In a rapidly evolving retail landscape, staying ahead of the curve is paramount for retailers. Recognizing this fact, many companies are turning to innovative technologies. Artificial Intelligence (AI) is a true game-changer in various industries, and retail/eCommerce is no exception. AI is a powerful transformative tool for this industry, and it is becoming an integral part of how retailers operate, innovate, and meet the changing demands of consumers. 

We are here to talk about specific applications of artificial intelligence. Let’s look at examples of how AI technology can benefit retail businesses.

AI is helping to increase retailer’s revenues by up to 15%. Personalized recommendations, which use AI, account for up to 30% of eCommerce site revenues.

– Barilliance

Demand Forecasting

AI-driven demand forecasting involves analyzing large amounts of data to identify patterns and trends. This data can include historical sales figures, customer behavior metrics, market trends, seasonal influences, and even external factors such as economic indicators or weather patterns. Based on this information, AI models can predict future product demand with a high degree of accuracy.

Well-known companies use artificial intelligence to forecast demand. Let’s take a look at the most successful examples of AI applications.

  • Walmart utilizes AI to process data from its over 11,000 stores to predict demand for over 500 million items. 
  • Amazon employs AI-driven algorithms for its Amazon Fresh. Algorithms analyze customer purchasing habits, seasonality, and other market trends.
  • Starbucks leverages AI for itsDeep Brew program. This system considers weather, community events, and historical data to predict the required inventory and staff levels.
  • H&M, with AI, can analyze store returns, receipts, and data from loyalty cards. This information helps them understand what products are popular and in which locations.

And, of course, the perfect image of utilizing AI in retail is Nike and its AI start-up Celect. This technology integrates complex algorithms that analyze various data points – from purchasing patterns to social media trends – to predict consumer demand more accurately. 

AI-enadbled demand forecasting
AI-based demand forecasting in Sybilla by

For Nike, implementing Celect has marked a significant shift in its approach to product distribution. Traditionally, demand forecasting in retail has been challenging, often resulting in surplus inventory or stock shortages. With Celect, Nike can optimize its inventory levels by accurately predicting which products will be in demand at specific locations and times. This targeted approach ensures that the right products are available at the right places and reduces the costs associated with overstocking or understocking.

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Personalized Recommendations

The following AI application we are looking at is personalized recommendations. Perhaps the most well-known example is Amazon. It uses AI algorithms to analyze customer purchase history, search queries, and browsing habits to suggest products that customers are likely to buy. 

AI-driven personalized recommendations can transform retail significantly. Let’s talk about what goals can be achieved.

  • Understanding customer behavior.
  • Tailoring product suggestions.
  • Enhancing customer engagement.
  • Forecasting future buying behavior based on past actions.
  • Providing a seamless and consistent personalized experience.
  • Building trustworthy relationships with customers.
  • Optimizing inventory management.
  • Boosting sales and revenue.

Some retailers’ AI systems can analyze customer data in real-time, adjusting recommendations instantly as the customer browses or interacts with products online or in-store. 

For example, Zara integrates AI technologies into its online and brick-and-mortar stores. In Zara’s online platform, AI algorithms track customer interactions: items they view, time spent on each product page, and so on. With this data, the AI system adjusts the product recommendations for each customer in real-time. 

AI-based recommendation in ecommerce

Conversational Chatbots

It is vital to provide expert advice to customers in the retail sector. It doesn’t matter what the specifics of your business are. In any case, you must ensure effective communication with the target audience. AI-driven conversational chatbots can help you in this case. You can use them instead of consultants. This solution is cost-effective, convenient, and profitable.

Chatbots can understand human language, whether typed or spoken. When a customer initiates a conversation, the chatbot processes the input, recognizes the intent behind the query, and responds accordingly. H&M is one of the companies that successfully implemented chatbots. It assists shoppers by answering questions about product availability, sizes, and store locations. 

AI-based intelligent chatbot for ecommerce
eCommerce chatbot by

Customer Behavior Analysis

AI algorithms can sift through vast amounts of data. Analyzing past purchases, browsing patterns, and even social media interactions, AI helps retailers understand what drives customer decisions. Deep analysis enables more effective targeting of products and marketing efforts. It ensures that the retailer’s offer aligns closely with customer desires and trends. 

Manual Process Automation

AI systems are adept at handling repetitive tasks such as inventory management, checkout processes, or customer service inquiries. It reduces the likelihood of human error. Staff can focus on more complex tasks. Such automation optimizes backend processes. 

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Reporting and Predictive Analytics

AI tools can analyze extensive data sets and generate insightful reports. So you can get a comprehensive view of business performance and customer behaviors. Beyond reporting, AI applies predictive analytics to forecast future trends, helping retailers make informed decisions. For example, Starbucks employs AI to analyze data from its global coffeehouse chain. The goal is to predict customer behavior and preferences with high accuracy. 

AI-based reporting in eCommerce and Retail

Fraud Detection and Prevention

We often encounter cases of fraud and money manipulation. Unauthorized access to accounts and leakage of confidential information are the most common, but not the only, problems of companies. Artificial intelligence plays a crucial role in fraud detection and prevention in retail. AI systems analyze transaction data in real-time, looking for patterns and anomalies that may indicate fraudulent activity. 

Here are a few examples to illustrate this AI application. PayPal uses AI to analyze billions of transactions. Its system examines each transaction across numerous data points, rapidly identifying and flagging potentially fraudulent activity. Amazon uses AI to track and analyze patterns, identifying interconnected fraudulent activities and accounts.

AI and ML in fraud detection
How is artificial intelligence used in fraud detection? Source:

How is AI Used in Supermarkets?

Let’s recall the typical inconveniences of supermarkets. Long queues at checkouts, expired products, and ineffective staff interaction due to poor communication are the most frequent and pervasive. Supermarkets can use AI to enhance efficiency, customer experience, and business operations. For what purposes can you use AI in your supermarket?

  • Smart inventory management.
  • Checkout-free shopping.
  • Personalized marketing.
  • Food quality control.
  • Waste management.
  • Customer behavior analysis.

For example, Walmart uses AI to track inventory and predict stock needs, reducing overstock and shortages. Amazon Go stores offer a checkout-free shopping experience. AI and sensors track what items customers pick up, automatically charging them as they leave the store without needing to stand in a checkout line. 

The Future of AI in Retail

After analyzing the artificial intelligence applications, it becomes clear that the future of AI in retail promises to bring many new opportunities. You cannot wait any longer and ignore the importance of using this innovative technology in your business. 

So, what are the key developments expected in the coming years?

  • Deeper personalization in retail.
  • Highly tailored shopping experience for customers.
  • Seamless integration across online and offline channels.
  • Autonomous, checkout-free store formats.
  • More informed business decisions.
  • AI-powered customer service (AI chatbots and virtual assistants).
  • More intelligent and efficient supply chains.
  • Dynamic pricing strategies.

The possibilities of using AI in eCommerce and retail tomorrow point towards a future where shopping experiences are more personalized, operations are more efficient, and decision-making is increasingly data-driven. AI is set to revolutionize the retail landscape. The technology can offer unprecedented levels of customer service and operational insights. 

Let our experience help you realize the potential of AI solutions for your business. We are ready to be your trusted technology partner. Contact us and tell us more about your needs!

Andrii Sydoruk
Andrii Sydoruk CEO, Managing Partner at SmartTek Solutions