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How would you decide to cancel a TV show?

Last updated: Mar 29, 2026

Quick Overview

This question evaluates a data scientist's competencies in business analytics and strategic decision-making, including financial and valuation reasoning, incremental profitability and revenue/cost driver analysis, and market/competitive assessment.

  • easy
  • Capital One
  • Analytics & Experimentation
  • Data Scientist

How would you decide to cancel a TV show?

Company: Capital One

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: easy

Interview Round: Technical Screen

## Case: Cancel/keep/sell a TV series You are the CEO of a streaming company. You currently produce and distribute a TV series called **"Analyst"**. ### Part A — Cancellation decision You are considering **canceling** the show. 1. What **factors** would you evaluate before deciding to cancel vs. renew? 2. What **market/competitive** considerations (e.g., trends, competitor moves) might change the decision? ### Part B — Improve profitability Assume you decide to keep the show for now. 1. What are the major **revenue drivers** for a TV series like this? 2. What are the major **cost drivers** (use common sense; you don’t have the detailed P&L)? 3. Propose **levers** to increase profit (revenue up and/or cost down). ### Part C — Selling the show/IP You are now considering **selling the "Analyst" project/IP** to another company. 1. What factors determine whether selling is better than keeping it? 2. What data/analyses would you request to make the recommendation? #### Assumptions (state explicitly in your answer) - Objective is to maximize **long-term company value** (not just this quarter’s profit). - If financials are needed, you may use **NPV** with a reasonable discount rate and scenario analysis. - “Profitability” should be interpreted as **incremental contribution margin** attributable to the show (including downstream subscription effects). **Deliverable:** Provide a structured framework and the key analyses/metrics you would use to reach a decision.

Quick Answer: This question evaluates a data scientist's competencies in business analytics and strategic decision-making, including financial and valuation reasoning, incremental profitability and revenue/cost driver analysis, and market/competitive assessment.

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Capital One
Feb 12, 2026, 11:22 PM
Data Scientist
Technical Screen
Analytics & Experimentation
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Case: Cancel/keep/sell a TV series

You are the CEO of a streaming company. You currently produce and distribute a TV series called "Analyst".

Part A — Cancellation decision

You are considering canceling the show.

  1. What factors would you evaluate before deciding to cancel vs. renew?
  2. What market/competitive considerations (e.g., trends, competitor moves) might change the decision?

Part B — Improve profitability

Assume you decide to keep the show for now.

  1. What are the major revenue drivers for a TV series like this?
  2. What are the major cost drivers (use common sense; you don’t have the detailed P&L)?
  3. Propose levers to increase profit (revenue up and/or cost down).

Part C — Selling the show/IP

You are now considering selling the "Analyst" project/IP to another company.

  1. What factors determine whether selling is better than keeping it?
  2. What data/analyses would you request to make the recommendation?

Assumptions (state explicitly in your answer)

  • Objective is to maximize long-term company value (not just this quarter’s profit).
  • If financials are needed, you may use NPV with a reasonable discount rate and scenario analysis.
  • “Profitability” should be interpreted as incremental contribution margin attributable to the show (including downstream subscription effects).

Deliverable: Provide a structured framework and the key analyses/metrics you would use to reach a decision.

Solution

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