Why the Marriage of AI and AR Can Help Reduce Product Returns
Thriving in today’s retail environment is no easy feat. It requires new thinking and new ideas. In addition to maintaining customer attention and loyalty, an old foe has come back, gobbling up margins and leaving a trail of waste: product returns.
Costing brands upwards of $300 billion every year, and growing as e-commerce expands as a consumer preference, returns present a unique challenge. However, technologies like artificial intelligence (AI) and augmented reality (AR) can prevent the return from even occurring. They act as powerful tools to meet consumers where they want to be, personalizing the shopping experience and providing them with what they need to make an informed and confident decision, which in turn helps retailers lower return rates.
AI Makes Retailers Smarter About Returns
AI technology has the power to boost consumers’ confidence in their purchases while also suggesting essential complements that can enhance the product purchased. Brands like Levi’s and West Elm are great examples of how retailers can use AI tools to provide customers with tailored recommendations when shopping online, based on their current interests and style preferences. The technology has helped eliminate the dreaded, “Why did I purchase a lime green sweater, I never wear lime green?” moment.
Another use case for AI is to help shoppers make informed decisions when it comes to sizing. Based on a shopper’s measurements, and some brand’s penchants for vanity sizing, a customer might range from a size two to a size six depending on the brand. That wide range often causes customers to buy multiple sizes, which makes return rates spike. Apparel return rates can range as high as 40 percent. Using machine learning and AI helps to understand brand-to-brand size translations, resulting in better fit recommendations for online buyers. Even a reduction of 15 percent in a return rate can lead to millions in cost savings.
Finally, AI can be used to identify consumers who are serial returners. Say “wardrobing” to an apparel retailer and watch shivers move up their spine. Some surveys found up to two-thirds of customers have returned an article of clothing after wearing it once. AI can help identify serial returners and enable the retailer to take action — e.g., charging them for return shipping — to discourage the practice.
Augmenting Reality Into Better Customer Experience
AR is more than just a fun experience for consumers; it’s also a tool to fight returns. Take for example furniture retailers, which are challenged by returns due to products being “not the right size” or “not how I thought it would look in my room.” Giving shoppers the opportunity via AR to preview a piece of furniture in their own home can inspire a customer to purchase, and, with sensor technology, allow them to get a feel of the size of the piece as well. Some early adopters of AR include furniture brands like Crate and Barrel and Ikea. Their apps leverage this exact experience to assist shoppers in making confident decisions in a category where returns might involve flatbed trucks.
AR can also be used to enhance the in-store experience. Clothing company Uniqlo was one of the first to implement AR tech in fitting rooms with its “magic mirror,” allowing shoppers to try on items and see how they would look in different colors. Its effect on consumers results in greater brand trust.
AI and AR: The Perfect Pair to Combat Returns and Enhance Customer Experience
When AI and AR are used in tandem, their strengths multiply to provide a totally comprehensive customer experience. Take Sephora. The beauty retailer is a pioneer in this space, and was one of the first brands to encompass a digital-first strategy for consumers. One of Sephora's most recognized offerings is its Virtual Artist, an AR tool that allows shoppers to try on makeup — from lipstick to eye shadow and more. This enables users to try a variety of products that might first seem out of their comfort zone, but actually result in a desired look. Additionally, it provides a much clearer idea of a product's color on the actual face of the shopper. The app uses AI for its color-match feature that helps users find the right shade of makeup by uploading a photo of themselves. It also teaches users how to apply makeup to achieve certain looks. Each of these elements combined engages consumers with Sephora in a more meaningful way than surface-level product interactions, and encourages confidence in purchase decisions — directly effecting return rates.
Returning to Better Customer Experience
Assisting shoppers — online or in-store — with making better decisions about the products they're searching for using AI makes the path to purchase a less bumpy road. Combining that with AR to “preview” their assisted decisions is an essential combination to the reduction of return rates. Embracing technology to combat returns leads to better margins and a better customer experience with the brand.
Maya Mikhailov is the co-founder and chief marketing officer of mobile retail app developer GPShopper.
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Maya Mikhailov is the co-founder and CMO of mobile retail app developer GPShopper.