How Visual AI Is Driving Sustainability in Retail

Find out how brands and retailers are using AI to lower energy consumption, limit overstock, reduce waste, and bring about meaningful change.

This article was originally published by Total Retail

For decades, the topic of sustainability was on the back burner for brands and retailers across their business models, networks of manufacturers, and supply chains. But now, that’s starting to change. 

Retailers in every sector are boosting their commitment to sustainability. For some brands, being environmentally friendly has been a core element of their DNA since day one. For others, increasing efforts to reduce waste and shrink their carbon footprint have been motivated by the desire to appeal to conscious consumers. 

Many brands and retailers are turning to advanced technology like visual artificial intelligence (AI) to lower energy consumption, limit overstock, reduce waste, and bring about meaningful change.

3 Ways Visual AI Fuels Sustainability

Many brands and retailers have already adopted visual AI for its ability to boost conversion and sales and provide an ideal product discovery experience. However, its benefits extend far beyond customer-facing capabilities. 

Visual AI, and the vast customer data it produces, can be instrumental in efforts to improve supply chain efficiency and support circular fashion. Here’s how.

1. Trend Forecasting and Supply Chain Optimization

Visual AI enables brands and retailers to forecast what shoppers want, which informs what styles to buy, how much, and when with a high degree of accuracy. 

Each time a shopper interacts with a product on your site, visual AI works behind the scenes to make inferences about their style, preferences, and intent based on the product’s visual attributes. Deep tagging makes this possible by producing a comprehensive list of tags down to minute details. With more precise product tags, it’s possible to understand exactly what shoppers are looking for.

For example, you might perceive a sudden uptick in the sales of linen trousers as a signal that you should increase your stock. However, upon closely analyzing your visual AI data, you learn that not all linen trousers are in-demand, only high-waisted and wide-legged styles. 

With this detailed insight, you can refine your inventory planning and buying to stock styles your shoppers want. Moreover, you can purchase the correct quantities to avoid surplus, which drives over-manufacturing and leads to textile waste. 

Textiles generate more greenhouse gasses per unit of material than almost any other industry, so reducing textile waste goes a long way. By manufacturing fewer low-demand products, you will also reduce the environmental impact of transporting and storing these items.

Woman in a linen dress sitting on an arm chair.

2. Online Merchandising

Insights derived from visual AI on your eCommerce site can improve your merchandising strategy by indicating when to promote certain products. You can keep inventory flowing and lower the impact of warehousing excess stock by combining information on consumer demand with stock levels. 

Brands and retailers replenish their inventory every season, and deadstock takes up valuable space which can otherwise be used to store new items. Operating more warehouses drives up a brand’s carbon footprint due to vast energy consumption, including lighting, heating, cooling, and ventilating, which increases storage costs and carbon dioxide emissions.

After analyzing your visual AI data, you might notice velour evening gowns are not selling well. Floor-length satin gown sales, on the other hand, are booming. To boost sales and clear out inventory, you can begin by altering your online merchandising strategy to highlight velour gowns. To do so, you might pair both types of dresses in relevant shoppers’ recommendation carousels, ranking the velour dresses higher in search results and category pages, and promoting user-generated content (UGC) in the form of shoppable stories. 

Girl in mustard yellow linen overalls and a white tee.

3. Second-Hand Fashion

Seasoned thrifters describe second-hand shopping as a treasure hunt. They can easily spend hours sifting through piles of pre-loved clothing and items in-store or scroll endlessly through online marketplaces. Visual AI makes product discovery instant, intuitive, and personalized for second-hand hunters and gatherers. It offers similar recommendations when one-of-a-kind pieces are out-of-stock, which increases conversion (CVR) for retailers.

Visual AI seamlessly connects buyers to the products and styles they are searching for. By providing a simple and tailored customer experience on second-hand marketplaces, brands and retailers can encourage consumers to buy more circular fashion while keeping inventory moving. This technology lowers the environmental impacts of extra warehousing and does away with excess stock, which is beneficial for long-term sustainable shopping practices.  

Sustainability Will Play a Bigger Role in the Future of Retail

With tools like visual AI, retailers can reduce their environmental footprint while boosting revenue and cutting costs. By gaining a real-time view of what customers really want, you’ll have the necessary insights to encourage more sustainable shopping habits and improve business outcomes.