Returns are costly for businesses, frustrating for customers, and generate significant waste.

One of the most common reasons customers return items is sizing and fit. I wanted to explore how this problem shows up in online shopping and across the user journey. I started with a simple question: why is it so hard to buy the right size online?

As I dug in, I became interested in third-party tools designed to address fit. That exploration led me to start hypothesizing where these tools succeed, where they fall short, and what new opportunities they might unlock.

1. Project Overview

• Project Title: Improving Sizing and Fit… and making it fun!
• My Role: Project Manager
• Timeline: 2 Weeks
• Objective: Enhance the online shopping experience pertaining to sizing + fit, aiming to reduce clothing return rates and increase customer satisfaction

2. Problem Statement

URBN spends about $500M on fit-related returns annually, an explicit bottom-line cost and an indicator of a user experience that needs improvement.

Supporting Evidence and Calculations

3. Goals and Objectives

Project Goal: Decrease returns due to size/fit and increase customer loyalty.

Objective 1: Reduce the % of returns tagged “too small / too big / didn’t fit” (overall, by brand, by category, by channel) by 3% in 12 months.

Objective 2: Reduce % of orders with same SKU in multiple sizes by 20% in 12 months.

Objective 3: Increase engagement with fit-related content by 7% within 6 months, while maintaining or improving conversion.

Objectives Tracker

4. Research

I analyzed 8 competitors and 7 third party tools to get a basic understanding of the existing fit landscape. I conducted secondary research to understand shopper behavior. I then synthesized insights into journey maps and opportunity areas.

Basic Understanding of the Fit Landscape

Summary: there are a variety of third party fit tools, with varying levels of technical complexity, which aid in increasing the confidence a shopper has at the point of size selection (before adding to cart) which has positive implications for customer satisfaction and overall supply chain performance. These tools greatly simplify a tedious spreadsheet alternative and leave opportunity to further develop product recommendation tools and customers gaining more value from offering zero party data.

Journey Map: New UO Online Jeans Shopper

Hypothesis 1: Adoption of a fit assistant will improve the shopping experience. (Try experimenting with some improvements.)

Comparing product dimensions to customer measurements could help shoppers better understand how a particular product size will actually fit them (i.e. loose in shoulders, just right in waist)

Size information should live in the shopper’s account and be easily editable.