← Nike Interview Insights

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

Intermediate
Jul 2026

Summary

Nike product analytics interview, one question about diagnosing a conversion drop. Pretty lean on details but the question itself had some meat to it.

Questions Asked (1)

Q1

Nike's sitewide conversion rate has been declining year over year. How would you go about evaluating what's happening?

Product Analytics & MetricsRoot Cause Analysis
Author's notes

My first instinct was to jump straight into funnel drop-off analysis, which I think was okay but I skipped past the step of actually defining what 'conversion' means in this context.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the metric definition and scope—sitewide conversion rate could be affected by traffic mix, seasonality, or product changes. Then systematically segment the data to isolate the root cause, considering both technical and business factors, and propose a hypothesis-driven investigation plan.

Pro tip: Mention that you would check for instrumentation or tracking changes first, as a sudden drop often stems from data quality issues rather than actual user behavior. Also, consider external factors like competitor launches or macroeconomic trends that could impact conversion.

1. Clarify the metric and scope

Define what 'sitewide conversion rate' means (e.g., sessions to orders, users to purchases) and confirm the time frame and segments (e.g., all platforms, regions). Ensure you understand how the metric is calculated and whether any recent changes in tracking could affect it.

2. Segment the data

Break down conversion rate by dimensions such as device type, traffic source, geography, new vs. returning users, and product category. Look for segments with the largest declines to narrow down the problem area.

3. Analyze the funnel

Examine each step of the conversion funnel (e.g., product view, add to cart, checkout initiation, purchase) to identify where the drop-off occurs. Compare funnel metrics year over year to pinpoint the stage with the most significant change.

4. Investigate technical and business factors

Check for technical issues like site performance, bugs, or A/B tests that could impact conversion. Also consider business factors such as pricing changes, promotions, inventory availability, and competitor actions.

5. Form and test hypotheses

Based on the segmentation and funnel analysis, develop hypotheses about the root cause. Validate them with additional data (e.g., user surveys, session recordings) and, if possible, run experiments to confirm causality.

Key Points to Mention

  • Data quality and instrumentation: verify tracking is consistent and no changes have occurred.
  • Segmentation: analyze by device, channel, geography, user type, and product category.
  • Funnel analysis: identify which stage of the purchase process is underperforming.
  • External factors: consider seasonality, competitor activity, and macroeconomic trends.
  • Technical performance: assess page load times, errors, and mobile responsiveness.
  • Business changes: review pricing, promotions, and inventory issues.

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