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Maybe it’s the sugary haze from too much pie, the brain fog from eight rounds of less-than-enlightened debate with the in-laws, or the grogginess from inconsistent holiday slumber — but the post-holiday blues are real — and so are post-holiday returns.
Last year, at least 10% of orders were returned each week from November 2022 to mid-January 2023 in the U.S., as noted by Insider Intelligence, meaning that shoppers made more returns (and did so earlier) than in the previous holiday season. In a broader scope, however, 59% of global respondents in a study conducted by YouGov end up keeping items they don't want due to difficult return policies.
As the halfway mark of the year is going, going, gone, it only means that the holiday shopping season is fast approaching. For global brands and retailers to prepare for the excitement and inevitable post-holiday returns, they may examine how they’re implementing artificial intelligence (AI) into their tech stack.
This begs the question: Can AI in retail help consumers, brands, and retailers, collectively reach a level of copacetic and mitigate post-holiday returns?
This post will cover AI in retail examples, AI in the workforce, and how these tools — when implemented thoughtfully — can make this upcoming holiday season all the merrier.
Digital transformation efforts of leading brands and retailers have been using AI in ecommerce and implementing AI in retail for a while now.
AI services are only projected to grow, with a predicted increase in the retail sector from $5 billion to more than $31 billion by 2028, as noted by Tech News World. And, in terms of global retail market share for AI, North America comes first, with Europe likely to rank second.
But how exactly is AI in retail being used, and what are the potential impacts (and benefits) on the shopping experience and post-holiday returns?
So, with slight shame, a customer walks up to a return counter (or visits a return landing page) and is greeted by the question, “Is there anything wrong with the item?” (Meanwhile, they hear or read, “Is there anything wrong with you?” And, silently they think, “Probably, yeah, I didn’t make the right decision.”)
Whether that’s their internal narrative or not, it happens. With so much competition on the digital shelf, and likely so many channels to shop for the same brands and similar items, it can be hard to make a decision. However, implementing AI in retail can enhance product recommendations based on the consumer’s preferences and browsing history.
It’s quite likely that an ad or “you may also like” can show something the consumer wants before they may even be aware of it. These implementations can also help you organize your product catalog and guide consumers along their buying journey in an intuitive, automated way.
Increase the delight before the sale is made, reduce the likelihood of a return thereafter.
For more than half (54%) of global consumers surveyed in Salsify’s “2023 Consumer Research” report, which offers a consolidated view of its surveyed countries, the number one reason they returned an item was due to it being the wrong size, clothing fit, or product dimensions.
It’s discussed ad nauseam how it’s up to brands and retailers to seamlessly blend their presence on digital and physical channels. And also discussed ad nauseam is the challenge the digital shelf presents of consumers not being able to physically feel or see an item in their space before they buy.
AI’s best remedy for this issue is virtual try-on and augmented reality (AR) in retail.
Though it doesn’t fully resolve the dilemma of consumers not being able to touch and feel clothing, for example, it does allow them to have a much better idea of how the item will look on, if the color or cut will flatter them, etc.
Beyond clothing, AR and in-room 3D modeling can almost perfectly replicate how furniture, art, and other odds and ends will complement a consumer’s space — no more fiddling with a tape measure or guesstimating with arms’ lengths.
Eighty-one percent of consumers in Australia, 83% in the U.S., 88% in Germany, 89% in Great Britain, and 90% in France, buy furniture online per Salsify’s "2023 Shopper Research," an interactive country-by-country breakdown of its annual consumer research — that’d be a lot of guesstimating.
And beyond clothing and furniture, equipping your shopping experience with interactive elements such as these doubles as entertainment.
AI and AR can’t prevent a consumer from changing their mind once they receive the item — or dissuade the “bracketing” phenomenon (when consumers buy multiple versions of the same or similar item with the intent of only keeping one), but it can certainly help them forge a more authentic attachment when they purchase.
To gain customers’ attention across the digital shelf, it might come down to more than just great product information and search engine optimization (SEO).
Visual search capabilities necessitate the incorporation of a healthy amount of high-quality product images.
Better yet, infusing videos and user-generated content (UGC) will also boost your chances that a consumer will stumble across your item in their pursuit of a rare colorway of Jordan 1s for their sneakerhead brother-in-law or a (replacement) Le Creuset soup pot in Ocean for their sister because they can’t find the lid of the one they borrowed. (Or something like that.)
The holiday season can be particularly hectic on and off the clock. Try as they might, your customer service team may not have as much time to address all the questions that roll in — which will likely increase in volume during the holidays anyway.
Employing a chatbot can take some strain off of your teams and better organize nuanced cases as they arise. They can even help employees infuse better recommendations and offers to delight consumers or upsell.
As a brand or retailer selling in the U.S., for example, an AI tool could be particularly impactful on apparel returns for a few reasons:
Additionally, AI and chatbots can leverage additional information that positively influences and informs purchases, such as reviews and UGC. An informed consumer is a returning customer (the good kind of returning).
For example, a customer can ask a chatbot, “Is this item true to size?” Or, “Are these pillow covers washable?” without having to sift through reviews or FAQs themselves.
“AI in the workforce” might stoke fears of replacing employees, but the reality is, AI will predominantly serve as another teammate and take on repetitive tasks or otherwise complex data lift. Per The Washington Post, a replacement of any grand scale won’t happen anytime soon (if ever), as even something as useful-sounding as an autonomous floor cleaner can be problematic.
Using AI to inform inventory management can ensure popular items stay in stock throughout the holiday season. Therefore, consumers will get what they actually want the first time rather than trying to find a replacement they (or a gift recipient) might want to return.
For consumers shopping in-store, AI can help consumers, or help employees help consumers find the preferred items more quickly, as in the case of Sam’s Club’s “Ask Sam” assistant — Sam’s Club being the tech pilot for Walmart, per The Washington Post.
AI can also recommend promotions in effective contexts. If a consumer can save on an item and enjoy their shopping experience, they’re more likely to keep what they buy and return to buy more.
In terms of AI helping with context, for example, it can help you sort contacts and determine that you shouldn’t send a discount for dog beds to a customer who’s only ever bought a heat lamp for a bearded dragon — that’s a wasted offer.
AI tools are another way to bridge the gap between the digital and physical, the human and computer (and AI tools can even help with brand messaging).
Implementing AI for quality assurance, for example, doesn’t have to replace human QC agents, but rather serves as another line of defense against error, especially around hectic holiday schedules.
If a consumer receives the wrong item, or not all of the parts for their item, for example, they might get so annoyed (perhaps rightfully so) that they’ll just return the item rather than give your brand another chance.
And, even more likely, if a consumer receives a broken or defective item, they’re even less likely to return (after making their return).
Related, AI can more quickly catch onto items, inquiries, or issues that are arising when analyzing customer feedback. They can then quickly sort and even predict recurring or critical issues.
You and your teams can then spend less time worrying about problems occurring or finding the problem and instead focus on executing solutions.
The post-holiday blues and high return rates don’t have to do your brand in. With a bit of creativity and the thoughtful application — or adjusting — of AI tools in your tech stack over the next few months, you’ll be more than equipped to make the sales that consumers will want to keep. And that’ll keep everyone’s spirits high.
Yvonne Bertovich (she/her) is an editor and writer at Salsify, reporting from Knoxville, Tennessee. With a longtime passion for research, she enjoys flexing her perspective on ecommerce, trends in consumer behavior, and health and wellness.
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