UX Case Study · Research & Iteration

Finding out why users quit a learning app's onboarding — then cutting the flow from five steps to two

Understanding why users drop off during the onboarding of a mobile learning app — then redesigning the flow around the findings, from five steps to two.

Onboarding steps

User interviews

Survey responses

Cited “too many steps”

RoleUX Researcher & Designer

PlatformMobile · Figma, Miro

Duration2026

UX Research · Mobile Learning

The Problem

The mobile learning app experienced a high drop-off rate during onboarding — analytics showed many users abandoning the app before completing profile setup or exploring key features.

Research goal

Understand why users drop off during onboarding, identifying usability issues that cause confusion, frustration, or disengagement among first-time users.

Emotional barriers

Explore users’ expectations when signing up for a learning app and uncover the emotional responses they experience during their first interaction.

The users

University students aged 18–25 who downloaded a learning or productivity app within the last three months.

The aim

Identify opportunities to improve the onboarding experience and increase user engagement and completion rates.

Method

Research Plan

A structured plan defined the problem, research objectives, target users, interview questions, and success metrics before any design work began.

Interviews

Semi-structured 30-minute Zoom interviews — recorded with consent, transcribed, and coded using affinity mapping.

Survey

An online survey distributed via Google Forms to validate the patterns found in the interviews.

Screening

Participants screened for recent, real onboarding experience with learning or productivity apps.

Key questions

What motivates users to download the app? What frustrations occur during onboarding? What would make users complete it?

6 interviews · 42 survey responses

Key Findings

Data from 6 user interviews and 42 survey responses, clustered into themes through affinity mapping in Miro.

Too many steps cause frustration

67% of survey participants selected “too many steps” as a reason for quitting; 4 of 6 interviewees said onboarding felt long. “I just wanted to start learning, not fill out five pages of info.”

Unclear value proposition

58% were unsure what the app offered after signing up. “I didn’t really know what made it different from other apps.”

Too much personal information

61% felt uncomfortable sharing detailed data before exploring the app. “Why do you need my major before I even try the app?”

No progress feedback

5 out of 6 interviewees didn’t know how long onboarding would take — users need progress indicators to reduce uncertainty.

Findings → design moves

The Redesign

Each design move traces directly to a research finding, backed by an established design principle.

Five steps become two

Instead of asking for major, GPA, interests, phone, and password immediately, the new design asks only for email and password — non-essential information is postponed. (Hick’s Law: reducing choices decreases cognitive load.)

Value proposition up front

“Start Learning Smarter Today” — a clear headline with supporting text explaining the benefit, placed at the top of the screen. (Visual hierarchy.)

Progress indicator

“Step 1 of 2” with a progress bar reduces uncertainty and increases perceived control. (Nielsen’s visibility of system status.)

Progressive disclosure

Non-essential data collection is delayed until after account creation — users explore first, share later, building trust.

Before and after: the onboarding redesign

// preview

Closing

Recommendations & Next Steps

The research phase closed with actionable recommendations and a plan to validate them.

Simplify and stage

Merge screens where possible, request only essential information, and allow optional fields later.

Say the value early

A 2–3 screen intro explaining benefits, highlighting unique features through visual storytelling.

Prototype and test again

A simplified onboarding prototype, tested with 5 users, measuring completion-rate improvement.

Want to go deeper?

Get in touch for the full walkthrough, or browse the rest of the work.

Let's Talk All case studies