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Instacart·Data Scientist·Technical Phone Screen·Senior

Senior
May 2026

Summary

Instacart data scientist interview with a tricky A/B testing scenario where the north star metric moves in the wrong direction but a secondary metric looks good. Forces you to think carefully about what you actually care about optimizing.

Questions Asked (1)

Q1

An experiment increases average order volume but decreases profit per order (the north star metric). Do you launch? Walk through your decision process.

A/B Testing & ExperimentationProduct Analytics & MetricsProduct Strategy
Author's notes

This one tripped me up because the instinct is to get excited about higher order volume and rationalize the rest.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the experiment design and metric definitions, then analyze the trade-off between AOV and profit per order to assess net impact on total profit. Consider guardrail metrics and long-term effects, and recommend a decision based on statistical significance and business strategy.

Pro tip: Always check if the decrease in profit per order is offset by the increase in order volume, leading to higher total profit. Also, consider whether the change aligns with the company's strategic goals, such as customer lifetime value or market share.

1. Clarify Metrics and Experiment Design

Ensure you understand how AOV and profit per order are defined, the experiment duration, sample size, and randomization unit. Confirm that the north star metric is indeed profit per order and not total profit.

2. Analyze the Trade-off

Calculate the net effect on total profit by multiplying AOV and profit per order, or by summing total profit across groups. Check if the increase in AOV compensates for the decrease in profit per order.

3. Evaluate Statistical Significance and Guardrails

Test if the changes are statistically significant and not due to chance. Also, check guardrail metrics (e.g., customer satisfaction, return rates) to ensure no negative side effects.

4. Consider Long-Term and Strategic Implications

Assess whether the change affects customer lifetime value, retention, or other long-term metrics. Consider if the experiment aligns with business objectives like market share growth or profitability.

5. Make a Recommendation

Based on the analysis, recommend launching, not launching, or iterating. If total profit increases and guardrails are fine, launching might be justified despite lower profit per order.

Key Points to Mention

  • Definition of north star metric: profit per order vs. total profit
  • Net impact calculation: total profit = AOV * number of orders * profit margin
  • Statistical significance and power analysis
  • Guardrail metrics and potential negative consequences
  • Long-term effects: customer lifetime value, retention, and repeat purchases
  • Business strategy alignment: short-term vs. long-term goals

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