I started with total internet users and tried to segment down by job-seeking behavior, which felt reasonable, but I got tangled up trying to define 'actively looking' vs 'passively browsing.' Ended up just picking a number for job-seeker rate without really defending it.
Break the problem into a top-down estimation: start with the total number of Google Search users, then estimate the fraction of those users who are job seekers, and finally the fraction of job seekers who use Google Search for job hunting. Use round numbers and state assumptions clearly, focusing on logical reasoning rather than precise figures.
Pro tip: Show product thinking by segmenting job seekers (e.g., active vs. passive) and discussing how Google's job search features (like Google for Jobs) might influence usage. Also, mention that the estimate is a starting point for further analysis, such as validating with internal data or surveys.
Define what 'use Google Search to find a new job' means: e.g., searching for job openings, company research, or salary information. Clarify whether it's global or a specific region, and the time frame (e.g., annually).
Start with the global population or internet users, then estimate the number of Google Search users. For simplicity, assume ~5 billion internet users and that most use Google Search, so ~4-5 billion users.
Determine the fraction of Google Search users who are actively looking for a new job. Consider employment rates, job turnover, and typical job search duration. For example, if 3% of the population changes jobs annually, that's ~150 million job seekers globally.
Not all job seekers use Google Search for job hunting; some use LinkedIn, Indeed, or referrals. Estimate that a significant portion (e.g., 50-70%) use Google Search at some point, yielding ~75-100 million users.
Validate the estimate by comparing with known data (e.g., Google for Jobs usage, search volume for job-related queries) and adjust assumptions if necessary. Acknowledge uncertainty and suggest ways to improve accuracy.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.