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Design A/B Test for Subscription Price Increase Effectiveness

Last updated: Mar 29, 2026

Quick Overview

This question evaluates competency in experimental design, statistical reasoning, and product analytics focused on pricing experiments and multivariate UI tests for sign-up funnels.

  • medium
  • Google
  • Analytics & Experimentation
  • Data Scientist

Design A/B Test for Subscription Price Increase Effectiveness

Company: Google

Role: Data Scientist

Category: Analytics & Experimentation

Difficulty: medium

Interview Round: Onsite

##### Scenario B2B SaaS company considering raising subscription prices. 2) Website sign-up funnel exploring button color and placement changes. ##### Question Your PM asks for a two-week A/B test to evaluate a subscription price increase. How would you design the experiment? Should pricing be A/B-tested at all, and how would you decide if the new price is beneficial? A sign-up page currently shows a red button at the top. The team wants to test red vs blue and top vs bottom to lift click-through. How would you structure and analyze this multivariate test? ##### Hints Discuss metrics (conversion, LTV, churn), sample-size, test length, randomization, interaction effects, user cross-bucket risk, and alternative before-after designs.

Quick Answer: This question evaluates competency in experimental design, statistical reasoning, and product analytics focused on pricing experiments and multivariate UI tests for sign-up funnels.

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Google logo
Google
Jul 12, 2025, 6:59 PM
Data Scientist
Onsite
Analytics & Experimentation
66
0

Scenario

A B2B SaaS company is considering:

  1. Raising subscription prices and wants a two-week A/B test to evaluate the impact.
  2. Improving a sign-up page where the current call-to-action (CTA) button is red and placed at the top. The team wants to test button color (red vs blue) and placement (top vs bottom) to increase click-through.

Task

  1. Pricing test
  • How would you design an experiment to evaluate a subscription price increase over two weeks?
  • Should pricing be A/B-tested at all? If so, how? If not, what alternatives would you use?
  • How would you decide if the new price is beneficial?
  1. Multivariate sign-up test
  • How would you structure and analyze a multivariate test for button color (red vs blue) and placement (top vs bottom) to lift click-through?

Hints

Discuss metrics (conversion, LTV, churn), sample size, test length, randomization unit, interaction effects, user cross-bucket risk, and alternative before-after designs.

Solution

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