Babbel | Growth | Q3 2023
Problem
The onboarding flow was too long and didn’t reflect users’ personal goals, which led to high drop-off rates.
Solution
Redesigned onboarding questions centring them around learner's motivations to highlight product value earlier in the journey.
Outcome
Results of an A/B test have shown a +7% in revenue and a +8% in visit-to-sale.
Role
Product Designer
Timeline
4 weeks
Team
1 Product Designer
1 Senior Product Manager
2 Senior iOS Engineers
2 Senior Android Engineers
Context
When I joined Babbel in Q2 2023, my first task was to evaluate and redesign the onboarding experience. After analyzing the current flow, benchmarking competitors, reviewing research, and wireframing, I presented the first proposal for a revised onboarding journey.
One of the key opportunities I identified was to reframe the onboarding questions to reflect user motivations, helping users connect with the product on a personal level and experience value sooner.
Researching motivations
Using existing research, I identified different types of motivations that drive people to learn with Babbel. Then I grouped the motivations to understand how they could be leveraged in the product experience.
I synthesized the insights and 3 categories emerged as key motivators:
Improving language skills - the smallest building blocks of communication, like speaking or vocabulary
Gaining tangible skills - the things people want to do in real life, like doing groceries or talking to a neighbour
Fulfilling aspirational motivations - deeper emotional drivers tied to identity, like connecting with family or travelling
These motivations build on one another to create a complete picture of why someone wants to learn a language.
Next step: motivation survey
AI-supported analysis
To validate the motivation clusters, we launched an in-app survey to ensure the questions were shown at the most impactful point in the onboarding flow.
I analyzed the results in a CSV format using advanced Google Sheets queries and quantitative techniques.
One task exceeded the limits of what I could do manually. Instead of waiting for analyst support, I explored whether I could bridge the gap with AI. Through a mix of trial-and-error and rapid iteration, I completed the task independently using ChatGPT.
At the time (early 2023), few designers in our org were experimenting with AI. This initiative was one of the first applications of AI-supported workflows in our team, and I was later invited to present it during our internal Design Day.
Survey results & final screens
Once our research validated the three motivation groups, we decided to test adding three screens which included questions and response options representing the motivations to the onboarding.
The decision was controversial since the general direction at the time was to cut the number of the onboarding screens, not add more.
I can’t share the full survey results within the case study due to data confidentiality, but I’d love to share one key insight which stood out:
The combinations of motivations naturally formed user profiles. Aspirational goals were often tied to tangible skills and language skills. For example, someone learning for their career (aspirational goal) usually wanted to improve writing emails (tangible skill) and grammar (language skill).
This gave us a really strong starting point for personalization in the future projects.
7% increase in revenue and 8% increase in visit-to-sale
The motivation screens led to a 7% increase in revenue and 8% increase in visit-to-sale. Through this we learned that understanding the motivations of the user can help us design experiences that support our revenue goals.
This experiment was a winner of a quarterly BOLD award given to projects where big bets lead to big revenue gains.
Personal learnings
This project will always hold a special place in my designer heart as it was one of our first big wins at Babbel. Beyond learning to trust my intuition, I took away two key lessons:
Take risks - Sometimes it’s worth going against the grain, especially when you have evidence to support your bold design decision.
Leverage AI - This was the first time I used ChatGPT in a project, and it quickly became an essential part of my process. I now use it for ideation, learning, feedback, and navigating design challenges.
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