In what ways can Perch optimize its home valuation tool to provide more accurate and timely estimates for sellers?

Introduction

To optimize Perch's home valuation tool for more accurate and timely estimates for sellers, we need to dive deep into user needs, market dynamics, and technological capabilities. I'll outline a comprehensive approach to improve this critical feature, focusing on enhancing accuracy, timeliness, and user trust. Let's begin by clarifying some key aspects of the current situation.

Step 1

Clarifying Questions (5 mins)

• Looking at the product context, I'm thinking Perch might be facing challenges with data freshness and granularity. Could you share more about the current data sources and update frequency for the valuation tool?

Why it matters: Determines if we need to focus on data acquisition or processing improvements Expected answer: Multiple sources with weekly updates, but some lag in local market data Impact on approach: Would prioritize real-time data integration and local market partnerships

• Considering user behavior, I'm curious about the typical user journey. How do sellers usually interact with the valuation tool, and at what stage of their selling process do they engage with it most?

Why it matters: Helps identify key touchpoints for improvement and user expectations Expected answer: Users often check valuations multiple times before listing, with peak usage just before deciding to sell Impact on approach: Would focus on providing trend data and improving re-engagement features

• Regarding product lifecycle, where does the home valuation tool stand in terms of maturity and adoption? Are we looking at incremental improvements or a major overhaul?

Why it matters: Influences the scale and scope of potential improvements Expected answer: Tool is established but facing increased competition and user demands for accuracy Impact on approach: Would balance quick wins with longer-term strategic enhancements

• Considering external factors, how has the recent market volatility affected user trust in automated valuation models? Are there specific areas where users are expressing skepticism?

Why it matters: Highlights potential areas of focus for improving user confidence Expected answer: Users are more skeptical of valuations in rapidly changing markets or unique properties Impact on approach: Would prioritize transparency in methodology and incorporate more real-time market indicators