Complete Market Research Guide for Education Apps

Most people who download a learning app mean it. They want to speak a language before a trip, pass an exam, learn to code or finally understand statistics. Many of them stop within weeks. Teams building education apps know this, and they often respond by adding features: another streak reward, another notification, another course. Some of these changes help. Many are decided without knowing where learners actually give up, or why.

In this category, the strongest competitor is often not another app. It is the learner's own tendency to stop: the evening they are too tired, the lesson that suddenly feels too hard, the moment the paywall appears before the app has proved its worth. Learners describe these moments in reviews with surprising honesty, and the same reviews explain what kept the ones who stayed.

This guide shows how a team behind a language, exam preparation, coding, tutoring or adult learning app can turn that feedback into real market research about its own app, its competitors and the market it serves.

Key Research Questions

Research starts with the questions it has to answer. For an education app, they fall into three groups: questions about your own app and learners, questions about the alternatives learners choose, and questions about how learning needs in your category are changing.

Your App

The first questions follow the learner. Why did they start, and what did they hope to achieve? At which stage do they give up: during onboarding, after the first few lessons, when the material gets harder, when a streak breaks or when the trial ends? Which parts of the app do learners mention when they explain a five-star review, and which when they explain a one-star review?

The second set is about perceived progress. Do learners feel they are getting better, and how do they describe that? A learner who feels stuck rarely says so in those words. They write that the lessons are repetitive, that the exercises do not match what they need, or that they cannot use what they learned. These comments are among the most valuable in the category.

Your Competitors

Your competitors include other apps, but also the other ways people learn the same thing: a private tutor, a video course, a textbook, a YouTube channel or a class at a local school. What do learners praise in those alternatives that yours never mention? What do they complain about that you already do well? Reviews of competing apps and courses are as public as yours, and learners often compare several options in the same review.

The Education App Market

The third group is about demand. Which subjects and skills are learners asking for that current apps do not cover well? Are learners moving from broad apps to specialized ones, from self-study to tutor-supported learning, or the other way around? How do they feel about subscriptions, and when does paying feel worth it to them? These questions are hard to answer from downloads and revenue alone, because those show what learners did, while their reasons sit in what they write.

Sources of Evidence

Evidence about an education app comes from several places, and none of them has to come first. You can analyze reviews without running a survey, and you can study competitors before you have interviewed a single learner. The strongest research combines what your own learners tell you, what learners of every app and course in your category write in public, and what you learn by asking.

Your Own Learner Feedback

Support tickets, in-app feedback, answers to onboarding and cancellation surveys and messages from learners are the most direct feedback an app has. Cancellation answers are especially useful, because they are written at the moment a learner decides to stop. Collected in one spreadsheet with columns for the date, the course or language, the learner's level, the plan and the platform, they become the start of a customer feedback analysis practice.

App and Course Reviews

App Store and Google Play reviews are the main public source for any learning app, and they cover your app and every competitor in the same detail. Reviews of online courses on Udemy show how learners judge structured courses on similar subjects, which is useful whether you compete with courses or build them. Reddit communities and comments under YouTube lessons add longer discussions: learners comparing methods, asking how others stayed motivated and describing what finally worked for them.

Surveys and Interviews

Traditional methods still have a place. A short survey after the first week can ask what the learner hoped for and whether the app is meeting it. A conversation with a long-term learner, or with someone who stopped, shows what made the difference. Teachers and tutors who recommend apps to their students are another source, because they see where learners struggle. Notes from these conversations are qualitative research, and they need the same structured analysis as reviews to become more than a set of impressions.

Researching Education Apps with Kimola

Kimola is an AI platform that turns customer feedback into enterprise-grade market research. For an education app, that means taking reviews of your app and of the apps and courses you compete with, together with your own support tickets and survey answers, and turning them into a structured study of why learners start, where they stop and what keeps them going. The steps below follow the order a researcher would work in, and you can start with a free account, without a credit card.

Building the Dataset

After signing up, go to the Create your report area on the Home screen and paste the link to your app's page on the App Store or Google Play, or search for the app by name. With the Add Multiple option you can paste several links, one per line, and Kimola collects the reviews from all of them into a single dataset. A practical first report includes your app on both stores and three or four apps learners compare you with. The support article on creating a report by adding links walks through each screen.

For Udemy courses, Reddit threads and YouTube comments, Kimola's browser extension, Airset Generator, collects the feedback from a page and sends it to your account as an Airset, which you can turn into a report. Your own feedback can be uploaded as an .xls, .xlsx, .csv or .tsv file. If the file has columns such as course, level, plan, platform or date, Kimola reads them, and you can filter and compare the results by those values.

By default, Kimola finds the themes in the data itself. If you prefer a classifier built for this kind of feedback, the Advanced option lets you choose one of Kimola's pretrained models, such as the Mobile App Feedback Classifier for app reviews or the Online Course Feedback Classifier for course reviews.

Choosing Dimensions

Dimensions are the research questions Kimola asks of every piece of feedback. You choose them when you create the report or add them later, and the guide to Dimensions explains each one. For an education app, six are especially useful, and two of them belong at the center of the research.

Experience Stages places each comment at a moment in the learner's journey: onboarding, the first lessons, building a habit, reaching harder material, the end of a trial and long-term use. Because learners often say exactly when things went wrong, this Dimension turns a pile of reviews into a map of where learners stop. Underlying Causes then asks why. A drop after the first week may come from lessons that feel too easy, from a placement that put the learner at the wrong level, or from reminders that turned into pressure. Together, these two Dimensions show where and why learners give up, which is the question most education apps need answered first.

Motivations asks why learners started, such as travel, work, an exam or personal interest, and the answer changes what they expect from the app. Pain Points asks what goes wrong, which in this category often covers repetitive exercises, content that does not match the learner's goal, bugs that break streaks and paywalls that arrive too early. Personas groups learners by who they are, which separates a student preparing for an exam from an adult learning for pleasure. Substitutions shows what learners compare the app with or switched from: a private tutor, a video course, a book or another app.

Reading the Report

The Overview shows the main themes in the feedback and how sentiment is distributed. Kimola finds those themes in the data itself instead of sorting comments into a fixed list of categories, so a review about the app can be tagged with something as specific as speech recognition that rejects correct answers or grammar explanations that appear only after a mistake.

Each review can mention several themes, and each theme gets its own sentiment. A learner who loves the short lessons but feels they are not learning to hold a conversation contributes a positive mention of lesson format and a negative mention of practical progress. A single star rating would hide that the experience and the learning itself are being judged separately.

The Performance screen ranks themes with a Satisfaction Score and a Dissatisfaction Score. These scores account for how many reviews mention a theme as well as the percentage, so a theme backed by five reviews does not outrank one backed by fifty. This protects against the most common mistake in small-scale research, which is changing the product because of a handful of strong opinions.

Signals

Signals are findings that have passed a statistical test. Kimola crosses every theme and Dimension with the columns in your dataset, such as app, store, star rating or date, and checks whether a topic is discussed more often or more negatively in one group than in the others (Differences) or more often recently than before (Trends). Only significant results become Signals, and they are ranked so the most important ones come first. The explanation of how Signals are tested covers the method in more detail.

For an education app, the date column is especially revealing. A Trends Signal might show that complaints about streak rules grew after a change to the reward system, or that comments about content difficulty rose after a curriculum update. In a dataset that includes the course or level, a Difference can show that frustration is concentrated in one course or at one level. Signals need enough feedback and at least some selected Dimensions. When the data does not contain a pattern strong enough to report, the report shows none, which is an honest result.

Compare

Compare puts segments of a report side by side: different apps, different stores, or one-star and five-star reviews. Up to five can be compared at once, without using extra queries. In a report built with Add Multiple, the most valuable use is placing your app next to the apps learners compare you with and seeing the volume of feedback, the sentiment, the themes you share and the themes that appear for only one app. If learners of a competitor keep praising how clearly it shows their progress and yours never mention progress at all, that is a decision waiting to be made.

Action Plans

Action Plans turn the findings into steps. You start by choosing or creating a Profile that describes your app, what it teaches and who it serves, then select a perspective: Our own offering, A rival or Our market. These match the three groups of questions at the beginning of this guide. A sensible first plan uses Our own offering with the Product Development goal, which focuses on content and features. Once your report includes competing apps, a plan with the Competitive Strategy goal focuses on how to position your app against them, and a plan with the Customer Experience goal focuses on onboarding, motivation and support.

Kimola builds hypotheses from the report, tests each one against the feedback and drops the actions the evidence does not support. Each remaining action comes with a confidence level and explains why it matters, who it is for, when and where to act, the risk involved and how to see that it worked, along with the evidence behind it. A plan contains up to 12 actions. Plans work best when the report already has Signals, as the support article on how actions are built explains.

From Findings to Decisions

Research is only useful if it changes a decision. For an education app the decisions are concrete, and each one connects to a specific part of the report.

Curriculum and Content

Content is the product. When Pain Points shows that complaints concentrate on repetitive exercises or on a gap between beginner and intermediate material, the curriculum needs attention before any new feature. Unmet Needs, if you add it, shows which topics learners are asking for, and Substitutions shows where they go to find them.

Motivation and Habits

Streaks, notifications and rewards can help learners return, and they can also become a source of pressure. Experience Stages shows at which point learners start describing these mechanics negatively, and Underlying Causes shows whether the problem is the mechanic itself or a lesson that has become too hard. Personas shows whether the same mechanic motivates one group and frustrates another.

Subscription Model

Subscription complaints usually have a specific cause. When reviews concentrate on the paywall, the issue may be when it appears. When they concentrate on value, learners may not have reached the part of the app that feels worth paying for. Comparing what learners say about free and paid use, and what they say about competitors' plans, shows which part of the model needs to change.

Learning Outcomes

Learners judge an app by whether they feel they are learning. Comments about using a language on a trip, passing an exam or writing a first program are the clearest evidence of perceived progress, and their absence is evidence too. Motivations and Personas show whether learners with different goals feel the app serves them, which matters more than any single feature.

Learner Retention

Learners who stop often explain why, in reviews and in cancellation answers. Comparing your own cancellation reasons with public reviews from dissatisfied learners shows which reasons repeat. When the same Underlying Cause appears in both at the same Experience Stage, it is a strong candidate for a real reason learners leave, and the right place to start.

Ongoing Research

A single report gives you a snapshot, and an app changes with every release and every new course. Repeating the research after curriculum changes, new reward systems or pricing changes shows whether the change moved the themes it was meant to move. For apps tied to the academic year or exam dates, repeating it around those periods shows how needs shift through the year.

On paid plans, Feeds keep the research running continuously. A Feed collects public mentions from social media, news sites, blogs, forums, YouTube and review sites, based on the keywords and links you define. Alerts email your team when something important happens, and Mailings send a regular summary. Over time, Trends Signals show which topics are rising and which are fading.

Education Publishers and Platforms

Education publishers and platforms face the same questions across many courses, subjects and markets, with one more added: why does the same approach work in one course and not in another? On the Enterprise plan, each source of feedback, such as an app, a course catalog, a support channel or a learner survey, can become a Space, a continuously growing source of feedback classified with the same Funnel, which is a shared set of custom models and Dimensions. Because every source is analyzed the same way, results stay comparable over time and between products. Spaces also calculate an NPS from what learners write, on a scale from -100 to 100. It is derived from the positive and negative share of written feedback, so it is not the same as a Net Promoter Score from a 0 to 10 survey, and NPS targets can be set for each area.

When a finding needs action, Tasks assign it to the right content or product team with the underlying feedback attached as evidence, and Tasks can be sent to Jira. After a Task is closed, Kimola measures feedback on the same topic again two and four weeks later, so a change to a course can be checked against what learners say afterwards. Executive summary screens give leadership a single view of what learners are saying across the organization. Enterprise accounts are set up together with a dedicated Account Manager, and you can request a demo to discuss your setup.

Frequently Asked Questions

A few practical questions come up when an education team starts researching with customer feedback for the first time.

Should app reviews and course reviews be analyzed together?

They can be, as long as the source is kept as a column. One report then shows whether learners judge apps and courses on the same things, and Compare shows where they differ.

Can reviews tell us whether learners actually learn?

Reviews show how learners describe their own progress, which is evidence about perception and satisfaction. They complement, and do not replace, the learning data and assessments inside your app.

How many reviews do I need before the findings mean anything?

There is no fixed threshold, and the ranking on the Performance screen is designed to protect you from small samples by weighing how many reviews support each theme. Adding a few competing apps to the same report is the easiest way to reach a dataset large enough for Signals.

Getting Started

Your learners, and the learners of every app and course in your category, have already written down much of what you need to know about where learning breaks and what keeps it going. Create a free Kimola account, add your app and a few competitors to a single report, and see at which stage learners talk about giving up. The market research guides for kid apps and productivity apps apply the same approach to neighboring categories, and the market research guide for small businesses covers the method for any industry.