artificial intelligence allows processes previously done by humans to be performed by machines, optimizing their time and automating the process. In a more practical way, the machine will execute tasks and, according to the received data, improve its tactics.

In the educational scenario, as we said earlier, this tool is essential! When it comes to student retention, AI can be decisive for your students' retention, and we'll show you how. Come on?

Anticipate scenarios and enable the construction of a more assertive strategy! 

Through predictive analysis of data from students who are already enrolled, it is possible to identify students who are more dispersed with the contents of their institution. That way, you can anticipate and create strategic content that will attract and reach these students again.

In many institutions, predictive analytics has evolved beyond manual spreadsheets. With machine learning models for student retention, it is possible to assign an individual “risk score” to each student by combining academic, financial and digital engagement data, helping teams focus on those who need immediate support.

These machine learning models for student retention can trigger automated alerts for success teams, launch personalized outreach flows and even optimize media campaigns only for high-risk profiles, making AI a truly strategic tool for retention.

Imagine the following situation: your institution has a student who does not open your emails and, for a long time, does not visit any of your platforms, not even download your content. This student is increasingly distant from his university and your communication with him needs to be reestablished.

With the intelligent system, it is possible to identify the student's behavior patterns and analyze their actions. At this point, by anticipating the scenario, your institution is able to identify such a situation in time and build a new strategy to prevent that student from dropping out. 

With AI, you personalize the experience and build a relationship with the learner!

Generating a connection with the student is not always an easy task, the student needs to identify with your institution and communicate with you! But to develop a solid relationship, the key is personalized communication. 

With AI, it is possible to automate responses according to user behavior. In this way, your university makes the student feel understood by your institution. 

Here, Copy professionals come into play! With the information discovered by AI, the creative sector is oriented to produce more assertive content, according to the pain and needs of the student.

Read too:

• How does CRM connects with the sales funnel steps
• What is the connection between CRM and the purchase funnel stages
• Relationship ruler: 5 best practices for relationships with students

Chatbots: your university is always available!

The student's journey does not end when he enrolls, it is necessary to accompany him throughout his trajectory and be present so that he remains in your institution. 

At this point, an agile service is needed to answer the student's possible doubts and show that the University is there to help him in whatever is necessary. 

But the big question is: how to be available 24 hours a day to serve you? There is only one answer: artificial intelligence. 

With a more humanized interaction, the objective of the virtual assistant is to speed up the process and make the first contact with the student. With the chatbot, the machines carry out customer service and solve their doubts in a practical way. But if necessary, the virtual assistant directs the student to one of the university's attendants.

With good service, your institution can offer a personalized and faster experience to the student, increasing the level of satisfaction and showing that this is the right place for him to continue his graduation. 

Image: Digital brain symbolizing how artificial intelligence supports educational marketing and student retention strategies.

How has your students' experience been?

Now that you know how AI can impact your retention, it's time to understand your student experience a little more. After all, how to measure the level of customer satisfaction? That's what we're going to talk about in this thread! 

To understand the consumer journey and build more assertive strategies, it is necessary to know how the user experience with your institution has been, from the registration process to the post-sales. 

By monitoring specific metrics and in-depth understanding of the collected data, your institution has the opportunity to improve its services. Remember that customer satisfaction is synonymous with achieving your main objective and having a successful strategy! 

At the same time, using AI for retention requires strong privacy safeguards. In Brazil, the Brazilian General Data Protection Law (LGPD) sets clear rules for processing students’ academic, contact and behavioral data, including legal basis, transparency and security throughout the entire data lifecycle.

Before launching any AI-based retention project, institutions should map what data is collected, how long it will be stored and how it will be anonymized, following the Brazilian General Data Protection Law (LGPD) and ANPD guidance to ensure responsible use of students’ personal data.

To help you know if you have achieved the expected results, below, we separate the main metrics that you need to take into account when measuring your customer satisfaction.

Net Promoter Score (NPS)

Net Promoter Score (NPS) is a loyalty metric that uses a single question to measure how likely students are to recommend your institution to a friend or colleague. On a 0–10 scale, scores of 9–10 are promoters, 7–8 are passives, and 0–6 are detractors.

To calculate Net Promoter Score (NPS), you subtract the percentage of detractors from the percentage of promoters, obtaining a value between -100 and +100. In higher education, this index helps you understand if the experience is truly creating advocates or silently increasing dropout risk. 

By combining Net Promoter Score (NPS) with AI, institutions can automatically analyze open-text feedback, detect recurring themes, and correlate survey answers with usage data, predicting which student profiles are more likely to churn and where retention efforts should be prioritized.

If your University has a low recommendation rate from students, there must be something wrong with your strategies, and you need to think of new tactics to make students interested in staying at your institution again. 

The calculation is simple, the greater the customer's satisfaction, the greater the chances of him staying at your college and recommending it to other students.

Customer Effort Score (CES)

Customer Effort Score (CES) measures how much effort a student needs to resolve an issue, get support, or complete a task with your institution. Typically, CES is based on a single statement — such as “The institution made it easy for me to solve my problem” — rated on a 1–5 or 1–7 agreement scale.

Higher Customer Effort Score (CES) values indicate lower perceived effort. Streamlined processes, intuitive self-service and quick responses tend to increase CES, while bureaucracy and fragmented channels decrease the score and raise dissatisfaction and dropout risk.

When Customer Effort Score (CES) is combined with AI-analyzed behavioral data, institutions can pinpoint friction points in the digital journey, prioritize improvements in critical flows and trigger proactive retention actions before students decide to leave.

Customer Satisfaction Score (CSAT)

In summary, the purpose of the Customer Satisfaction Score (CSAT) is to assess student satisfaction regarding the services provided by their university, from the campus to activities within the classroom and even the course offered. . 

Unlike NPS, which focuses on loyalty, and the CES metric, which focuses on user effort, CSAT captures student feedback about its services. Through this metric, it is possible to identify whether your institution has been doing a good job from the student's point of view. 

Finally, based on the data from these assessments, your marketing team can identify which points to improve and create more assertive retention and capture strategies. With the metrics listed above, you can get to know the student's view of your educational institution. 

After all, what has been the perspective of students regarding your university? Is your educational institution seen as a college that listens to them and solves their problems with ease, or as an institution that is difficult to reach and whose students have difficulty getting in touch? 

With the answers in hand, it's time to rethink your tactics and use artificial intelligence in your favor to streamline processes and optimize the customer experience. And since we are talking about educational marketing strategies, Mkt4Edu is a reference in the matter. 

We are the largest educational marketing agency in Brazil, Mexico and the United States, and also Hubspot's largest partner worldwide. Want to know more about us? Visit our website and find out how we can help change your student enrollment results!

Frequently asked questions about artificial intelligence in student retention

What is artificial intelligence in the context of educational institutions?

In the context of educational institutions, artificial intelligence is the use of machines to perform processes that were previously carried out by humans. This technology executes tasks based on data, automates routines and learns from its own results to improve actions over time. In practice, it means saving time, standardizing processes and making teams more strategic. Instead of spending energy on operational activities, the university relies on systems that analyze information, suggest paths and support more assertive decision-making.

How can artificial intelligence help with student retention?

Artificial intelligence helps with student retention by identifying risk behaviors and supporting more assertive strategies. Based on academic, financial and digital engagement data, AI highlights students who are more disengaged, no longer open emails or stopped accessing platforms and content. From these signals, the institution can act before dropout happens, with specific content, segmented campaigns and targeted relationship actions. In this way, AI becomes a central component of educational marketing strategies focused on keeping students enrolled.

How do predictive analytics and machine learning models help reduce dropout?

Predictive analytics and machine learning models allow the institution to go beyond simple manual spreadsheet filters. They make it possible to assign a risk score to each student, combining academic, financial and engagement data. This score helps prioritize who needs immediate support, trigger automatic alerts to relationship teams and start personalized communication flows. Media campaigns can also be adapted to profiles with a higher probability of dropout, making the use of AI more strategic and strongly focused on preventing students from abandoning their studies.

How does AI make communication with students more personalized?

AI makes communication more personalized by analyzing student behavior and automating responses and interactions based on that data. The technology identifies browsing patterns, email opens and content consumption to understand each student’s moment. With this, it enables messages that truly address their pain points and needs. The insights generated guide copywriting professionals, who start producing more accurate and relevant content. The result is a stronger relationship, in which students feel understood and perceive that the institution speaks directly to their reality.

What is the role of chatbots in the student experience and journey?

Chatbots keep the university always available to students at every stage of their journey. They handle the first service contact, answer frequent questions and speed up support, providing a more humanized and practical interaction. With artificial intelligence, the chatbot guides students towards solving their issues or, when necessary, forwards the contact to a human agent. This ensures fast and continuous service, increasing student satisfaction and reinforcing the perception that the institution is present and ready to help them stay in their program.

Why is it important to measure the student experience along the journey?

Measuring the student experience is essential to understand whether the institution is truly delivering a quality journey, from enrollment to post-sale. By monitoring specific metrics and analyzing collected data, the university identifies friction points, improvement opportunities and aspects that already work well. This view guides adjustments in services, processes and marketing strategies, making retention actions more precise. Ultimately, student satisfaction indicates that the strategy is successful, while dissatisfaction signals an urgent need to rethink tactics and approaches.

What is Net Promoter Score (NPS) and how does it relate to retention?

Net Promoter Score (NPS) is a loyalty metric that measures how likely a student is to recommend the institution to a friend or colleague. Based on a single question using a 0–10 scale, students are classified as promoters, neutrals or detractors. The score is calculated by subtracting the percentage of detractors from the percentage of promoters, resulting in an index from -100 to +100. A low NPS indicates weaknesses in the experience delivered and higher dropout risk. A high NPS shows that the institution generates satisfied students, who are more likely to stay and recommend the college.

What is Customer Effort Score (CES) and what does it reveal about your institution?

Customer Effort Score (CES) measures how much effort a student needs to make to solve a problem, clarify doubts or complete a task with the institution. The survey is usually based on a statement such as “The institution made it easy to solve my problem” on a rating scale. The higher the score, the lower the perceived effort. Simple processes, well-structured self-service and quick responses increase CES. Bureaucracy, queues and disconnected channels lower it. Therefore, CES reveals whether the university is making students’ lives easier or creating obstacles that may push them towards dropout.

What is Customer Satisfaction Score (CSAT) and how does it support retention strategies?

Customer Satisfaction Score (CSAT) evaluates how satisfied students are with the services offered by the university, such as campus, classroom activities and the course itself. Unlike NPS, which focuses on loyalty, and CES, which measures effort, CSAT captures students’ perception of what they receive in their daily interactions. Based on these evaluations, marketing teams and other areas can identify improvement points and adjust services and communication. This makes retention and acquisition strategies more accurate and aligned with how students truly see the institution.

How does LGPD affect the use of artificial intelligence in student retention projects?

LGPD directly affects the use of artificial intelligence in retention projects because it defines rules for processing students’ personal data. Academic, contact and digital behavior information must have a legal basis, transparency and security throughout its life cycle. Before starting any project, it is important to map which data are collected, how long they will be stored and how they will be anonymized. Following the General Data Protection Law and the guidelines issued by the ANPD helps ensure that the institution uses AI responsibly, while protecting students’ privacy.