I blanked for a second on where to even start.
Break the problem into a top-down estimation: start with Facebook's total user base, segment by daily active users and engagement levels, then estimate average likes per user per day. Validate with a bottom-up sanity check and state assumptions clearly.
Pro tip: Show product sense by linking the estimate to Facebook's business model—likes drive engagement and ad revenue—and mention that you'd validate with internal metrics like DAU/MAU and likes per DAU.
Define what counts as a 'like' (e.g., reactions, comments? just the Like button?) and the time zone (global day). Confirm whether we're estimating for all Facebook surfaces (app, web, etc.).
Start with Facebook's global monthly active users (MAU) and estimate daily active users (DAU) using a typical DAU/MAU ratio (e.g., 60-70%).
Divide DAU into light, medium, and heavy engagers based on how often they like content. Assign average likes per day for each segment.
Multiply the number of users in each segment by their average likes per day, then sum to get the total daily likes.
Validate the estimate by comparing to known metrics (e.g., total likes per day per user) or by doing a bottom-up check (e.g., average likes per post × posts per day).
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.