Product design question

How would you improve LinkedIn messenger?

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

Product sense for a professional-context messaging tool, distinct from consumer chat apps.

Define the user: a professional using LinkedIn messenger for networking, recruiting, or sales outreach, not casual chat.
Identify the pain point: high volume of low-quality cold outreach messages makes the inbox feel like spam, reducing response rates.
Prioritize inbox quality over new chat features, since trust in the inbox is what drives usage for professional messaging.
Propose a solution: a smarter message filtering/prioritization system that surfaces warm, relevant messages (mutual connections, shared context) above cold outreach.
Add a lightweight response-intent signal, like a quick 'interested/not now' reply option, to reduce friction for recipients.
Define success metrics: response rate to first messages and reduction in reported spam/cold outreach complaints.

Identifies inbox quality, not feature richness, as the real problem for a professional messaging product.
Proposes a concrete prioritization mechanism using existing LinkedIn signals like mutual connections and shared groups.
Gives an illustrative metric, e.g. raising first-message response rate from 20% to 30%, marked as an assumption.
Adds a low-friction reply option, recognizing recipients often ignore rather than reject unwanted messages.

Proposing consumer-chat features like stickers or reactions that don't fit LinkedIn's professional context.
Ignoring the spam and cold-outreach problem that dominates the real user pain point.

Chapters of the AI PM course that teach what this question tests.