Google·Software Engineer·Hiring Manager Screen·Intermediate

Intermediate

Jun 2026

Summary

Interviewed for a business analyst role at Google, just the one question that I can remember clearly. It was a competitive pricing analysis type of thing and I fumbled through it more than I'd like to admit.

Questions Asked (1)

How would you assess our pricing relative to competitors using only publicly available data?

Pricing & MonetizationProduct StrategyProduct Analytics & Metrics

Author's notes

I went straight to listing data sources (review sites, job postings, press releases) but didn't really structure a methodology before diving in.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the scope—which products or tiers and which competitors—then outline a structured method using public data like pricing pages, feature lists, and third-party sources. Emphasize that as a software engineer, you'd focus on building scalable data collection and analysis pipelines to enable ongoing competitive pricing intelligence.

Pro tip: Acknowledge data limitations upfront and propose a triangulation approach, combining multiple public sources to increase confidence. Show that you think about automation and repeatability, not just one-off analysis.

1. Define scope and competitors

Clarify which Google products or services are in scope and identify the key competitors to compare against. This ensures the analysis is focused and actionable.

2. Identify public data sources

List publicly available data such as competitor pricing pages, feature comparison charts, press releases, SEC filings, and third-party review sites. Consider APIs, web scraping, and public datasets.

3. Collect and normalize data

Gather pricing and feature data, then normalize it into a common format (e.g., price per unit, per user, per GB) to enable apples-to-apples comparison. Use scripts or ETL pipelines for scalability.

4. Analyze and benchmark

Compare Google's pricing against competitors across dimensions like cost, value metrics, and packaging. Calculate relative price indices and identify patterns or gaps.

5. Derive insights and recommendations

Summarize findings, highlight where Google is priced at a premium or discount, and suggest potential actions or further data needs. Emphasize automation for continuous monitoring.

Key Points to Mention

Public data sources: pricing pages, feature lists, SEC filings, press releases, third-party review sites (e.g., G2, Capterra).
Normalization techniques: converting prices to common units (per user, per GB, per API call) for fair comparison.
Automation: using web scraping, APIs, and scheduled jobs to collect and update data regularly.
Data limitations: public data may be incomplete or outdated; triangulate multiple sources and state assumptions.
Competitive dimensions: price, features, packaging, discounts, and total cost of ownership.
Actionable output: dashboards or reports that inform pricing strategy and product decisions.

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