Swiggy Product Strategy: Getting Customers to Spend More per Order

Quick Overview

A PM product strategy question on raising average order value for Swiggy, the Indian food and grocery delivery app. It tests reasoning about per-order unit economics, customer and order-occasion segments, basket-building levers, and metrics that keep order frequency and margin from falling.

Swiggy Product Strategy: Getting Customers to Spend More per Order

Company: Paytm

Role: Product Manager

Category: Product Design & Strategy

Difficulty: medium

Interview Round: Other

Swiggy wants customers to spend more each time they order. How would you raise its average order value (AOV)? ```hint Start from per-order economics Ask why basket size matters to Swiggy at all. Some costs are paid once per order no matter what is in the bag, which tells you what a bigger basket is worth and what must not get worse while you grow it. ``` ### Clarifying Questions - Which business is in scope: restaurant food delivery, Instamart quick commerce, or both? Their baskets and margins behave differently. - Why does AOV matter right now: a profitability push to spread per-order delivery cost, a target from leadership, or open exploration? - What must not get worse while AOV rises: orders per customer, total GMV, conversion, or margin after discounts? - Which levers are available: delivery fees and free-delivery thresholds, platform-funded offers, restaurant-funded offers, or only product changes such as recommendations? ### What a Strong Answer Covers - Why AOV matters for Swiggy's per-order economics, and how the answer treats food delivery versus Instamart. - Customer and order-occasion segments, and why each one's baskets stay small today. - Levers grouped by mechanism (offer thresholds and fees, add-ons and bundles, group and planned orders, cross-selling between food and grocery), prioritized by impact, effort and risk. - A success metric that pairs AOV with order frequency and margin, so a higher average cannot come from losing small orders. - Risks such as price-sensitive users moving to Zomato, Blinkit or Zepto, discount cost eating the gain, and slower deliveries for larger baskets. ### Follow-up Questions - After you raise the free-delivery threshold, AOV goes up but weekly orders per user go down. How do you decide whether the change was a win? - How would you design the experiment, given that AOV is a per-order ratio and users may take several weeks to adjust their habits? - How does your plan change if a competitor responds by cutting its own delivery fees?

Overview: A PM product strategy question on raising average order value for Swiggy, the Indian food and grocery delivery app. It tests reasoning about per-order unit economics, customer and order-occasion segments, basket-building levers, and metrics that keep order frequency and margin from falling.

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Paytm
Mar 28, 2026
mediumProduct ManagerOtherProduct Design & Strategy
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Swiggy wants customers to spend more each time they order. How would you raise its average order value (AOV)?

Clarifying Questions Guidance

  • Which business is in scope: restaurant food delivery, Instamart quick commerce, or both? Their baskets and margins behave differently.
  • Why does AOV matter right now: a profitability push to spread per-order delivery cost, a target from leadership, or open exploration?
  • What must not get worse while AOV rises: orders per customer, total GMV, conversion, or margin after discounts?
  • Which levers are available: delivery fees and free-delivery thresholds, platform-funded offers, restaurant-funded offers, or only product changes such as recommendations?

What a Strong Answer Covers Guidance

  • Why AOV matters for Swiggy's per-order economics, and how the answer treats food delivery versus Instamart.
  • Customer and order-occasion segments, and why each one's baskets stay small today.
  • Levers grouped by mechanism (offer thresholds and fees, add-ons and bundles, group and planned orders, cross-selling between food and grocery), prioritized by impact, effort and risk.
  • A success metric that pairs AOV with order frequency and margin, so a higher average cannot come from losing small orders.
  • Risks such as price-sensitive users moving to Zomato, Blinkit or Zepto, discount cost eating the gain, and slower deliveries for larger baskets.

Follow-up Questions Guidance

  • After you raise the free-delivery threshold, AOV goes up but weekly orders per user go down. How do you decide whether the change was a win?
  • How would you design the experiment, given that AOV is a per-order ratio and users may take several weeks to adjust their habits?
  • How does your plan change if a competitor responds by cutting its own delivery fees?