Exploring the Future of Retail: Top Innovations to Watch for at NRF 2024
Retail innovation can often be a great idea in search of a problem. As AI exploded into our consciousness this year, it has quickly become a hammer where almost every problem looks like a nail. Solving retail problems with technology can be beneficial but also worsen issues. Retail theft is a significant problem that the rapid expansion of self-checkout technology might have exacerbated. Several retailers have recently said that more employees are the simple solution to retail theft. Old-school.
The NRF Big Show is coming up soon, and plenty of retail innovations will be displayed this year as usual. Among all the exciting developments happening in retail, there are three things that I am most excited to see and learn more about, including Retail Automation, Returns Wrangling, and Practical Retail Uses For Retail AI. I can’t wait to witness these advancements and discover more about their practical applications.
Cashierless Technology Morphs Into Automated Shopping
AmazonGo has been leading the way in cashierless technology, and it plans to license it more widely by 2024. This technology has slowly evolved due to two significant challenges: high deployment costs and limited store coverage. However, AI Visual Technology is expected to overcome these challenges. Thanks to the rapid pace of AI development, the use of this technology has expanded significantly over the past few years. In 2024, we can expect a significant increase in automated shopping systems (In-store OS), which will be lighter and more powerful.
As the technology behind cashierless stores advances and becomes less reliant on expensive shelf sensors and RF technology, its costs are expected to decrease significantly while performance improves. With the technology becoming more cost-effective, stores are likely to expand in size and number, and other applications of the technology are likely to be developed to enhance supply chain management and inventory tracking and automate routine tasks currently performed by store employees.
This technology will enhance the customer experience by allowing store employees to interact more with shoppers. While privacy concerns will arise, as with any new technology, it can be resolved by addressing the challenges before widespread implementation. Many shoppers will likely embrace AI personalization as it will make loyalty and experiential connections across channels smooth and effortless.
Amazon is implementing its technology at high-traffic locations such as airports, sports venues, and college campuses. This move is aimed at gathering valuable insights to enhance their technology. Additionally, several startups, such as Standard AI, Cooch, and Sensei, have made significant strides over the past couple of years, utilizing various computer vision technologies and artificial intelligence to tackle a range of retail challenges.
Returns Wrangling
Newsflash: retail margins aren’t great. Returns are a real problem, especially as retailers set loose expectations during a land grab for e-commerce market share. In the US, 16% of items are returned on average for in-store and e-commerce purchases, of which around 10% are fraud and a figure that almost triples for items bought online and returned to the store, according to Capital One Shopping.
What emerging ideas are happening to deal with returns? Shopper behavior has evolved as Amazon set different expectations for the shopping experience. What predictive technology is being developed to prevent a return in the first place?
New companies have popped up to help meet the demand for solutions, including Happy Returns and Loop, and a whole new crop of approaches is going on as machine learning is applied to counter fraud and predict return likelihood. Companies like Onebeat are rethinking the efficiency of secondary sales and how to maximize return resales, all part of operational effectiveness.
Practical Uses Of Retail AI — Holistic Asset Protection
This year, we have been hearing a lot about retail theft, mainly organized retail crime. Although it may seem like a significant issue, the reality is different. Recent data has shown that shoplifting actually decreased in the past year, which contrasts with the sensationalized news reporting on the problem. The NRF initially made strong statements about organized retail crime and has since backtracked.
Retailers have been facing an old problem of preventing theft, whether it’s from the front, side, or back door. However, with new challenges like BOPIS ‘Sweet-hearting’, it has become even more difficult to check on it. This problem has two consequences — firstly, it results in more theft in stores, and secondly, it may prompt some shoppers to shop less out of fear.
Asset protection is now an essential aspect of maintaining and increasing retail profitability. To identify unusual activities in their stores and determine the root cause of the problem, retailers are adopting new comprehensive techniques such as facial recognition and digital twin technology. Although combining artificial intelligence and the Internet of Things (IoT) can bring significant benefits, ethical AI concerns must be addressed before implementing solutions. Retailers have access to vast amounts of data, and AI can be used to understand what is happening in real-time and take action based on that information. The issue is not having too much information but managing the data.
This year’s NRF conference brings together 40,000 retail industry professionals to discuss emerging retail innovation, along with challenges and opportunities in the industry. I’m looking forward to learning something new and expanding my thinking about the applications of retail technology to solve some of its most pressing problems.
