How can Skillz enhance its tournament matchmaking system to ensure fairer competition across skill levels?

Introduction

Enhancing Skillz's tournament matchmaking system to ensure fairer competition across skill levels is a critical challenge that directly impacts user satisfaction, retention, and the overall health of the platform's ecosystem. I'll approach this problem by first clarifying our understanding of the current situation, then analyzing key user segments and their pain points. From there, we'll generate and evaluate potential solutions, prioritize our approach, and establish metrics for measuring success.

Step 1

Clarifying Questions (5 mins)

• Looking at Skillz's position in the competitive gaming market, I'm curious about the current user retention rates. Could you share some insights on our user churn, particularly for new players versus experienced ones?

Why it matters: This helps us understand if matchmaking issues are causing player dropout, especially among newer users. Expected answer: Higher churn rates among new players, with experienced players showing better retention. Impact on approach: If confirmed, we'd prioritize solutions that improve the new player experience and progression.

• Considering the importance of fair matchmaking, I'm wondering about our current skill rating system. Can you elaborate on how we currently assess and categorize player skill levels?

Why it matters: Understanding the current system helps identify potential flaws or areas for improvement. Expected answer: A combination of win/loss ratio, average score, and perhaps some game-specific metrics. Impact on approach: If the system is too simplistic, we might focus on developing a more nuanced skill rating algorithm.

• Given the competitive nature of tournaments, I'm curious about the balance between matchmaking speed and accuracy. What's our current average wait time for tournament matchmaking, and how does it vary across skill levels?

Why it matters: This helps us understand if we're sacrificing match quality for speed, or vice versa. Expected answer: Average wait times of 30-60 seconds, with longer waits for high-skill players. Impact on approach: If wait times are already long, we might need to focus on optimizing the algorithm for both speed and accuracy.

• Thinking about the broader ecosystem, I'm interested in understanding how tournament rewards are currently structured. Do we see significant differences in reward distribution across skill levels?

Why it matters: This could reveal if there are incentive misalignments causing players to manipulate their skill ratings. Expected answer: Higher rewards at top skill levels, with a significant drop-off for lower tiers. Impact on approach: If there's a large disparity, we might need to consider adjusting the reward structure alongside matchmaking improvements.