Amazon Average Order Value: Levers, Sizing and Guardrails for Doubling Basket Size
Company: DoorDash
Role: Product Manager
Category: Product Design & Strategy
Difficulty: medium
Interview Round: Other
As a product manager on Amazon's online store, how would you make the average customer cart worth twice as much within six months?
```hint Break the metric apart
Cart value is built from simpler terms. Split it into those terms, and for each one ask whether raising it helps customers and Amazon or only moves the number.
```
### Clarifying Questions
- Does cart value mean the average value of a completed order, or the value of items sitting in carts before checkout?
- Is the target for the whole store, or for a segment such as Prime members, grocery orders or one country?
- Is it acceptable for customers to order less often as long as each order is bigger, or must total spending per customer also grow?
- Are pricing levers such as the free-shipping threshold and multi-buy discounts in scope, or only product and experience changes?
### What a Strong Answer Covers
- A precise definition of the metric and the business reason Amazon would want it higher.
- A breakdown of cart value into its drivers, with a sized check of whether doubling in six months is realistic.
- Levers for each driver, aimed at the shoppers and orders where carts are smallest, and prioritized by impact, effort and time to ship.
- Guardrails that stop a bigger cart from costing order frequency, conversion, total spending or customer trust.
- An experiment plan that measures each lever's real effect.
### Follow-up Questions
- Average order value doubles, but total spending per customer falls. What happened, and was the project a success?
- How would you test a change to the free-shipping threshold for shoppers without Prime, and what would you watch?
- How does your plan change if the goal applies only to grocery orders?
Overview: A product strategy exercise on doubling the average value of an Amazon shopping cart within six months. It tests defining the metric precisely, breaking it into drivers, sizing and prioritizing levers, and setting guardrails so that bigger baskets do not come at the cost of order frequency, conversion or customer trust.