Fermi Estimate of Instagram's Daily Like Volume

Quick Overview

A product manager estimation exercise asking the candidate to size how many likes Instagram users give in a single day. It tests defining what counts as a like, building a segmented user-based equation with labeled assumptions, and validating the total with an independent cross-check and a sensitivity range.

Fermi Estimate of Instagram's Daily Like Volume

Company: Amazon

Role: Product Manager

Category: Product / Decision Making

Difficulty: medium

Interview Round: Other

Estimate how many likes Instagram users give, across the whole app, in a single day. Talk through your reasoning and finish with a number. ```hint Not everyone taps at the same rate Before multiplying anything, think about which groups of users behave differently enough that one average would mislead you, and what you could count from a second direction to test your result. ``` ### Clarifying Questions - Which taps count: only hearts on feed posts and Reels, or also likes on Stories, on comments and in direct messages? - Should likes from bots and fake accounts be counted, or only likes from real people? - Does the interviewer want a single point estimate, or a range along with the assumption that drives it most? ### What a Strong Answer Covers - A definition of what counts as a like, and over which window, settled before any arithmetic - An equation that builds the total from users and per-user behavior, with users split into engagement segments - Round assumptions labeled as assumptions, and arithmetic the interviewer can follow line by line - An independent cross-check, for example from the volume of content posted, plus a sanity check against something known - Which assumption the answer is most sensitive to, and the resulting range ### Follow-up Questions - How would your number change if like counts were hidden from viewers by default, and why? - Would you expect the like rate on Reels to be higher or lower than on feed photos, and how would that shift the total as Reels grow? - If this number fell sharply in one week, what would you check first?

Overview: A product manager estimation exercise asking the candidate to size how many likes Instagram users give in a single day. It tests defining what counts as a like, building a segmented user-based equation with labeled assumptions, and validating the total with an independent cross-check and a sensitivity range.

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Amazon
Dec 24, 2024
mediumProduct ManagerOtherProduct / Decision Making
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Estimate how many likes Instagram users give, across the whole app, in a single day. Talk through your reasoning and finish with a number.

Clarifying Questions Guidance

  • Which taps count: only hearts on feed posts and Reels, or also likes on Stories, on comments and in direct messages?
  • Should likes from bots and fake accounts be counted, or only likes from real people?
  • Does the interviewer want a single point estimate, or a range along with the assumption that drives it most?

What a Strong Answer Covers Guidance

  • A definition of what counts as a like, and over which window, settled before any arithmetic
  • An equation that builds the total from users and per-user behavior, with users split into engagement segments
  • Round assumptions labeled as assumptions, and arithmetic the interviewer can follow line by line
  • An independent cross-check, for example from the volume of content posted, plus a sanity check against something known
  • Which assumption the answer is most sensitive to, and the resulting range

Follow-up Questions Guidance

  • How would your number change if like counts were hidden from viewers by default, and why?
  • Would you expect the like rate on Reels to be higher or lower than on feed photos, and how would that shift the total as Reels grow?
  • If this number fell sharply in one week, what would you check first?