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Company focus

Angi
Product Trade-Off Hard Member-only

For Angi's instant booking feature, should we optimize for maximum availability of providers or maintain stricter vetting to ensure higher quality service?

Prepared by NextSprints

15 mins
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Trade-Off Analysis Data-Driven Decision Making Experimentation Design Home Services On-Demand Economy Marketplace Platforms User Experience Product Strategy Marketplace Optimization Growth Quality Vs Quantity
Product Management Trade-Off Question: Angi instant booking provider availability versus service quality optimization

Introduction

The trade-off we're examining for Angi's instant booking feature is between maximizing provider availability and maintaining stricter vetting for higher quality service. This scenario involves balancing user convenience with service quality, which are both crucial aspects of Angi's value proposition. I'll analyze this trade-off by considering its impact on various stakeholders, potential outcomes, and key metrics, ultimately providing a recommendation based on data-driven experimentation.

Analysis Approach

I'd like to outline my approach to ensure we're aligned on the key areas I'll be covering in my analysis.

Step 1

Clarifying Questions (3 minutes)

  • Based on Angi's business model, I'm thinking instant booking might be a key revenue driver. Could you share how significant instant bookings are to our overall revenue?

Why it matters: Helps prioritize the trade-off against business objectives Expected answer: Instant bookings contribute 30-40% of revenue Impact on approach: Higher revenue contribution would lean towards maximizing availability

  • Considering user behavior, I'm assuming convenience is a primary factor for choosing instant booking. What percentage of users abandon bookings due to lack of immediate availability?

Why it matters: Indicates the importance of availability to user conversion Expected answer: 20-30% abandonment rate due to lack of availability Impact on approach: High abandonment would prioritize increasing availability

  • From a technical perspective, I'm curious about our current vetting process. How automated is our provider vetting system, and what's the average time from application to approval?

Why it matters: Assesses the feasibility of scaling vetting processes Expected answer: Semi-automated with manual review, 2-3 days average approval time Impact on approach: Longer approval times might necessitate process optimization

  • Regarding our current resources, what's our capacity for increasing manual vetting if needed?

Why it matters: Determines the feasibility of stricter vetting Expected answer: Limited capacity, would require hiring or reallocating resources Impact on approach: Resource constraints might favor maintaining current vetting levels

  • Considering our product roadmap, is there a specific timeline or milestone we're aiming for with this decision?

Why it matters: Helps frame the urgency and scope of the decision Expected answer: Aiming for implementation before peak season in 3 months Impact on approach: Short timeline might favor incremental changes over major overhauls

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Updated Jan 22, 2025