How Artificial Intelligence Is Changing Retail

by | Jul 22, 2022

How Artificial Intelligence Is Changing the Retail Landscape

The digital transformation of the retail industry has been going on for years. It has increased speed, efficiency, and accuracy across every branch of retail business. Thanks in large part to advanced data and predictive analytics utilizing artificial intelligence systems that are helping companies make data-driven business decisions.

Few of those insights would be possible without the internet of things (IoT), and most importantly, artificial intelligence. AI in the retail space has empowered businesses with high-level data and information that is leveraged into improved retail operations and new business opportunities.

What Technologies & Solutions Are Used for AI in Retail?

Artificial intelligence is a term that is thrown around quite a bit, but many people don’t fully grasp what it means. When I say AI, I will be referring to a number of technologies, including machine learning and predictive analytics, that can collect, process, and analyze a copious amount of data, and use that information to predict, forecast, inform, and help companies make accurate, data-driven business decisions.

These technologies can even act autonomously, using advanced AI analytical capabilities to convert raw data collected from the IoT and other sources into actionable insights. AI in retail also utilizes behavioral analytics and customer intelligence to create valuable insights about different market demographics and improve many different touchpoints in the customer service sector of business.

So, What Does AI in Retail Even Look Like?

Today’s ever changing retail industry is built on a new idea of data-driven retail experiences and heightened consumer expectations. But delivering a personalized consumer experience at scale is no easy feat for any business. As digital and physical purchasing channels blend together, the retailers that are able to innovate their retail channels will set themselves apart as market leaders. Here are some examples.

  • Inventory Management – AI in retail is creating better demand forecasting. By mining insights from marketplace, consumer, and competitor data, AI business intelligence tools forecast industry shifts and make proactive changes to a company’s marketing, merchandising, and business strategies. This also impacts supply chain planning, as well as pricing and promotional planning.
  • Demand Forecasting – Mining insights from marketplace, consumer, and competitor data, AI business intelligence tools forecast industry shifts and make proactive changes to a company’s marketing, merchandising, and business strategies.
  • Operational Optimization – AI-supported logistics management systems adjust a retailer’s inventory, staffing, distribution, and delivery schemes in real-time to create the most efficient supply and fulfillment chains, while meeting customers’ expectations for high-quality, immediate access and support.
  • Interactive Chat – Building interactive chatbots are a great way to utilize AI technologies while improving customer service and engagement in the retail industry. These bots use AI and machine learning to converse with customers, answer common questions, and direct them to helpful answers and outcomes. In turn, these bots collect valuable customer data that can be used to inform future business decisions.
  • Personalization and Customer Insights – Intelligent retail spaces recognize shoppers and adapt in-store product displays, pricing, and service through biometric recognition.  This reflects customer profiles, loyalty accounts or unlocked rewards and promotions — creating a custom shopping experience for each visitor, at scale. Stores are also using AI and advanced algorithms to understand what a customer might be interested in based on things like demographic data, social media behavior, and purchase patterns. Using this data, they can further improve the shopping experience and personalized service, both online and in stores.
  • Responsive Research and Development – Deep learning algorithms collect and interpret customer feedback and sentiment, as well as purchasing data, to support next-generation product and service designs that better satisfy customer preferences or fulfill unmet needs in the marketplace.
  • Customer Engagement – Using IoT or location enabled technologies to interact with customers, businesses can gain valuable insights on consumer preferences without ever directly interacting with them. For a restaurant group, one of our data and AI specialists created a QR code enabled engagement tool that integrated into their POS system. This allowed guests to not only browse the menu and order, but offered personalized discounts, a loyalty program, and connection points to our sister businesses. This system leveraged consumer data and behavior trends, allowing their businesses to increase engagement and success with customers.
  • Dynamic Outreach – Advanced CRM and marketing systems learn a consumer’s behaviors and preferences through repeated interactions to develop a detailed shopper profile and utilize this information to deliver proactive and personalized outbound marketing — tailored recommendations, rewards, or content.

Why You Need AI in the Retail Industry

Aside from the business intelligence and sheer speed that these technologies can provide, the AI transformation in retail is simply setting successful businesses apart from unsuccessful ones. There are countless benefits that can be credited to artificial intelligence in retail business, but here are five primary ones that retailers can count on.

  • Create Retail Omnichannel – Digital and physical shopping channels typically operate under a different set of initiatives and approaches but treating these channels as distinct business units adds friction for customers seeking a seamless shopping experience and leads to operational inefficiencies.
  • Empower Flexible Logistics Networks – In order to service a wider range of customer demands that are moving from mainstream to niche, retailers need to rethink their traditional supply chain in favor of adaptive and flexible ecosystems that can quickly respond to consumers’ shifting behaviors
  • Gain Insights from Siloed Data – Faced with an onslaught of information from all aspects of their business from supply chain to stores to consumers, retailers need to filter through the noise to transform these disparate data sources into consumer-first strategies.
  • Curate Exciting Experience – To drive continued interest, retailers need to differentiate their products and offer consumers compelling service and experiences. By integrating predictive analytics to gather more market insight, retailers can lead with innovation rather than react to change.

Implementing the systems to support AI in retail can seem overwhelming, but it doesn’t have to be. With Microsoft technology solutions partner like Covenant Technology Partners, you will be supported and guided through every step of the process, even after deployment. Reach out to one of our experts to learn more about how Covenant and Microsoft’s AI 4 Retail can help your business.