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The Convergence of Data & AI to Support Sustainability in Fashion

April 22, 2019

Today, on Earth Day, and everyday, we are thinking about the retail industry’s push towards sustainability. Last week, both Everlane and Adidas announced initiatives around sustainable footwear, as awareness of sustainable practices and ethical production processes grows. Research shows that the fashion industry is responsible for up to 10% of global CO2 emissions, 20% of the world’s industrial wastewater, 24% of insecticides and 11% of pesticides used. In The United States alone, roughly 15.1 million tons of textile waste are produced each year. It is estimated that 85% of this waste ends up in landfills, significantly impacting ecosystems across the globe.

Retailers and brands are beginning to change their practices and must continue to adopt sustainability as a core value in order to connect with today’s shoppers, especially millennials who overwhelmingly (83%) report it is important to them that companies implement programs to improve the environment. In fact, 73% of millennials are willing to pay extra for sustainable offerings. If retailers want to attract the next generation of loyalists to their brand, they should listen to consumers.

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Ethics and Sustainability in Retail

According to Fit and Sizing Thought Leader and Strategist, Mark Charlton, there are two main contributors to the immense amounts of textile waste produced each year. The “Push” model of the fashion industry, and the associated Logistics.

The process of retailers mass producing products and subsequently “pushing” new collections and trends onto customers in excess inventory leads to high rates of waste once trends go out of style if retailers do not sell all of their inventory. Logistics is defined as the impact of expedited shipping and free returns - this leads to an increase in oil usage and carbon emissions associated with flying, driving, and shipping products back and forth from retailers to customers and vice versa.

Using Data to Optimize Product Development, Design and Sourcing  

The retail industry is often centered around the manufacturing pressure of fast-fashion and consistent trends adoption. Since trends have a limited life-cycle, many retailers often find they have overproduced items. This can lead to the destruction of unsold merchandise, rather than extend its uses through recycling and repurposing efforts. 

Data and AI can allow retailers to better understand their customer’s shopping behavior and product preferences, which decreases the chance of overproducing merchandise and helps optimize product development, design and sourcing. For instance, strategizing product development for micro-planning around weather, events, and social media, paired with insights around local demographics and body shapes can optimize assortment and size run curves. Deeper insights into the key products that drive conversion and more accurate forecasts can also help predict the demand and size profiles of your customers. In turn, this results in fewer markdowns, less overproduced product, and the assurance that customers receive a truly one-to-one shopping experience.    
 

Data & AI Improve
Ecommerce Shopping

When customers shop online, there are a variety of added challenges that come with emulating the in-store experience. Without the ability to try on clothes before purchasing, customers often take a risk by choosing what style, fit or size they believe will be right for them. Through data analysis and machine-learning, retailers can eliminate uncertainty and enable consumers to shop with confidence by recommending them products they will both love and keep.

On average, 40% of online purchases are ultimately returned, which substantially increases the "logistics" waste produced through online shopping. Offering fit and style recommendations to consumers based on averages, vs. their personal preferences, is a major contributor to this statistic. The ability to recommend the best style, fit and size to a consumer based on their individual preferences helps diminish the likelihood that customers will need to make returns and contribute to this on-going cycle.

When consumers shop for clothing and shoes online without the aid of personalized recommendations, they are more likely to size sample, or purchase the same item in multiple sizes. When a consumer size samples, retailers can anticipate that at least 50% of the order will be returned once the consumer receives the items and tries them on. This process is inconvenient for shoppers, negatively impacts the retailer’s conversion rates and leads to unnecessary cardboard waste and carbon emissions. If consumers can shop with the same ease and confidence as the traditional in-store shopping experience, then the likelihood of excess waste accumulation from returns decreases.

"On average, 40% of online purchases are ultimately returned, which substantially increases the "logistics" waste produced through online shopping."

 

Embracing Sustainability

As seen from Everlane and Adidas, brands and retailers across the industry are becoming more sustainable and environmentally aware in manufacturing apparel and footwear.

TOMS was founded under the premise that sustainability and social responsibility matter - for every shoe purchased, another pair is donated to a child in need. TOMS offers versions of it’s classic Alpargata shoe using vegan, sustainable materials such as natural hemp, organic cotton, and recycled polyester. Since their conception, TOMS has donated more than 86 million pairs of shoes across the globe.

Premium denim supplier, Levi’s , implemented its own sustainable practices, by creating a line of Water<Less®  Denim. This line was created to diminish the amount of water used in the production of some of the brand’s most popular styles and fits. Levi’s has created more than 20 innovative techniques that result in less water for producing denim with a desired look.

H&M released a new Conscious Exclusive collection to reduce waste and create products made from sustainable, eco-friendly resources. Fabrics from the collection were made using biodegradable materials such as pineapple leaves, orange peels, and algae. The brand launched its first eco-friendly collection in 2012, where all pieces were made from organic cotton, hemp and recycled polyester. The latest collection supports H&M’s larger goal to increase the use of sustainable resources to 100% by 2030.

Outdoor recreation retailer, Moosejaw, noticed many of their customers were resorting to size sampling when shopping online. By improving their customer analytics and data, the brand has been able to significantly reduce returns as a result of size sampling by 24%.

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Understanding the Consumer Helps to Reduce and Plan

The attention around e-commerce impacting the environment is here to stay. The constant introduction of new trends increasingly defines fast-fashion, and leads consumers to buy more. Increased consumption decreases a product’s life-cycle, and increases the likelihood it will end up in a landfill. Additionally, the convenience of shipping items directly to consumers and the widespread promotion of free, easy returns, perpetuates this impact.

In the age of digital and demand, retailers are forced to strategize their production and recommendation processes to simplify the shopping experience for each unique customer. Data and artificial intelligence allows retailers to effectively recommend products in terms of style, size, and fit that satisfy their customer expectations the first time. An increased understanding of customer wants and needs increases customer satisfaction, improves conversion, and decreases the amount of waste produced through a single return.