There’s a lot more to being a successful retailer these days than moving product off your shelves. Competition is fierce, with brands constantly innovating new shopping experiences, marketing campaigns, and ways to interact with customers. Add to that the growing influence of digital natives like Amazon and Allbirds in the brick-and-mortar realm, and traditional retailers have themselves a challenging puzzle to solve: Namely, how to stay relevant in this digital-first consumer culture.
Many brands have zeroed in on their online shopping platforms in order to meet and hopefully exceed these changing customer expectations. The new gold standard is becoming truly ‘omnichannel’ – in other words, having a brand that extends its digital fluency beyond the e-commerce platform and into its stores, using technology to elevate the in-person experience. These efforts have manifested in sophisticated mobile apps, geotargeting technology, and even “smart” fitting rooms.
The technology behind a large number of these omnichannel innovations? It’s a term you’re probably sick of hearing about, but that’s only because it’s important. Artificial intelligence (AI) is taking retail to new heights, and experts predict the technology will continue to surge over the next several years: Juniper Research predicts that retailers will spend $7.3 billion on AI by 2022 (compared to $2 billion spent in 2018).
Like it or not, AI is here to stay and it’s worth understanding how major brands are implementing the technology within their operational infrastructure. Read on to learn more about AI and its potential long-term impact on retail.
What is Artificial Intelligence?
Whether you’re totally new to the world of AI or you’re a seasoned vet, it’s easy to get thrown off by the huge variety of applications and functions the technology has in today’s commercial sector. In fact, the Brookings Institution has deemed AI one of the most misunderstood terms amongst business leaders.
So, what is it, really? Merriam Webster defines AI as “a branch of computer science dealing with the simulation of intelligent behavior in computers.” You might be thinking robots – and yes, they’re relevant – but AI has more to do with algorithms at its core. It’s an intricate modeling system that relies on immense quantities of data (historical and real-time). And it’s capable of sorting through, interpreting, and deriving actionable insights from this data in a way that mimics human cognition.
These capabilities are transforming business functions and operations across industries, including retail and retail facilities management. AI can be applied across both micro- and macro-level use cases in retail operations – everything from asset maintenance and work order approval (on the FM side) to inventory management, marketing execution, promotional planning, and the in-store customer experience.
It’s important to note that AI encompasses several other complex, algorithm-powered technologies, such as machine learning (ML), deep learning, natural language processing (NLP), robotics, and others. Want to learn more about ML specifically? Read How Machine Learning Benefits Facilities Management.
How AI is Being Implemented by Retailers
Retail executives are starting to pay more attention to AI, and rightly so. McKinsey estimates that by 2030, AI-powered technologies will deliver $13 trillion in additional economic output around the globe. For a little perspective on this figure, note that the entire value of U.S. commercial real estate is estimated at approximately $15 trillion.
It’s more than “keeping up with the Joneses.” Investing in AI offers traditional retailers a level of insight into their brick-and-mortar operations that they’ve never before had access to, making it easier to spot weaknesses or opportunities for improvement. It allows them to turn around the gloom-and-doom headlines about the (nonexistent) “retail apocalypse” and make their physical spaces a competitive advantage rather than a detriment.
Perhaps more importantly, AI-driven tech is forging the path towards hyper-personalization, something that today’s consumers value immensely in their shopping experience. When brands begin to anticipate their customers’ needs and use data to learn about how and when they prefer to shop, they graduate to a whole new level of customer satisfaction. This is especially true when digital and physical modes of shopping are interconnected, creating a seamless, interactive experience.
AI has the potential to massively alter brick-and-mortar retail for the better – and it’s already yielding return on investment for a large number of brands. Let’s take a look at a few use cases.
Interactive Shopping Experiences
Shoppers visit brick-and-mortar stores so they can get up close and personal with the product and brand, exploring, touching, and trying on merchandise before making a purchase. There’s intrinsic excitement to this process – but when AI is used to heighten the in-store experience, retailers can create an even more memorable encounter that increases the likelihood for continued engagement.
Some examples of these customer-facing, AI-driven technologies include in-store navigation services, cashierless checkout, augmented reality (AR) tech for virtual “try-ons,” and even virtual shopping assistants available via customers’ mobile devices.
The shared goal behind each of these offerings is to make the shopping process simpler and more enjoyable. This is to say, brands aren’t using AI to snag a quick sale. They’re investing in these technologies in order to retain loyal customers for the long term – while simultaneously leveraging the marketing buzz that often comes along with new and exciting tech.
Sephora has seen great success with its machine-learning-driven Color IQ platform, which scans the surface of a visitor’s skin to provide a personalized foundation and concealer shade recommendation. The brand’s AR tool, Sephora Virtual Artist, is an equally engaging in-store feature that scans shoppers’ faces and allows them to test products and experiment with the latest beauty trends without touching a single sponge, brush, or wand (though this is, of course, still an option).
As we’ve touched on in prior blog posts, AI has a tremendous amount of potential for retail facilities management, and AI-powered technology is already available in a variety of iterations to FM professionals. These range from advanced work order management and preventive maintenance scheduling software to smart energy consumption and space utilization technology.
The simple ability of AI to make data-backed decisions is one of its most powerful functions for FM operations. Rather than making a gut decision on whether or not to replace an asset, how much to pay for a particular service, or how often to perform preventive maintenance, ML-powered algorithms (such as those harnessed in ServiceChannel’s Decision Engine technology) are able to quickly assess a wealth of historical data and suggest the best course of action. This eliminates user error and allows retailers to more easily keep stores up and running while sticking to tight R&M budgets.
Investing in AI-enabled service automation software is an excellent way to test the proverbial waters without a whole lot of risk. There are, however, many other AI-driven FM technologies that stand to significantly benefit retailers of all sizes once further developed and refined. Walmart, for example, has already employed self-driving robotic floor scrubbers in a multi-million dollar play to cut costs and optimize operations at more than 1,500 of its locations across the United States.
Energy management is another promising arena for AI, with smart buildings cropping up around the globe that feature sustainable, “intelligent” thermostats that learn inhabitants’ schedules and preferences over time. Retail FMs should take note; while some of these technologies are currently being marketed for consumer use, we’re sure to see more energy-optimizing gadgets and software making an appearance in retail spaces.
Demand Forecasting & Inventory Control
According to the same report prepared by Juniper Research, 16 percent of retail spending on AI by 2022 will be put towards demand forecasting. This makes perfect sense, being that one of the key benefits of AI integration is its capacity for advanced predictive modeling. With AI-driven predictive analytics in play, businesses are able make data-backed decisions around spend and perform sophisticated inventory and supply chain control.
An AI-enabled platform produces standardized, easily scalable performance benchmarks that take into account local economic variations and other confounding factors. These benchmarks are difficult – if not impossible – to produce without technology. And they make a big impact on businesses with narrow margins (something that many of today’s top retailers contend with).
Major grocers Target and Whole Foods have already begun to integrate AI and ML to streamline their supply chain and fulfillment system, driving towards an “order-to-shelf” model that allows items to be restocked almost as soon as they leave the shelves. Meanwhile, multinational retailer H&M has turned to AI and big data to analyze store receipts and returns, making it easier to analyze purchasing patterns across locations and to restock inventory appropriately.
Eventually, we may see more businesses operating without storage rooms or warehouses. If demand forecasting becomes accurate enough, it will be possible for stores to generate an exact count of the number of items that need restocking – and then place an order with the supplier at exactly the right moment. Even if these back-end processes aren’t immediately evident to shoppers, fully stocked shelves will be. It all circles back to the in-store customer experience: Stores that master demand generation with AI-enabled technology will be better prepared to face the next retail revolution.
If there were ever a time to invest in AI technology, this is it. The maturity of the market for AI in retail is close to its peak, having moved past the hype and into a new phase of showing, proving and yielding ROI.
With its advanced predictive and decision-making capabilities, AI-enabled software has the power to completely transform retail store operations, marketing, and customer experience. This is, of course, heavily dependent on the quality and quantity of data at your fingertips. Corporations must continue to invest in data infrastructure that can not only handle AI technology, but can also host the array of APIs needed to string data together to train and feed algorithms.
Brick-and-mortar retail is far from dead, and the smartest brands will capitalize on their physical assets in order to meet customers anywhere and everywhere. Sophisticated store operations – including maintenance and facilities management – is going to become even more critical as customers expect to move seamlessly from digital to in-person shopping experiences. Even if the initial investment seems daunting, the insights and efficiencies gained from AI-enabled software and technology will more than likely pay for themselves in the long run.
Ready to embrace digital transformation within your retail FM program? Schedule a demo with the #1 facilities management platform.