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Americans love shopping — so much so that in the pandemic's second year, NPR dedicated an episode of its show “Consider This” to the country's shopping culture. But while just a few decades ago shopping meant going to the mall, much of the activity is now moving online.
Personalized shopping is another area that new technologies have transformed. Where personal shoppers put together clothes for their customers just a few years ago, artificial intelligence is ready to take its place and reinvent our shopping experience.
Related: 5 Innovative Ways to Give Your Customers the Personalized Experiences They Want
AI technologies in retail personalization
Personalization has been a big topic in fashion retail for decades. While personal styling was reserved for the elite in the 19th century, the emergence of personal stylists and personal shoppers in department stores made a curated wardrobe accessible to the masses. Today, leading retailers are turning to artificial intelligence and machine learning to take their customers' shopping experience to the next level.
The trend is not just limited to fashion. Retailers like Amazon have been relying on personalized recommendations since 2010, initially through the “Customers Who Purchased” feature. Offering product recommendations wasn't Amazon's first foray into personalization. The company started this trend back in 1999 by allowing its customers to store shipping and payment information.
Today, retailers continue to use sophisticated machine learning algorithms to provide personalized recommendations to their customers. The use of AI in retail also includes chatbots that greet shoppers on an e-commerce site the way a salesperson would have greeted them in a brick-and-mortar store.
Benefits of AI-driven personalization
Imagine a customer in a huge department store looking for a small item. Even with the best signage, they will likely spend a lot of time searching before finding the specific item. A knowledgeable salesperson would make things easier.
When it comes to eCommerce, most retailers offer a simple search function on their platform. However, using this search feature means someone knows exactly what they are looking for. If the buyer only has a vague idea, the search could become time-consuming. A well-designed AI chatbot can shorten this time by offering products that solve a consumer's problem without them knowing the exact name of the product.
When you look at the fashion industry, the benefits of AI-driven personalization in retail become even clearer. Iconic denim brand Levi Strauss & Co. is working on a project using AI-generated models that would allow customers to see clothes on different body types. The company acknowledged last year that it was not possible to present every single product on different models. AI could potentially step into the breach.
Other benefits include more accurate forecasting of customer demand and the ability to manage deliveries and staff accordingly. This would allow in-person customers to benefit from limited wait times, while e-commerce customers would rarely if ever see the words “out of stock” when ordering. Personalized retail marketing, including on social media platforms, already offers customers more relevant products than traditional marketing tactics. AI can take retail marketing personalization to the next level.
Related: 3 Revolutionary Ways AI is Transforming E-Commerce
Implementing AI in retail
Retailers are facing similar changes to other businesses when implementing AI. In addition to accessible and affordable technology, they need to collect consumer data, select the most appropriate AI tools for their situation, and find ways to integrate AI-based applications into existing systems.
According to the National Retail Federation (NRF), many retailers are interested in leveraging the benefits of AI and are closely monitoring developments. However, they continue to wait to see how the technology evolves and what best practices might emerge. Despite the hesitation, there seems to be no doubt that AI will transform retail.
Challenges and Considerations
Privacy concerns and the cost of implementation are two of the main barriers currently preventing retailers from adopting AI on a larger scale.
Some NRF members have noted that implementation costs remain relatively high, the benefits appear logical but are not yet proven, and may not provide an acceptable return on investment.
Successfully implementing AI in retail also requires significant amounts of data to train algorithms and deliver meaningful results. Convincing consumers to share their valuable personal information requires a high level of trust. Just as Amazon had to convince its early customers to store payment information on the fledgling platform, retailers must reassure their customers that personal information will not be misused.
As retailers and industry organizations work to create a framework for AI in retail, adoption of these technologies is likely to increase.
Future trends
AI will play an important role in improving customer experience in various areas of retail. Early adopters like Germany's largest sparkling wine producer are already using AI to customize the content shoppers see in their stores. The company uses digital signs to display dynamic bottle promotions near the sign and avoid mentioning products that are out of stock.
Related: 3 Reasons AI and In-Store Teams Are a Great Duo for Smoother Retail Operations
While retailers may have different opinions, many share the same goal: eliminating friction in the shopping experience, both in-store and online. Optimizing interactions and customer service through AI is likely part of this evolution. Like other industries exploring the potential of AI, retailers are not looking to replace humans in their stores, but to give their employees more time to do complex tasks.
Whether it's fashion, gadgets, cars or groceries, Americans love shopping, and we're not alone. Personalizing the shopping experience is one of the keys to leveraging this affinity and increasing any retailer's customer base. AI will be one of the driving forces in maximizing personalization and transforming retail as we know it today.
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