How would you design a size-and-fit feature on AJIO to reduce fit-related returns for first-time buyers?

Introduction

Fit is the single biggest reason fashion orders come back in India, and AJIO is no exception. A first-time buyer who has always shopped at a local store or a Trends outlet cannot try the kurta or the pair of jeans before paying, sizes vary wildly between brands on the same platform, and many shoppers in Tier 2 and Tier 3 towns pay cash on delivery precisely because they are not sure the item will fit. Every return costs AJIO reverse logistics, quality checks and a lost sale, and every bad first experience lowers the odds that the customer ever orders again.

The question asks us to design a size-and-fit confidence feature for AJIO's first-time buyers. I'll clarify the scope, explain why AJIO should build this now, choose a user segment, map pain points, generate and prioritise solutions, and close with success metrics.

Step 1

Clarify Questions (3 minutes)

• Is the primary goal to lower return rates, raise first-order conversion, or improve repeat purchase among new customers?

• Why it matters: A feature tuned to reduce returns can also reduce conversion if it makes buyers hesitate.
• Hypothetical answer: The goal is to reduce fit-related returns for first-time buyers without hurting conversion.
• Impact: We'll treat conversion as a guardrail and fit-return rate as the primary outcome.

• Which categories should we focus on first?

• Why it matters: Fit behaves differently for jeans, ethnic wear, footwear and innerwear.
• Hypothetical answer: Start with women's ethnic wear and men's denim and casual shirts, which have the highest fit-return share.
• Impact: The MVP needs to handle both tailored and loose silhouettes.

• Do we have size charts and garment measurements for all brands, including marketplace sellers?

• Why it matters: AJIO sells its own labels, Reliance brands and thousands of third-party brands, and data quality varies.
• Hypothetical answer: Own labels and large brands have measurements; long-tail sellers often have only a generic S/M/L chart.
• Impact: The solution must work with partial data and improve it over time.

• What is the timeline and team?

• Hypothetical answer: One pod (PM, designer, 5 engineers, 1 data scientist) for two quarters.
• Impact: We favour data-driven recommendations over hardware-heavy ideas such as 3D body scanning.

Propose the Goal

Help first-time AJIO buyers choose the right size the first time, so that fit-related returns fall and new customers come back for a second order.

Define the Scope

Focus on the AJIO Android app (the majority of first orders), on product detail pages and the size selector, for apparel in the two pilot categories. AJIO Luxe and footwear are out of scope for the MVP.