How would you measure the success of Instawork's shift matching algorithm?

Introduction

Measuring the success of Instawork's shift matching algorithm is crucial for optimizing the platform's performance and ensuring value for all stakeholders. To approach this product success metrics problem effectively, I'll follow a structured framework that covers core metrics, supporting indicators, and risk factors while considering all key stakeholders.

Step 1

Product Context

Instawork's shift matching algorithm is a core feature of their on-demand staffing platform. It connects businesses needing temporary workers with qualified professionals seeking flexible work opportunities. The algorithm considers factors like worker skills, availability, location, and past performance to suggest optimal matches for open shifts.

Key stakeholders include:

1. Businesses: Seeking reliable, qualified workers on short notice
2. Workers: Looking for flexible, well-matched job opportunities
3. Instawork: Aiming to facilitate efficient matches and grow the platform

User flow:

1. Businesses post shift requirements
2. Algorithm processes available workers and shift details
3. Matched workers are notified and can accept shifts
4. Businesses review and confirm worker selections

This feature is central to Instawork's value proposition, differentiating them in the gig economy space. Competitors like Wonolo and Shiftgig offer similar services, but Instawork aims to provide more precise matches and a smoother user experience.

Product Lifecycle Stage: Growth - The algorithm is established but continually evolving to improve match quality and expand to new markets and job categories.