What features could SeatGeek add to its Deal Score system to provide more personalized recommendations for event tickets?

Introduction

To improve SeatGeek's Deal Score system for more personalized ticket recommendations, we need to analyze user behavior, identify pain points, and develop innovative features that enhance the overall ticket-buying experience. I'll outline a strategic approach to address this challenge, focusing on user segmentation, pain point analysis, and solution generation.

Step 1

Clarifying Questions (5 mins)

• Looking at SeatGeek's position in the ticket marketplace, I'm curious about the current user engagement metrics. Could you share insights on the average user session duration and frequency of visits?

Why it matters: This helps us understand user behavior and identify opportunities for increased engagement. Expected answer: Average session duration of 8 minutes, with users visiting 2-3 times per month. Impact on approach: Longer sessions might indicate a need for more comprehensive features, while shorter sessions could suggest a need for quick, efficient recommendations.

• Considering the competitive landscape, I'm wondering about SeatGeek's unique value proposition. How does the current Deal Score system differentiate from competitors like StubHub or Ticketmaster?

Why it matters: Helps identify areas where we can further strengthen our competitive advantage. Expected answer: Deal Score provides a 0-100 rating based on historical pricing data and seat quality. Impact on approach: We might focus on enhancing the transparency of the scoring system or incorporating more factors into the algorithm.

• Given the importance of data in personalization, I'm interested in understanding what types of user data SeatGeek currently collects and utilizes. Can you provide an overview of the key data points used in the current recommendation system?

Why it matters: Determines the scope of personalization possible and identifies potential data gaps. Expected answer: Currently using search history, purchase history, and basic demographic information. Impact on approach: If limited data is available, we might prioritize features that encourage users to share more information or explore alternative data sources.

• Considering the product lifecycle, where does SeatGeek see the most significant growth opportunities? Are we focusing more on user acquisition or retention at this stage?

Why it matters: Helps align our feature development with overall business objectives. Expected answer: Focusing on retention and increasing average order value from existing users. Impact on approach: We might prioritize features that encourage repeat purchases or upselling premium experiences.