6 Ways AI Is Improving the Online Shopping Experience Now

GenAI and other AI tools are at the center of a dynamic conversation about transformation in virtually every digital aspect of life. Because GenAI is so new and still evolving, many of these discussions focus on what lies ahead.

But GenAI and older types of AI are already quietly improving the e-commerce customer experience, with several behind-the-scenes applications making it increasingly easy to find exactly what you’re looking for and get it when you need it. Some of these AI applications are making e-commerce more secure and sustainable—a win-win for consumers and businesses (and the rest of us).

Here’s how AI is already improving shopping—and what’s likely to come next.

1. SMARTER SEARCHES—OR NO NEED TO SEARCH

AI can give shoppers more relevant search results, but it’s faster if you don’t need to search for products to add to your cart. For example, Walmart customers can round up items they want by telling their voice assistant what to add to their carts, without needing to slow down their speech or search for each item.

What’s Next?

The ability to search by use case to get a list of relevant products is likely next. Walmart and Microsoft recently announced a GenAI search tool partnership that will provide lists based on the type of event or project a customer is planning, like “a football watch party” or “a unicorn-themed party for my daughter.”

2. MORE PRECISE PERSONALIZATION

Many retailers already use AI-powered analytics based on third-party and first-party data to personalize offers for customers. Personalization appeals most strongly to Gen Z shoppers. In ClearSale’s most recent international survey of consumer attitudes on e-commerce, fraud, and CX, 20% of Gen Z respondents said personalization is one of the reasons they shop online rather than in-store, the highest percentage of any age group.

What’s Next?

GenAI can create content in real time that matches customers’ interests as they browse and search, enhancing the concept of one-to-one personalization at scale.

3. CUSTOMIZED CUSTOMER SUPPORT

Customer service chatbots have come a long way since the days of pre-set menu options and “I don’t understand” responses. Beauty retailer Sephora adopted NLP-backed conversational chatbots early, driving a trend that’s made it easier for customers to get the information they need from chatbots.

What’s Next?

Virtual store assistants powered by GenAI will let customers get personalized product recommendations and information, reserve items for pick up, get questions answered about product use, return policies, and more. Sephora is already experimenting with this approach to bring in-store experiences online.

4. FASTER, MORE ACCURATE FRAUD PROTECTION

No one wants fraudulent credit card charges, and retailers don’t want the losses that result from e-commerce fraud—an estimated $48 billion in 2023. Leading fraud prevention providers have used AI for years to screen orders for fraud risk and to keep good customers from being rejected by mistake. AI can also help to identify large-scale e-commerce fraud through batch analysis and pattern recognition to spot hijacked accounts.

What’s Next?

GenAI makes it easier for criminals to commit fraud by generating realistic-looking phishing campaigns and exploiting stolen consumer data at scale. However, GenAI also allows fraud detection systems to scan more fraud indicators in real time and detect fraud patterns faster.

5. SUPPLY CHAIN MANAGEMENT

Disruptions during the pandemic showed consumers how fragile the supply chain can be. Since then, many companies have added AI capabilities to improve demand forecasting, procurement, process optimization, and sustainability tracking. These functions can help avoid bottlenecks and waste in the supply chain, so customers get their goods on time and companies conserve resources.

What’s Next? 

GenAI supply chain tools, like Amazon’s Q chatbot embedded in the company’s AWS Supply Chain solution, offer the ability to run risk scenarios for planning and risk mitigation, drawing on real-world data. This capability could reduce supply chain costs, delays, and environmental impacts further than existing AI tools.

6. REINING IN RETURNS

Product returns are a huge problem in e-commerce: About 30% of online clothing orders are sent back, in part because fashion sizes aren’t standardized. Each return represents a disappointing customer experience, added expense for the retailer, and in some cases, new goods going to the landfill.

Some retailers have adopted AI to make the returns process more efficient. AI can identify the causes of returns, find the shortest return-logistics pathways for specific returns, and get more products back on shelves instead of in landfills.

What’s Next?

GenAI gives retailers new tools for preventing the need for returns. Amazon recently announced a suite of new ways to help shoppers find the right clothing sizes on the site in real time, based on “the sizing relationships between brands and their size systems, a product’s reviews and other details, and a customer’s own fit preferences.”

What’s clear in all of these areas is that GenAI is building on the foundation laid by older forms of artificial intelligence and machine learning, but the rate of change may pick up rapidly now that retailers are adopting GenAI. As the technology is trained on more e-commerce data across CX, security, payments, logistics, and more, we can expect to see more innovation emerging faster in this space.

Original article at: https://www.fastcompany.com/91125431/6-ways-ai-is-improving-the-online-shopping-experience-now