How would you test the LinkedIn feature People you may know when you don't have any data to base your decision off of?

Introduction

Testing the LinkedIn feature "People You May Know" without existing data presents a unique challenge in product success metrics. To approach this 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 (5 minutes)

"People You May Know" is a recommendation feature designed to expand users' professional networks on LinkedIn. It suggests potential connections based on various factors like mutual connections, similar work histories, or shared educational backgrounds.

Key stakeholders include:

1. Users seeking to grow their professional network
2. LinkedIn's growth and engagement teams
3. Advertisers looking to reach a broader audience

User flow:

1. User logs into LinkedIn
2. They navigate to the "My Network" tab
3. They view suggested connections in the "People You May Know" section
4. Users can choose to connect, ignore, or view more details about each suggestion

This feature aligns with LinkedIn's broader strategy of fostering professional connections and increasing user engagement. Compared to competitors like Facebook or Twitter, LinkedIn's recommendations are uniquely focused on professional relationships rather than personal ones.

Product Lifecycle Stage: As we're starting without data, this would be considered an early-stage or MVP (Minimum Viable Product) launch. The focus will be on rapid learning and iteration based on initial user interactions.