The Rise of AI in Retail Industry: Enhancing Customer Experience and Boosting Sales

Are you ready for the future of retail? Artificial Intelligence (AI) is revolutionizing the industry, offering retailers powerful tools to enhance the customer experience and drive sales. From personalized shopping experiences and chatbots that provide customer service, to computer vision that optimizes brick-and-mortar store layouts and product placement, the potential applications of AI in retail are staggering.

In this article, we’ll explore how AI is transforming the retail industry, the technologies and solutions being used, and the emerging trends that will shape the future of retail. Whether you’re a retailer, consumer, or simply interested in the future of shopping, this is an exciting time to be part of the retail industry. So, let’s dive in and explore the rise of AI in retail!

TL;DR

• AI is transforming the retail industry by enhancing customer experiences, streamlining processes, and boosting sales, resulting in a more customer-focused and data-driven approach to business operations.

• Key AI technologies in retail include computer vision for virtual fitting rooms, recommendation engines for personalized suggestions, predictive analytics for better inventory management, dynamic pricing for optimized revenue, and natural language processing for improved customer service.

• AI applications in retail cover a wide range of areas, such as personalized shopping experiences, chatbots and virtual assistants for customer service, AI-powered recommendation engines, predictive analytics for inventory management, AI-powered visual search and product discovery, smart shelves and product tracking, and augmented reality for in-store experiences.

• Emerging AI technologies help retailers understand their customers better by processing valuable customer data, optimize processes using machine learning to identify inefficiencies, and provide opportunities for automation, allowing employees to focus on more demanding tasks.

• Stay ahead of the competition and enhance your retail business with AI solutions tailored to your needs. Contact nexocode AI experts today for professional insights and innovative solutions.

The Potential of Artificial Intelligence to Transform the Retail Industry

Can you remember when you actually had to know what to buy and where? When the prices wouldn’t change for months, the items would be only available on the particular store’s website, and if you wanted a refund, you had to go to the physical store. These standard aspects of retail changed radically, mainly thanks to artificial intelligence. 

While fuelling the profit for retailers, AI also makes customer’s life easier, facilitating purchases and providing them with bargain options. It brought online shopping to a new level, allowing brands to gain worldwide recognition without opening up a physical store in various locations and reach different targets that would otherwise remain unreachable. At the same time, it permanently changed our habits, getting us accustomed to recommendations and online shopping procedures, including delivery. All while using these habits to maximize the probability of the purchase.

It’s just the beginning of that process, which accelerated during the pandemic and hasn’t stopped gaining momentum ever since. In the future, AI will continue shaping retail, not only in terms of online but also offline experiences. Here’s our recap of the most captivating applications of AI in both these areas.

Technologies & Solutions Used for AI in Retail

While you may associate AI in retail mainly with dynamic pricing, its innovative potential reaches various other areas. The technologies below transform the online and offline shopping experience, allowing users to buy whatever they like, wherever they like, at a favorable price and ensure the purchase matches their needs 100%.

Computer Vision

Apart from streamlining supply chain operations, which results in faster delivery, computer vision can also impact the way we shop and increase the expansion of the online retail sector. It is already revolutionizing the online customer experience in the clothing sector, removing the ultimate barrier for online shopping skeptics - how will I look wearing that? 

In the virtual fitting rooms, the customers can try on the clothes after the webcam scans their bodies to create the 3d 360 degrees models. That process involves computer-vision-based AR technology, a branch of AI providing immersive experiences. Similar computer-based solutions are used by hair and makeup companies, enabling customers to check virtually what’s their best fit. 

Recommendation Engines

Today, recommendation engines are everywhere, suggesting us all kinds of content - from music, through social media posts, to retail items - based on our personal data and behavioral patterns. While they make our life easier (or the opposite, depending on how you put it, as they may make you spend much more than you planned), for retailers, they are a true goldmine. Since the algorithms can understand what you like and recommend it to you, the probability of the purchase goes much higher. 

There’s more to it - the retailers can also feed the recommendation engines with data on your personal habits to maximize the probability of the purchase. For instance, if you show a pattern of purchasing things at a particular time, the algorithm will pick it up. Plus, if it notices some special event in your calendar is coming - like a birthday, vacation, or wedding - it will recommend fitting items.

Predictive Analytics

With predictive analytics that are often a part of retail solutions, retailers can understand how their decisions and market trends impact their business. This empowering tool serves them for various purposes, including: 

• customer segmentation - by analyzing customer behavior and identifying the patterns with predictive analytics, the companies can divide the customers into groups and adjust the recommendations and communication on this basis;
• inventory management - predictive analytics helps businesses to understand the real-time demand and availability of their items and predict the fluctuation of demand in the future, optimizing their inventory to predict those changes;
• revenue forecasting - using real-time and historical data, they can combine such indicators as market trends and buying patterns to predict revenue and make informed business decisions on this basis.

Dynamic Pricing

The dynamic pricing strategies enable retailers to maximize their demand, using time opportunity and customers’ personal traits to find the highest price point they are willing to pay while keeping the probability of the purchase high. Retailers can construct their dynamic pricing strategy in various ways, focusing, for instance, on inventory, value, costs, competition, or demand. Retail marketplaces, which grew big in the last decade, have popularized dynamic pricing, allowing retailers to automate the pricing process and enjoy the opportunities flexible prices provide.

NLP (Natural Language Processing)

Natural language processing is a branch of artificial intelligence that enables machines to comprehend human language - in a written, but also a spoken form. It has become a foundation of various tools commonly used today, including generative models like ChatGPT or Bard. In retail, natural language processing finds its application mainly in customer service. 

Considering its specifics (purchase processes, delivery, returns), retail is customer request-intensive, and NLP can support the customer agents in solving various tasks, for instance, in the form of chatbots. NLP also enables retailers to carry out sentiment analysis in order to draw feedback from various channels and use it for optimization.

Applications of Artificial Intelligence in the Retail Industry

Having already discussed various branches of artificial intelligence in retail, let’s now move to real-life specific examples that can help you understand the potential of AI in this industry.

Personalized Shopping Experiences With AI

AI in retail is all about understanding you as a customer and using these insights to make you buy more. Personalized shopping experiences are designed based on your historical and real-time data, creating a funnel that will likely lead you to a finalized purchase. Various elements can constitute it, depending on the retailer’s choice - from personalized ads newsletters, and push notifications, through customized product categorization and recommendations to special offers tailored to customer preferences and tastes. It’s hard not to succumb to this personalized experience - the brand gains your confidence little by little, and before you know it, your purchase is finalized!

Chatbots and Virtual Assistants for Customer Service

As the development of NLP is gaining momentum, chatbots are becoming much better at understanding human questions and requests, but also the sentiment behind them. They can thus carry out the conversation in a more natural way, saving customers some frustration. Retailers rarely decide to replace the human customer service department with bots - and actually, many countries, like Spain, are introducing laws that provide the customer with the right to require a human consultant. However, chatbots can take over less complex or often repeating problems, saving consultants a lot of time and allowing them to focus on more demanding tickets. That, of course, results in better productivity.

AI-Powered Recommendation Engines

Good recommendations are the key to high margins, whether you run a marketplace or have your own shop. Based on what the customer viewed previously, the algorithms can identify the items they are most likely to purchase and recommend them to them, increasing the cart value. If they combine the viewing data with customer behaviors (what do you buy the most and when, what are the aspects that stop you from buying), the probability of purchase increases even more. Pair it with the price estimated based on your data and real-time factors, and the purchase probability skyrockets.

Predictive Analytics for Inventory Management

Retailers can use predictive analytics to understand the fluctuations in demand and adjust their supplies to the forecasts in order to prevent overselling or overstocking and optimize the usage of warehouse space. Many retail companies incorporate these insights into their pricing strategy, manipulating the prices to stimulate the sales of overstocked products or, on the contrary, decelerate the sales of these in the highest demand to refill the stocks.

AI-Powered Visual Search and Product Discovery

Visual search creates new awesome possibilities for retailers, making it much easier to gain recognition. In a nutshell, this rapidly developing technology makes it possible to point your phone camera at a specific object and identify it, moving directly to the retailer’s shop. Whether it is the dress in the film you are watching or the item you are seeing on the street market, within a few seconds you can get to know what the product is and how to purchase it. It’s possible with the marriage of computer vision and other AI methods. 

Smart Shelves and Product Tracking With AI

While artificial intelligence changes the online shopping experiences, it can also help retailers improve the offline one while providing them with more control over their inventory. Smart shelves rely on computer vision, which processes the captured image in search of missing, misplaced, or damaged products and verifies their availability. That provides the retailers with the big picture, making it easier to manage the stock in a way that reflects actual demand. 

With the smart shelves systems, which involve cameras and AI-powered algorithms that process the image, they can also keep the aesthetics of the store under control, making the shopping experience better. Product tracking works in a similar way, often involving camera-equipped drones, but it allows the employees to track products in the inventory, streamlining the restocking operations.

Augmented Reality for In-Store Experiences

Online shopping is the new normal, but that doesn’t mean you cannot have a real-life-like in-store experience anymore. Augmented reality allows you to feel like in a physical store without leaving the house, experiencing the products and the environment brand is willing to create. The aim of AR implementation is to remove the obstacles that traditional shopping created - above all, the inability to fully see the product and verify its properties. At the same time, the brand has much more opportunities to sneak its branding in augmented reality than they have in the regular online store, and that aspect also may impact sales positively.

Optimizing Store Layout, Product Placement, and Planograms With AI

Using computer vision, stores can easily identify elements of the layout that are not in line with their visual guidelines. They can collect the sales results and customer feedback after introducing the changes in the layout and draw data insights from them with the machine learning algorithms for optimization purposes. Planograms serve a similar purpose as the smart shelves, providing the store managers with a big picture of the store. As a digital reflection of retail space, it shows them how and where the product should be placed. With AI technology, retailers can automatize their updates so that they include all the requirements and automatically adjust them to the changes in the company’s policy.

AI-Powered Supply Chain Management

Artificial intelligence can be used throughout the whole supply chain to find the optimal delivery routes in terms of time and expenses, shorten the delivery time, and improve cost-efficiency (fuel use, etc.) With artificial intelligence tools using predictive analytics, companies can predict demand and adjust the supply to these estimations, optimizing their business operations in terms of costs and inventory management. AI helps avoid deficits and overstocking, leading to better customer satisfaction and higher margins.

AI in Online Advertising and Marketing

Artificial intelligence can also serve retailers to improve the efficiency of their marketing efforts. Personalized advertising campaigns are an integral part of a tailor-made, seamless shopping experience, making it much more likely for the customer to finalize their purchase. Personalized ads use customer data - from the search query and the visited sites to location and demographic information - to make the displayed content more accurate and increase the probability of purchase. Retailers can adjust the communication based on segmentation to align with customers’ expectations and combine it with a personalized price estimated with a value-based method.

Streamlining Returns and Exchanges With AI

Returns and exchanges are inherent to retail business, and both these processes often rely heavily on AI. Retailers can speed up the processing of claims by directing them to chatbots which collect basic information about the return or exchange and verify whether it’s valid and in line with the company’s guidelines. With the support of particular algorithms, they can evaluate if the claim could be potentially fraudulent and whether it contains all the necessary elements/documents. Then, it’s time to fill up the information required to process the return, which can be done with the help of NLP. 

After the product is returned via a reverse supply chain, the warehouse unit can engage computer vision to automatically verify its state and check whether all the elements are present. At the same time, retailers can track data on the returns and exchanges - how much time it took to finalize the deal, was the help of the human consultant was needed, etc. - to evaluate the efficiency of these processes, crucial in terms of retention rate. 

Emerging Technologies and Their Potential Impact on the Industry

Artificial intelligence has an immense potential to further transform the retail industry, making it more data-driven and customer-focused. Here’s how retail as we know it today can benefit from employing AI-based solutions.

AI Helps Retailers Understand Their Customers Better

In the end, the secret of good sales is a good understanding of your target, and that is difficult to achieve without valuable customer data. Artificial intelligence allows retailers to process it and draw insights from it. These insights can serve for personalization purposes at any stage of a customer journey and building tailored experiences but also for improving the processes, offer, and products in order to maximize margins and solve such issues as abandoned carts, low conversion or low customer engagement or customer loyalty.

AI Means Optimized Processes

Aside from customer data, companies also have operational data at their disposal, and they can use AI to draw insights from them. Machine learning can find the processes that are not efficient enough and suggest changes based on the observed patterns, leading to better productivity. Whether it’s the supply chain, the sales process, delivery, or returns, there’s always something to improve! Many of these issues would not be possible to identify without AI-based analytics, but they would still impact the financial safety of the company.  

AI Provides Opportunity for Automation

By employing artificial intelligence, retail companies can increase their cost-effectiveness and optimize their use of resources, automating repetitive and labor-intensive tasks while the employees can focus on more demanding ones. Automation can cover customer service, supply chain management, quality control, and various other areas relevant to retail.

The Future of Retail is Here: Are You Ready to Embrace AI?

Artificial intelligence will continue to change the face of retail, providing retailers with opportunities to optimize their operations and maximize margins. However, in order to benefit from it, you need to fully understand the mechanisms behind it, the data you need to feed your model with, and different approaches to developing your model. As an experienced AI company, we can help you with that! Reach out to us so that we can talk about your idea.