Four Ways AI Can Transform the Hospitality Consumer Experience
While the discussion around Artificial Intelligence (AI) has been going on for years, there has been a renewed level of enthusiasm since the introduction of generative AI technologies like ChatGPT.
Across all consumer industries – from hotels to retail to restaurants – the discussions around, and the adoption of, AI show no sign of ending. Many owners and operators have long been using or experimenting with machine learning (ML) to optimize forecasting and pricing, improve inventory placement, and plan merchandising assortments. This movement is accelerating as consumer-facing companies look to improve their margins while still striving to build loyalty and brand affinity with increasingly fickle consumers. Oracle’s consumer-facing industry groups, including retail, food and beverage, and hospitality, are working together to find common ground and build AI solutions for our customers, and for their consumers.
Hotels are in the unique position of serving three types of consumers. Everyone who walks in the front door of a hotel is a guest, but those guests can also be shoppers, browsing through hotels’ retail outlets, as well as diners at hotels’ many food and beverage operations. Whatever their role, consumers in hotels may interact with many types of AI during their stay.
From improving guest experiences to better back-end operations, here are four areas where applied AI can make its mark on consumers and businesses alike.
Elevating guest experiences
Today, consumer-facing companies can use AI to personalize their relationships with customers. Businesses are starting to realize the impact of smart recommendations, and user experiences that remove manual tasks and decision-making. This is particularly true in restaurants and hotels. Whether you’re using AI to predict which offer would best serve a particular customer on a kiosk or to assist a server or reception agent with a mobile device in hand, intelligent and consistent offers can improve check and folio value, as well as customer and staff satisfaction.
AI-driven automation is also helping brands offer more targeted customer service and guest experiences. Hoteliers that implement Oracle Hospitality’s Nor1 can present personalized merchandising offers for room upgrades, attributes like balconies or high floors, and non-room products and services like early check-in, parking, or even food and beverage packages. Guests can interact with these offers from booking through arrival via email, apps, mobile web, messaging, and even in-person. And every offer is selected, ordered, and priced via machine learning in real-time.
In retail and restaurants, AI-powered voice, text, and offer engines are replacing the counter experience, including upselling and service recovery. Additionally, natural language processing continues to improve and allow brands to build an identity unique to their values and deliver it in a way that blurs the line between human interaction and automation—while simultaneously reducing labor requirements in high volume channels like drive thru and phone orders.
However, it’s important for companies to assess the marketplace and deploy technology in a way that elevates the guest experience and doesn’t hinder it. Retail, food and beverage, and hospitality are all industries that need some aspect of the human touch – consumers expect it, and businesses know the human interaction is a vital part of their service delivery. But AI offers automation based on where business owners and operators need it most; this means it’s not AI or humans, it’s AI and humans.
Simplifying operational tasks, refining staffing efficiency
Beyond consumer experiences, businesses across the hospitality and retail industries are integrating AI technologies into their back- and front-end processes. Organizations have turned to AI to streamline workflows, helping to minimize complex or time-consuming efforts and empower employees to allocate more time to value-driven tasks. Simultaneously, AI is expected to revolutionize staffing optimization in the sector by accurately identifying essential skill sets and roles, as well as optimizing operational efficiency in line with the growing industry demand for flexibility in performing various job roles and responsibilities.
Some companies are finding success in using AI tools to assist employees in generating creative content. For example, they may use generative AI tools to help write marketing copy for maximum clickthrough or even create images that can be used as a backdrop.
In addition, spurred by open APIs and plug-in marketplaces, restaurants can test new technologies faster and cheaper than ever before. Where it previously may have taken months for new technology adoption to fail or succeed, brands can now see results in just a few weeks and decide whether to fully adopt that new solution or quickly pivot to another technology.
Optimizing inventory for restaurants and retail
Inventory is the constant scale that restaurateurs and retailers need to balance. An excess of inventory – whether it’s food or shoes – drags down margins. Increased deployment of inventory management and intelligence tools, including automation, AI, and generative AI can help brands gain a better understanding of real-time inventory.
By analyzing customer data, AI can help businesses better understand item affinity, thereby helping operators predict ordering trends and item availability. With self-learning and self-tuning approaches to inventory optimization, these tools provide retailers with integrated capabilities such as embedded forecasting and intelligent pricing capabilities that can continuously provide predictive and prescriptive recommendations on what should be in assortments and how to manage that inventory most effectively.
Retailers, for example, can use responsive, AI-driven inventory management and merchandising systems to optimize margins while having the agility to capitalize on new trends faster - keeping customers happy and coming back for more.
Loyalty
At the heart of this AI revolution is data. Before AI can truly be effective, businesses must integrate all their data across applications and platforms into a common data foundation to increase their ability to derive its full predictive and prescriptive value. As a result, many companies are focusing less on rolling out or altering existing loyalty programs in favor of better understanding the data around each customer and what moves them from a browser to a buyer and builds lasting brand affinity.
By applying generative AI to harness preexisting loyalty program data, such as past ordering behaviors, guest preferences, offer redemption, and shopping preferences (in person, online, or both), operators across restaurants, hotels, and retail can have a better understanding of each consumer to make timely, personalized offers at the right time and place – both online and in-store. For instance, associates armed with mobile point-of-sale systems can easily pull up a customer profile and receive prompts on what that they might be interested in buying next. The information could also be used to create generalized “look-alike segments” by identifying trends in customer behaviors, including regional and location-specific attributes to drive assortment planning and marketing decisions.
Moving forward, companies will continue to seek out technology that can examine large data sets across retail, food and beverage, and hospitality to help them garner actionable data insights, such as understanding how certain actions lead to the next likely outcome and ultimately how to better influence those outcomes. This integration is the next step in the digital transformation of industry and modern AI can help unlock new value and make a significant impact on operations, people, and the bottom line.
Louise Casamento
Vice President of Marketing
+1 443 285 8144
Oracle Hospitality
