Artificial intelligence continues to be one of those topics that permeates every single industry event in some capacity. At the same time, it remains a topic that independent retailers – and professionals from nearly every other industry, for that matter – can’t quite sink their teeth into from a practical standpoint. I think we “get” AI, without really getting AI.

The disconnect, which became apparent during a recent panel discussion at the 2024 Furniture Today Leadership Conference, has to do with our approach to every discussion around the topic. When you talk about AI with a retailer, it seems to be this lofty, up-in-the-sky idea that doesn’t directly impact their business. The other sense I get is that many people still view AI as a convoluted technology that’s just so far outside of our understanding that we simply refuse to take the time to actually understand it and the impacts it can have on every facet of one’s business.

One simple adjustment, suggested by panelist Ziv Fass, CEO of Package.ai, is to start thinking about AI as software rather than this “all knowing system” that’s going to make decisions for you.

Additionally, the panel collectively agreed that the best way to approach implementing any form of AI into one’s business is by taking baby steps. Find one area of your business that you’re hoping to streamline or improve and see if there’s a system or software out there that can help you accomplish your goals. Change can and should come quick, the panelists agreed. Meaning, if at any point you find yourself frustrated or ultimately wasting more time than it’s likely not a good fit, and you should move on.

All of that said, we’ve really only talked about how to approach or think about AI to this point. What, then, are some of the practical ways that you can use some of these tools in your business right now? (Glad you asked.)

Marketing and Advertising

This is the area that most retailers we talk to say they are leaning into the most and realizing the most return on their investment with AI. These tools are great for helping to lay the foundation for your marketing and advertising messaging. Some high-level prompts plugged into a platform like ChatGPT are great, but the capabilities go so far beyond that as well.

From a cost-savings standpoint, tools like image generation are a great way to take a simple photo of a couch and change the color or place it in a living room setting, all without having to have that couch in a different color or actually move it into a new environment or hire a professional photographer to stage things and take those photos and touch them up. (We heard from Hamza Bennis, co-founder of Presti AI, on this panel. His is a tool designed specifically for the furniture industry that does just that with simple photos.)

Predictive Analytics

One of the most underrated and least talked about aspects of AI – at least in our space – is its ability to crunch data and provide predictive analysis in a matter of seconds. These tools are capable of running tasks that would otherwise take hours, or days, or longer, and give you the information you need to act on much quicker.

Fass explained it like this: AI has the ability to eliminate “data islands” – these buckets of information that exist exclusive of one another. By plugging, say, your historical purchasing data into a tool, you can cross reference it with things like weather trends, migration data, or any other possible data sources you’d want to try to plug in. And, rather than digging through sheets and trying to make sense of these different buckets of information, the AI software can do that for you and provide instantaneous analysis that you can then use to make informed purchasing decisions.

Understandably, there’s concern around plugging your data into an AI platform and the perceived vulnerabilities with your proprietary information. The key to this is understanding the difference between closed AI and open AI platforms. A closed model – which is what you’d want to use in this instance – is one that doesn’t plug into public sources or share out information for others using that platform. Open AI is just the opposite, it’s using data inputs to constantly learn, evolve, and improve. Simply put, in a closed AI model, your data is safe and secure.

Chatbots and Virtual Assistants

Another popular use case for AI in the retail sphere is with website chatbots and virtual assistants. It’s cliché at this point, but no matter what your physical store hours are, the lights to your virtual location, your website, are always on. Utilizing on-site AI can help by enhancing that customer experience.

These virtual assistants can work to answer questions about the features of a product, provide order status and tracking updates, offer personalized product recommendations based on a customer’s browsing patterns, and so much more – and it works for you 24/7. When implemented properly, they can really help to convert leads and drive business.

Personalization

Though already mentioned above in different formats, personalization through AI is worth calling out on its own, because it can truly create a unique experience for your customer. By capturing and analyzing all kinds of data and information about how a shopper engages with your website, you can build incredibly detailed and unique customer segments that allow you to better target and market to your customers.

Every click can lead to you better understanding shopper intent on your website and at your store, which can result in personalized product recommendations, custom email campaigns for an item that a customer was researching, unique offers to drive them back to your store – and, ultimately, an appreciation for the meaningful messaging that results in a more loyal customer.

Are you leveraging AI in your business in any way? Let us know at pr@nmg.org.