For Eventbrite's event discovery feature, should we emphasize personalized recommendations or promote a wider variety of events to increase user exploration?

Introduction

The trade-off between personalized recommendations and promoting a wider variety of events for Eventbrite's discovery feature presents a classic product dilemma. We're essentially weighing the benefits of tailored user experiences against the potential for increased user exploration and engagement. This decision will significantly impact user satisfaction, event organizer success, and Eventbrite's overall platform growth.

In my analysis, I'll cover the following key areas:

1. Clarifying questions to understand the context
2. Identification of the trade-off type
3. Product understanding and ecosystem analysis
4. Trade-off agreement and hypothesis
5. Key metrics identification
6. Experiment design
7. Data analysis plan
8. Decision framework
9. Recommendation and next steps

Step 1

Clarifying Questions (3 minutes)

• Context: I'm thinking about Eventbrite's current market position and growth strategy. Could you share any recent shifts in user behavior or market trends that are driving this consideration?

Why it matters: Helps understand the urgency and potential impact of the decision. Expected answer: Increased competition or changes in user expectations. Impact on approach: Would influence the balance between short-term gains and long-term platform health.

• Business Context: Based on Eventbrite's business model, I assume ticket sales are a primary revenue driver. How does event discovery currently contribute to overall revenue, and are there any specific growth targets tied to this feature?

Why it matters: Aligns the solution with business objectives and revenue impact. Expected answer: Discovery drives X% of ticket sales, with Y% growth target. Impact on approach: Would help prioritize between immediate conversion and long-term user engagement.

• User Impact: I'm curious about our user segments. Can you tell me which user groups (e.g., frequent event-goers, occasional users) are most affected by or engaged with the discovery feature?

Why it matters: Ensures the solution addresses the needs of key user segments. Expected answer: Breakdown of user engagement levels with discovery. Impact on approach: Would influence the balance between personalization and variety for different user groups.

• Technical: Considering the complexity of recommendation systems, what's our current technical capability for personalization, and are there any scalability concerns?

Why it matters: Assesses feasibility and potential technical constraints. Expected answer: Current personalization capabilities and any limitations. Impact on approach: Would impact the complexity and timeline of implementing changes.

• Resource: How is our product and engineering team currently structured around the discovery feature? Are there dedicated resources or competing priorities?

Why it matters: Determines the scope and speed of potential implementation. Expected answer: Team structure and availability for this project. Impact on approach: Would influence the scale and timeline of proposed solutions.