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Google·Software Engineer·Onsite - Product Sense / Strategy·Intermediate

Intermediate
Jun 2026

Summary

Google business strategy question, pretty classic case-style thing but it covers a lot of ground if you actually dig into it.

Questions Asked (1)

Q1

How does Google make money, why has it chosen that business model, and what are the biggest risks to that model going forward?

Pricing & MonetizationProduct Strategy
Author's notes

This looks easy and that's the problem.

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AI HintsAI Generated

Suggested Approach

Start by explaining Google's core business model: selling targeted advertising across its search, display, and video platforms, with additional revenue from cloud, hardware, and app sales. Then discuss why this model was chosen—aligning with Google's mission to organize information and its strength in data and machine learning—and finally outline the biggest risks such as regulatory pressure, privacy changes, and competition.

Pro tip: Show that you understand the engineering implications of the business model—e.g., how ad targeting relies on large-scale data processing and machine learning—and tie risks to technical challenges like privacy-preserving ad tech.

1. Explain the revenue streams

Describe how Google makes money primarily through advertising (Search, YouTube, Network) and secondarily through cloud, hardware, and Play Store. Mention specific products and their contribution.

2. Justify the business model

Explain why advertising is a natural fit: it aligns with Google's mission to make information accessible, leverages its strengths in data, AI, and scale, and creates a virtuous cycle with users and advertisers.

3. Identify key risks

Discuss risks such as regulatory scrutiny (antitrust, privacy laws), platform changes (e.g., Apple's ATT), competition from TikTok and AI chatbots, and dependence on ad spend cycles.

4. Connect to engineering

Highlight how these risks and the business model impact engineering decisions, such as the shift to privacy sandbox, investment in AI for ads, and diversification into cloud.

Key Points to Mention

  • Advertising revenue breakdown: Google Search, YouTube, Google Network, and other bets
  • Why advertising: aligns with mission, monetizes free services, benefits from network effects and data
  • Risks: regulatory (antitrust, GDPR), privacy changes (ATT, cookie deprecation), competition (TikTok, AI search)
  • Google's response: Privacy Sandbox, AI-powered ads, cloud growth, hardware (Pixel)
  • Engineering implications: large-scale data processing, ML for ad targeting, privacy-preserving technologies
  • Future outlook: diversification, AI integration, regulatory adaptation

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.