How can ClassPass improve its class search functionality to help users find more relevant workout options?

Introduction

To improve ClassPass's class search functionality and help users find more relevant workout options, we need to dive deep into user behavior, pain points, and potential solutions. I'll analyze the current situation, identify key user segments, explore pain points, generate innovative solutions, and propose a roadmap for implementation. Let's begin by clarifying some crucial aspects of the problem.

Step 1

Clarifying Questions (5 mins)

• Looking at ClassPass's position in the fitness market, I'm thinking about the primary use cases and key features driving user engagement. Could you share insights on the most common user behaviors and interaction patterns across platforms (mobile app, web, etc.)?

Why it matters: Helps identify areas of friction in the current search experience Expected answer: Users primarily search on mobile, often looking for same-day classes Impact on approach: Would prioritize mobile-first solutions and real-time availability features

• Considering the evolving fitness landscape, I'm curious about ClassPass's current product lifecycle stage. Where are we in terms of market penetration, and what key metrics are driving this improvement initiative?

Why it matters: Determines if we focus on user acquisition or retention strategies Expected answer: Mature growth stage, focusing on user retention and engagement Impact on approach: Would emphasize personalization and loyalty features in search

• Given the competitive nature of the fitness industry, I'm interested in understanding ClassPass's unique value proposition. How does our class search functionality currently differentiate us from competitors, and what are the main pain points users express?

Why it matters: Identifies areas where we can further strengthen our competitive advantage Expected answer: Diverse class options are a strength, but users struggle with decision paralysis Impact on approach: Would explore ways to simplify choice while maintaining variety

• Considering the potential for data-driven improvements, I'm wondering about the availability and quality of user data. What types of data do we currently collect on user search behavior and class attendance patterns?

Why it matters: Determines the feasibility of implementing AI-driven personalization Expected answer: Rich data on search queries, bookings, and attendance, but limited personal preferences Impact on approach: Would focus on leveraging existing data while exploring ways to gather more personalized information