The presence of Artificial Intelligence (or simply AI) in retail is no secret—more and more companies are finding their second wind thanks to intelligent software and machine learning processes. The benefits of this transition can vary between industries, but retailers generally enjoy more consistent profits, better client outreach, and improved market flexibility thanks to AI tools. As a whole, AI is revolutionizing the way many companies approach their business processes.
1. Optimal Price Points
The demand for most products fluctuates throughout the year and can do so for a few reasons. First, and perhaps most obvious, is when a product is “getting old”—there won’t be as much demand for an older version of the iPhone, for example. Alternatively, a drop in demand could be related to the product’s seasonality; it’d be hard to sell a winter coat in the summer. Changing consumer expectations or a price drop in competing products can also have an impact. Whatever it may be, it’s important to recognize demand fluctuations quickly and deal with them effectively.
Ideally, a retailer would want to keep sales, and thus demand, consistent throughout a product’s lifetime. Figuring out the price at which a product’s demand remains at a relatively high level—the price point—is key for consistent sales and maximized profit. As you might’ve guessed, AI tools are very powerful in this regard, as they can analyze and adapt to effectively “learn” the optimal prices at a given point.
2. Effective Product Recommendations
Anyone that’s shopped on Amazon has probably seen the “customers also bought” or “frequently bought together” sections of a product’s page. The power of these recommendations can’t be understated—according to a 2018 survey, over 70% of Millenial and Gen Z consumers are likely to make a purchase based on a recommendation.
It probably comes as no surprise that AI is a big component of these suggestions for many, if not most, online retailers. With the volume of customer data available, a machine learning tool that can make sense of and draw patterns from it all can really propel an e-commerce business. Essentially, the “customers also bought” items are a representation of the AI figuring out the good recommendations based on previous buyers of the product and any similar to it.
3. Personalized Marketing
For a lot of people, ads are an unavoidable nuisance; they pop up all over web pages and in some cases interrupt your online content for a few seconds. Regardless, online advertising has become a lot less of a guessing game in recent years. Before, retailers would throw out a wide net to try to catch as many potential customers with a marketing campaign. Nowadays, with the power of AI, many retailers can afford to wait for consumers to flock to them thanks to targeted advertising.
Like with recommendations, AI tools can learn what to market to your demographic or even to you personally. If your search history suggests you’re in the market for new headphones, you might just see an ad for headphones next time you’re browsing Facebook. While these targeted ads might seem a bit creepy to a lot of people, it’s a much more effective way to make sure your product is seen by people who care about it.
4. Automated Customer Service
Chatbots are becoming more common in recent times, and for good reason. Automated customer support is already fairly established, and is certainly more convenient for consumers than filling out a “Contact Us” form. However, AI is creeping its way into this medium as well, with a few implementations already impressing customers.
Launched just a year ago, Lidl’s chatbot Margot offers shoppers wine advice based on any constraints they might have. Perhaps the most impressive aspect of this bot is its ability to talk to customers in natural language rather than through buttons and commands. Margot can offer recommendations according to the shopper’s budget and taste, and even suggest wine pairings.
There are a few other AI chatbots in the retail sphere, notably those that can help you pick out clothes based on descriptions. Whatever the implementation, automated customer service makes shopping far more convenient, and AI elevates that convenience to another level.
5. Visual Assistance
Visual searching and augmented reality are two key components of a push towards integrated visual assistance in retail. While these technologies are still far from being commonplace, its implementation is inevitable; 62% of the Millenial and Gen Z consumers surveyed ranked visual search as the technology they want to see most. While the machine learning technology itself does exist, there’s no guarantee that every customer’s search will be understood accurately.
Visual searching is essentially an image-based search of a retailer’s stock—the customer gives a photo example, and the AI returns the product results it deems accurate. A few companies (Walmart, for example), are already experimenting with this technology. On the other hand, Ikea offers a similar experience through an augmented reality app, wherein you can input your home’s dimensions to see how certain furniture will fit or look. Whenever visual assistance does become a common theme in retail, it’s bound to make online shopping even easier.