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

Intermediate
Apr 2026

Summary

Interviewed for a business analyst role at Swiggy, got hit with a product growth question that felt more like a product manager interview than anything else. Not a bad experience, just unexpected.

Questions Asked (1)

Q1

What strategies would you use to increase the average order value on a food delivery platform?

Product StrategyPricing & MonetizationProduct Analytics & Metrics
Author's notes

I went straight into upselling and cross-selling, like recommending add-ons at checkout, and then talked about bundling deals and minimum order thresholds for free delivery.

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AI HintsAI Generated

Suggested Approach

Start by clarifying the goal and defining AOV, then segment users and orders to identify levers. Structure your answer around product, pricing, and engineering strategies, and tie each to measurable impact and feasibility.

Pro tip: Emphasize experimentation and data-driven iteration: propose A/B tests for each strategy and mention how you'd measure success beyond AOV, such as retention and margin.

1. Clarify and Define

Confirm what 'average order value' means (e.g., per user, per order) and the platform's current goals. Ask about constraints like user experience and restaurant partnerships.

2. Segment and Analyze

Break down users by behavior (e.g., frequency, spend) and orders by composition (e.g., items, cuisine). Identify high-potential segments and patterns that drive higher AOV.

3. Brainstorm Levers

Generate strategies across product (bundles, recommendations), pricing (free delivery thresholds, discounts), and engineering (personalization, dynamic pricing). Prioritize by impact and effort.

4. Design Experiments

Propose A/B tests for top strategies, defining success metrics (AOV, conversion, retention) and guardrails (e.g., delivery time, customer satisfaction).

5. Measure and Iterate

Outline how to analyze results, scale winners, and iterate. Discuss potential trade-offs and long-term effects on user loyalty and restaurant partners.

Key Points to Mention

  • Product bundling and combo offers to encourage larger orders
  • Free delivery or discounts above a certain cart value
  • Personalized recommendations and upselling at checkout
  • Loyalty programs and subscription models (e.g., Swiggy One) to increase order frequency and size
  • Dynamic pricing and targeted promotions based on user segments
  • A/B testing and data-driven decision making to validate strategies

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