Exploring AI in Retail: Essential Use Cases, Common Challenges, and What’s Next

To stay competitive in a global economy, retailers need to pivot quickly and effectively. Artificial intelligence (AI) provides support to retail storefronts and ecommerce platforms, transforming their operations through personalized customer service, automated business processes, and actionable insights. In fact, AI in the retail industry has been predicted to reach $85 billion by 2032—this indicates the pace at which the technology is being adopted by retailers.

We all know how integral personalization is to the success of retail operations. Technology-savvy customers demand experiences that are instant, tailored, and seamless. AI opens the doors for retailers to meet these expectations. Its capabilities to comprehend customer preferences allow retailers to customize their services as required. In addition, retailers face several challenges in the form of geopolitical upheaval, climate crisis, and more. AI-enabled analytics arms businesses with the ability to forecast the twists and turns of the marketplace and fine-tune their strategies in response.

In this blog, we’ll discuss the many ways in which AI can deliver substantial value to the retail industry. We’ll also explore how AI may impact the sector going forward.

Applications of Artificial Intelligence in Retail Industry: 5 Essential Use Cases

For both brick-and-mortar and online retailers, there are several opportunities to incorporate AI into day-to-day operations. Here are some of ways retail players can apply AI to realize tangible value.

1. Personalized Shopping Experiences

AI algorithms analyze the preferences and purchase history of every customer. This allows retailers to create highly engaging, personalized shopping experiences where every aspect of the interaction is tailored to individual needs. Recommendation engines, which suggest products based on a user’s historical search and browsing behavior, have also become commonplace in online retail. Increased personalization leads to enhanced conversion and retention.

Many ecommerce brands, including Amazon, customize product costs through dynamic pricing to lure customers. In dynamic pricing, retailers adjust prices in real time by taking into account product demand, user preferences, and competitor pricing. This enables them to boost sales during low-traffic periods by offering discounts to customers who may not convert otherwise.

2. Demand Forecasting

A few years back, retail establishments relied solely on past data and intuition to forecast product demand. Not any longer. Today, advanced machine learning models utilize multiple variables including customer data, historical sales data, and seasonal trends to predict future demand. These models tend to be highly accurate, as they process large swathes of data and decipher trends and patterns conventional forecasting tools might miss. The result? Retailers have the right product in their inventory at the right time.

Plus, they are better prepared to deal with unforeseen events such as shortages or economic slowdowns. In short, data-driven insights help retailers avoid scenarios of overproduction or underproduction while effortlessly meeting customer demands.

3. Supply Chain Management

AI can be incorporated into different functions of the supply chain such as supplier management or transportation to optimize stock levels, increase efficiency, and minimize errors. For instance, AI-powered solutions assist retailers with route optimization, i.e., finding the most cost-effective routes for their drivers.

AI models calculate the most optimal routes in each scenario for swift, cost-efficient product delivery. These models also allow the stakeholders to respond to last-minute changes to delivery schedules and update their route plans whenever needed. This speeds up operations while ensuring customer satisfaction and reducing fuel costs.

4. Enhanced Customer Service

AI-driven virtual assistants provide timely support to customers, address issues, and fast-track the ordering process. Using techniques such as generative AI and natural language processing, retail businesses develop chatbots that understand the context of a conversation and deliver human-like responses. For example, bots help customers visiting an ecommerce app or website find a specific product or navigate through their offerings.

Additionally, retailers combine augmented reality with AI to let customers research products and find exactly what they are seeking. This is particularly useful for home decor and beauty brands where users have the option to see how a specific product might look before committing to a purchase.

5. Loss Prevention

Preventing inventory loss due to employee and external theft is a perennial challenge for any retailer. It has been found that retail companies lose an estimated $122.1 billion annually because of theft. AI-driven video analytics allow intelligent surveillance that goes far beyond traditional recording. With real-time analysis of video footage, it flags any unusual or suspicious activity. This minimizes the incidence of vandalism or shoplifting.

AI-based systems also help in identifying behavioral patterns indicative of theft. For instance, if an individual is found lingering near a high-value item in an outlet, an alert may be triggered, and the security teams may intervene to take appropriate action.

AI may also be used to spot fraudulent activity during checkouts. AI-based systems process video feeds to pinpoint anomalous user behavior such as hiding merchandise or misusing coupons. Additionally, AI is used along with radio frequency identification (RFID) to track in-store inventory. So, if there is a discrepancy between the recorded and actual inventory levels, the staff gets alerted.

Implementing Artificial Intelligence in Retail Industry: Challenges and Best Practices to Overcome Them

While AI solutions in retail offers avenues to business owners to improve operations, their implementation is no easy undertaking. Adopting and implementing AI requires retailers to address certain challenges.

I. Reluctance to Change

Many believe AI-based solutions displace human workers and take over their jobs. That’s why most retail organizations struggle to incorporate AI into their existing processes. To overcome the hurdle, business owners should engage with their workforce early on and communicate how virtual assistants or automated workflows may help ease their workloads. It’s also vital to come up with realistic use cases of the technology to ensure better buy-in.

II. Inadequate ROI

All too often, retail businesses implementing AI for the first time fail to see any tangible outcomes. This is primarily due to the high cost of resources spent on implementing AI initiatives. Besides, several companies jump headfirst into adopting AI with no clear strategy in place.

Before implementing AI, it’s essential to identify use cases where AI can bring a perceptible difference. Retailers should ideally start with a pilot project that validates the effectiveness of an AI solution and scale up gradually if significant improvements are seen.

III. Poor Quality Data

To get valuable insights from AI-driven solutions, it’s vital to have accurate, relevant, and up-to-date data. To ensure a steady flow of high-quality data, retailers should enforce stringent data governance practices. The latter involves defining data standards, implementing data validation, and auditing datasets regularly. Additionally, tools should be put in place to continually monitor data quality and promptly address anomalies, if any. Retail businesses may also consider purchasing third-party data to fortify their existing databases if the need arises.

IV. Skill Gap

AI is a rapidly evolving space seeing new developments now and then. As a result, it becomes difficult to hire AI talent with the requisite skill set. Retail businesses should address this gap by investing in training programs to upskill their workforce. Online courses and workshops may be organized to allow people to learn AI skills. Additionally, retail organizations may collaborate with technical schools and universities to attract individuals with the required expertise.

V. Customer Adoption

The idea of interacting with chatbots may not excite every customer. In many situations, they want to connect only with a human representative to talk about their concerns. To mitigate such challenges, retailers should strive to clearly communicate the benefits of AI to their user base. To foster trust, they should make their customers learn how their AI application works. Customers should also be encouraged to provide feedback on these applications from time to time. This way, retail businesses can make necessary adjustments to their solutions, increasing their acceptability among users.

VI. Integration with Existing Systems

Integrating AI solutions into their existing systems can be cumbersome for many retail businesses. Without proper compatibility with the current infrastructure, AI solutions may not deliver the expected returns. To overcome this challenge, retail organizations should consider partnering with vendors having experience in the retail industry. Their capabilities will help retailers build custom APIs or third-party platforms that enable seamless AI integration.

Future of AI in Retail: What’s Next

AI has the potential to transform nearly every facet of the retail industry. Here are a few developments we should expect in the days to come:

• Focus on Hyper Personalization: Today, retail businesses are going beyond just the past purchasing history of a customer. They are gathering real-time data from a broad array of sources (e.g., in-app behavior, engagement data, and browsing behavior) to personalize an individual’s experience at every step of their journey. Additionally, several top retailers use a combination of online and offline data to provide an integrated, omnichannel user experience.
• Robotics: AI-powered robots are increasingly used in retail stores to enhance operations and offer superior customer service. Robotic kiosks help customers find specific items in a store and restock shelves whenever required. In addition, retail companies deploy robots in warehouses to pick, classify, and pack products intended for shipping.
• Augmented Reality (AR): Augmented reality creates immersive shopping experiences for customers from the convenience of their homes. For instance, virtual fitting rooms allow individuals to understand what kind of clothing will suit their body type. Likewise, 3D virtualizations display how a piece of furniture or home decor product will fit into their living spaces.
• Automated Checkouts: Picture a scenario where a customer steps into a retail outlet, buys what they need, and walks out without requiring to stand in a queue to make the payment. Cashier-less stores enabled by AI have made this possible. Today, customers can buy items without the need to go through a conventional checkout process involving human cashiers. AI-powered cameras and sensors track the products picked up by a customer. This way, they are charged automatically when they leave the store after completing their purchase.
• Smart Stores: Retail players are increasingly building ‘smart stores’ by intelligently leveraging AI along with sensors, the Internet of Things (IoT), and Radio-Frequency Identification (RFID). AI systems help retailers get a better sense of foot traffic in their stores. These systems pinpoint items most customers don’t linger near or purchase, so that these may be replaced with more frequently bought products.

  AI-based solutions also help retailers cluster products that are often purchased together. As a result, customers spend much less time searching for what they may need. Additionally, AI may also assist with targeted promotion of specific products on customers’ smartphones when they are browsing items while walking through the store.

• Visual Search: Typing a query into a retail app or website isn’t the only way users search for products these days. As online search continues to evolve, visual search methods are becoming mainstream. Here, users look for information by simply uploading an image or screenshot of a product. This way, they are able to find visually similar products and explore a broader range of options they may have missed through text-based searches. Visual search thus simplifies the discovery and purchase of products, leading to effortless conversions.

Leverage the Capabilities of AI in Retail to Drive Success

The retail industry is steadily expanding its horizons, thanks to AI and other similar technologies. With its ability to analyze large volumes of data, AI enables retail organizations to understand customer preferences and market trends. By strategically incorporating AI into their operations, retailers improve customer experiences and work with enhanced efficiency. In the long run, this translates into higher revenue and profitability.

Implementing solutions to support AI in retail, however, can be overwhelming. Technology providers such as Damco help retail companies overcome the challenges of adopting AI. Damco’s AI experts devise well-thought-out solutions to empower retailers. Our solutions allow retail organizations to optimize various aspects of their business—pricing, product assortment, store layouts, demand forecasting, and more. This helps them boost profit margins and win more customers in competitive markets.