Dataford
Interview QuestionsInterview GuidesExperiencesCoaching
New
Pricing
Get started
Dataford
Popular roles
Software EngineerData AnalystData ScientistData EngineerBusiness AnalystAI EngineerMachine Learning EngineerProduct Manager
Browse
Browse All RolesEvery role hub, from analyst to MLBrowse All CompaniesCompany-specific interview loopsAll Interview GuidesThe full guide library
Top questions by role
Software EngineerData AnalystData ScientistData EngineerBusiness AnalystAI EngineerMachine Learning EngineerProduct Manager
Top questions by skill
SQLPythonStatisticsMachine LearningA/B TestingSystem DesignGenerative AIProduct SenseMetricsBehavioral
Browse all questions →Try a mock interview
Experiences
Practice
Mock InterviewsTimed interview simulations with feedbackCoaching1:1 coaching with people at your target companiesSuccess PathYour 6-week structured planModulesCurated lessons by topicWebinarsTalks from ex-Big Tech data leadsPlaygroundA free-form scratch editor
Learn
BlogInterview strategy and career adviceTech Job Market ReportHiring trends across data and AI rolesFor UniversitiesDataford for career centersAbout DatafordWho we are and how we build
Pricing
Build my plan

North Star Metric for Airbnb

HardMetrics00:00
Practice interviewer
In session
5 left
00:00

Your question is North Star Metric for Airbnb. Take a moment with it on the right.

Talk me through your thinking if you like. When you're confident, submit your answer and I'll grade it like a real screen (7/10 or better passes).

You need to log in / sign up to chat or submit.

Problem

Analytics case study: how would you define/analyze the North Star Metric for a company like Airbnb?

Asked in the data science interview final loop stage, this was part of a Senior PM final loop. It was framed as a hypothetical case using Airbnb as the example company rather than Zillow itself.

Task

  1. Propose and defend a North Star Metric that reflects guest and host value.
  2. Define its numerator, denominator, time window, and inclusion rules.
  3. Explain how you would validate the metric and decompose changes in it.
  4. Identify leading indicators, guardrails, and risks of optimizing it.

Data Available

Assume access to search, listing, booking, cancellation, review, host, guest, and revenue event logs.