Decide content volume and price under uncertainty

Quick Overview

This question evaluates a candidate's competency in pricing and content-production optimization under uncertainty, including defining optimization objectives and constraints, specifying necessary metrics, and assessing sensitivity to changes in variable costs.

Decide content volume and price under uncertainty

Company: Capital One

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: HR Screen

How would you decide how many shows to produce and what subscription price to set for an online-content startup? Lay out: a) an optimization objective (e.g., maximize monthly profit or LTV) and constraints (budget, price cap at $20, production lead times); b) the minimum data you need (demand elasticity to price and content, engagement lift per show, acquisition curve, churn); c) how you would estimate that data (A/B tests, conjoint analysis, holdout-based uplift modeling); and d) how your recommendation would change if variable cost increased from $4 to $6 per subscriber per month.

Quick Answer: This question evaluates a candidate's competency in pricing and content-production optimization under uncertainty, including defining optimization objectives and constraints, specifying necessary metrics, and assessing sensitivity to changes in variable costs.

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Oct 13, 2025, 9:49 PM
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How would you decide how many shows to produce and what subscription price to set for an online-content startup? Lay out: a) an optimization objective (e.g., maximize monthly profit or LTV) and constraints (budget, price cap at 20,productionleadtimes);b)theminimumdatayouneed(demandelasticitytopriceandcontent,engagementliftpershow,acquisitioncurve,churn);c)howyouwouldestimatethatdata(A/Btests,conjointanalysis,holdoutbasedupliftmodeling);andd)howyourrecommendationwouldchangeifvariablecostincreasedfrom20, production lead times); b) the minimum data you need (demand elasticity to price and content, engagement lift per show, acquisition curve, churn); c) how you would estimate that data (A/B tests, conjoint analysis, holdout-based uplift modeling); and d) how your recommendation would change if variable cost increased from 4 to $6 per subscriber per month.

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