How technology drives fit consistency, and how learning about your customer leads to ecommerce loyalty.
A brand’s fit is the most important element to its success and legacy. However, fit consistency has long been a challenge for fashion brands. Fashion’s fit problem was born out of the lack of standardization in sizing across the apparel industry but has only grown with the rise of ecommerce and the globalization of fashion. Read on to learn more about fit expectations vs. shopper preference and how data can bring harmony to those often opposing ideas.
Jessica Murphy, True Fit’s co-founder and Chief Operations Officer told Vogue Australia earlier this year that “We all have different body shapes and individual preferences and these two things make the determination of a ‘great fit’ unique for every body. When you combine this with the millions of options that shoppers are presented with, finding a perfect match for your unique body and preferences can be a daunting task, even for the most avid shopper. Billions of garments and shoes are produced annually and these styles are designed to fit differently, produced with different fabrics… all contributing to inconsistent fit and sizing.”
So how can garment technologists leverage retail technology to improve fit consistency across their apparel line? Fibre2Fashion states that brands who utilize 3D shape research to develop grade rules, pattern blocks and fit forms for their ideal customer will reap rewards of repeat business, return reduction and full-price sell through.
Once a fit standard is established and properly maintained across the supply chain, there is still work to be done. True Fit’s Jessica Murphy states:
“There is technical fit and there is how a consumer chooses to wear a garment or footwear. The difference between these two is how we have to reset as an industry. That is why shopper preference and continuing to learn and understand about your shoppers is critically important to getting fit right.”
True Fit observes shopper buying behavior and data across thousands of brands in similar categories to provide this detail back to garment technologists and product development teams to understand fit at source and improve consistency.
To truly understand fit consistency across an apparel line, brands must stay close to observing how their shoppers buy and wear their apparel and footwear to get fit right. True Fit works with hundreds of retailers to help them leverage a cross-market dataset that benchmarks fit by category and by style.
Below, we outline three different ways brands are utilizing True Fit’s intelligence to improve fit consistency for their customers to reduce ecommerce returns and increase loyalty.
01. Fit Block Driving Fit Quality
In the below example, the slim-fit gingham check dress shirt, slim-fit geometric-print dress shirt and slim-fit floral dress shirt were all manufactured from the same fit block, the slim-fit dress shirt block, and all three products are running small. Garment technologists, in this case, can revisit the fit block, grade rules and customer feedback to understand if they should make adjustments to the fit block to increase the fit quality of garments produced in the future.
02. Fabrication Driving Fit Variance
In the below example, each Alexa Cropped Jean was manufactured from the same fit block yet two styles are running large and the other style is running true to size. This indicates that there might be more stretch in the fabrication for the styles running large, causing shoppers to size down in this product for their desired fit. True Fit guides shoppers to the right size on the product page to help them navigate design elements like fabric stretch, rise or the cut of a garment but for a garment technologist, it is important to see this data to understand that the fit block is not driving inconsistency and in this case, fit inconsistency can be attributed to the fabric.
03. Consumer Preference Driving Fit Variance
Consumers are unique in their body shape and in their preferences. Add to this the complexity of trends and styling season over season. What we observe often in our data is that shoppers may not wear a garment the way a garment technologist or designer intends for the garment to be worn. The example below shows a shift dress that shoppers are sizing down in. Rather than wearing the dress oversized and shapeless, shoppers desire for it to fit closer to the body. Conversely, we are seeing trends where shoppers are sizing up in t-shirts or blazers to achieve a boxy, oversized look that was perhaps never intended for the design and fit of the blazer or t-shirt. Observing this data can inform garment technologists on the desired look and fit for their customers.
Apparel is a sized category where fit is so critical to customer sentiment, advocacy and ultimately loyalty. It is the second highest returned category with an average return rate of 12.2% according to a report by CNBC. Maintaining a fit standard means making fit core to a fashion brand’s retention strategy. Fit touches every part of a retailer’s business from product development and manufacturing to operations, marketing, customer experience and finance.
Today, brands are focused on new customer acquisition and competing in a marketplace where there are thousands of brands for shoppers to choose from. The most important element of maintaining and improving fit consistency to earn that shopper’s loyalty is to prioritize continuous learning by staying close to their customers’ behaviors and preferences and adjusting the fit and product offering based on real time insights and data.
Fit consistency leads to loyalty. Get in touch with True Fit today to discuss your strategy.