What features could we add to Skillshare's mobile app to enhance the learning experience on-the-go?

Introduction

To enhance the learning experience on-the-go for Skillshare's mobile app, we need to identify key features that align with user needs and technological trends. I'll approach this by understanding our users, analyzing pain points, generating solutions, and prioritizing implementations. Let's dive in.

Step 1

Clarifying Questions (5 mins)

• Looking at the mobile learning landscape, I'm seeing a shift towards micro-learning and personalized experiences. Could you share insights on how our users currently engage with Skillshare's mobile app compared to the desktop version?

Why it matters: Determines if we should focus on bite-sized content or full course experiences Expected answer: Higher engagement but shorter session times on mobile Impact on approach: Would prioritize features supporting quick, focused learning sessions

• Considering the diverse range of courses on Skillshare, I'm curious about our user demographics and their primary learning goals. Can you provide information on our most popular course categories and user segments on mobile?

Why it matters: Helps tailor features to specific user needs and interests Expected answer: Creative fields dominate, with a mix of hobbyists and professionals Impact on approach: Would focus on features supporting creative workflows and skill progression

• Given the competitive edtech market, I'm interested in understanding our unique value proposition. What sets Skillshare apart from other mobile learning platforms, and are there any specific areas where we're looking to improve our market position?

Why it matters: Guides feature development to reinforce our strengths and address weaknesses Expected answer: Strong in creative courses, looking to improve user engagement and completion rates Impact on approach: Would prioritize features that enhance community interaction and course progress tracking

• Considering the potential for AI and machine learning in personalized learning, I'm curious about our current data infrastructure. What kind of user behavior data do we currently collect, and how are we leveraging it for personalization?

Why it matters: Determines the feasibility of implementing advanced personalization features Expected answer: Basic user preferences and course history, limited predictive capabilities Impact on approach: Would suggest features to improve data collection and utilization for personalized recommendations