AI technology has become increasingly prevalent in the retail industry, providing retailers with new and innovative ways to engage with customers, optimize their operations, and drive sales.
Algorithms can analyze factors such as historical sales data, weather patterns, and social media trends to forecast demand and optimize inventory levels. As a whole, this analysis can help retailers reduce waste, avoid stock issues, and improve their bottom line.
While some retailers are experimenting with AI-powered store experiences and shopping assistants to help customers navigate stores, find products and make purchase recommendations, others are leveraging AI for fraud detection, inventory management, and supply chain optimization.
Retailers can use AI to analyze customer data, such as purchase history, and browsing behavior to deliver targeted and personalized marketing messages. This not only increases the relevance of marketing messages but can improve the overall customer experience. For consumers, one of the most significant applications of AI is its personalized marketing abilities. Personalization has become a key driver of success in the retail industry. Consumers want tailored experiences that cater to their individual needs and preferences, and retailers who fail to deliver risk falling behind.
Stylitics, a leading provider of AI-powered digital merchandising and styling technology, is helping retailers meet this challenge and stay ahead of the curve. Stylitics’ platform leverages machine learning algorithms and consumer data to deliver highly personalized recommendations to shoppers. Their system recommends outfits and bundles in over 50 billion shopper sessions a year and in 2022 has driven more than $4 billion in incremental revenue for its customers; and sold 200 million plus additional units.
Stylitics builds a rich ‘Style Profile’ based upon each visitor’s engagement with outfits, items, and bundles. The platform’s AI can help direct the shopper’s browsing path, create personal shopping experiences like “looks you’ll love” and can deliver personalized ads, emails, landing pages, and even clienteling.
“Our AI says ‘Okay, what is this product, what is the brand, what is the context’ and then it automatically will style it, depending on guidelines and agreements that we’ve set up for the brand.
A bad version of AI would be if it said this pair of jeans is a great pairing with this other pair of jeans, or maybe some shorts. That’s a turnoff for shoppers – It doesn’t show them variety. So what our system is actually doing is, the AI is going to say ‘what similar types of outfits exist for similar types of products’ and start pulling outfits together. Are they different enough? Do they have occasion, variety and seasonality built in?
At the same time, it’s also accounting for all of the specific brand guidelines that might exist. Our system is dramatically different – if you, the merchant, say “Stylitics, we have our new collection and it cannot be styled with the old collection – except if it’s ‘maternity’ or if it’s in this new print, in which case you can, but not in these regions, and not at these price points” – We have built a system that can take those guidelines and across 1000s of different attributes and combinations, teach the system this is what the merchants want – And this happens in the course of a day. So now this product in this collection will be styled exactly as they want. And for a different brand, a different retailer, a very similar product might be styled completely differently, again depending on the brand context.”
– Rohan Deuskar, Founder & CEO, Stylitics
Stylitics’ content automation and visual. Merchandising technology allows more than 4,500 brands and retailers—including Walmart, Puma, Macy’s, Kohl’s and Revolve—to scale outfitting and bundling programs without the need to build out a dedicated styling and merchandising team.
By providing such personalized recommendations, retailers can capture the attention of shoppers who may have otherwise left their site or store without making a purchase and increasing the average order value by suggesting complementary products and upsell opportunities. These solutions can build stronger customer relationships by showing shoppers that they are understood and valued.
As with most innovations, retailers must also be aware of the potential drawbacks associated with AI, such as the risk of perpetuating bias if AI systems are not designed with diversity and inclusion in mind. Additionally, data privacy and security are paramount, and retailers have the responsibility to store customer data responsibly and protect it.
Overall, it’s clear that AI is here to stay in the world of retail and beyond. AI has firmly established itself and its ability to enhance customer experiences, optimize operations, and increase sales growth. It’s crucial for retailers to approach AI implementation with these concerns in mind and collaborate with trusted partners who prioritize ethical AI practices.
By adopting AI in a responsible manner, retailers will create a brighter future for themselves and customers. The question is, will you leverage AI in your business?