Generative artificial intelligence has quickly become available for many industries, and its adoption often appears to happen instantly for some businesses. Moreover, the demand for the technology grows steadily: the global generative AI market in eCommerce was valued at USD 624.51 million in 2022 and is projected to grow to approximately USD 2,530.89 million by 2032.

In 2024, generative AI in eCommerce is taking off, transforming almost every aspect of retail, from content creation to preventing fraud. Moreover, it is reported that generative AI brings efficiency and reduces costs by over 30% thanks to automating business processes. So, with this insight in mind, we suggest you take a closer look at eCommerce operations that can be disrupted thanks to generative AI and explore generative AI’s impact on the eCommerce industry in the near future.

Generative AI in eCommerce: Value-Driving Use Cases to Consider 

The business impact of big data is hard to overestimate. The more information eCommerce businesses have, the more meaning and worth they draw from it. Online stores are full of data: shopper reviews, product descriptions, item images, prices, and more information can be analyzed and utilized to improve online sales platforms with generative AI. Moreover, GenAI can offer much more, and we delve deeper into the use cases below. 

How Generative AI Is Used in eCommerce

Optimization of Content Creation 

One of the most popular uses of generative AI solutions is, of course, content generation. For instance, the craft store Michaels utilizes generative AI to create better website copy, marketing emails, and SMS campaigns, thus achieving better customer engagement. In fact, the company says that using AI algorithms for content creation resulted in a 25-41% improvement in click-through rates. 

In one of our projects, we also used generative AI in eCommerce to help our client effectively extend its product range. Our team was responsible for fine-tuning product descriptions and cleaning up names for over one million items available. We employed ChatGPT to find and eliminate irrelevant textual information from product descriptions and titles. We also created a custom script to support ChatGPT functionality and elaborated the list of prohibited words and pertinent keywords to improve the accuracy of the content generation and cleanup. 

# AWS infrastructure, # Data Analytics, # UI/UX Design, # Web development
Leveraging AI/ML for Expanded Product Range and Enhanced eCommerce Product Listings 

Highlights Client Our client is an online retail business based in the United States, operating according to the dropshipping…

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Efficient Inventory and Supply Chain Management

The global retailer Amazon masters artificial intelligence and machine learning for demand forecasting. The company’s tech team ensures accurate prediction results thanks to the combination of deep learning, image recognition, and natural language processing that serve as a foundation of generative AI. 

With demand forecasting done by examining vast amounts of historical sales data, Amazon spots intricate trends, derives meaning from product photos, and examines user reviews. Such an approach helps to avoid overstocking or stockouts, product waste, and improve inventory management overall. In addition, Amazon is investigating the use of deep reinforcement learning (DRL) for supply chain management optimization based on the aforementioned demand forecasting. 

Customization of Products to Meet Specific Needs

Unilever, a global FMCG (Fast-Moving Consumer Goods) company, has decided to improve its hair care products with generative AI tools. For one of its brands, the company created an interactive diagnostic tool that implies collecting information from customers. It works the following way: first, shoppers respond to inquiries regarding their hair and scalp conditions. Then, using generative AI capabilities and a wealth of knowledge from dermatologists, the application creates a personalized profile of the scalp and hair and recommends products that may help customers to have better hair care.

Such an application of generative AI in eCommerce app development allows for staying connected to clientele, understanding their needs, and achieving customer satisfaction. 

Utilization of Real-Time Analytics for Informed Decisions

Target, an American retail corporation, uses generative AI tools along with machine learning to monitor the availability of products. The company tracks the behavior of customers when they are scrolling through multiple products on a website. It also checks customer feedback on social media and monitors market trends concerning one or another product. Based on such data, Target predicts demand for items and improves inventory management.

Target is undoubtedly an inspiring example but if you are planning to build an online marketplace, you need to consider that the marketplaces’ business operations are much more complex compared to small online stores. Nevertheless, real-time analytics can significantly simplify the processes for you. Target proves it because, on top of improved inventory management, real-time analytics also enabled them to dynamically manage product placements and ensure optimal stock levels. 

Want to learn how to efficiently predict customer behavior in retail? 

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Large-Scale Market Research and Data-Driven Insights 

A major consumer insight researcher GfK utilizes generative AI models to interpret extensive customer data, information about market trends, and, hence, equip the eCommerce industry with actionable insights. The company collects data from POS terminals, customer interactions with brands online, and other multiple sources to craft market reports and help eCommerce businesses see what their shoppers want, what their competitors are after, and what decisions are crucial to make right away to stay afloat.

Serhii Leleko: AI&ML Engineer at SPD Technology

Serhii Leleko

AI&ML Engineer at SPD Technology

“Traditional market research is expensive and relies on limited focus groups. Generative AI offers much more: by analyzing vast amounts of online data from social media or reviews, GenAI can uncover hidden customer preferences and emerging trends in real-time. This allows businesses to gain customer insights at scale and identify what resonates with their audience to improve overall customer experience.”

Efficient Translation and Context-Driven Localization

Building an eCommerce website available in several locations requires localization efforts. That means allocating a drastic part of your budget to specialists who will translate digital store content into different languages and tailor it to the cultural specifics of the target audience. However, generative AI can streamline this process and reduce costs. 

AI-automated localization is a common practice now, and tech vendors can even sell ready-made solutions. For instance, Amazon designed such a tool specifically for retail. This solution offers functionalities for scalable, real-time, and accurate translation. The localized content looks like natural language and fits the context of products in the store. As a result, eCommerce businesses can expand their reach, win new markets, and serve customer satisfaction.

Deployment of Intelligent Chatbots for Customer Support

Statista reports that the most common use of generative AI in eCommerce in 2023 was for customer support, with 42 percent of respondents utilizing it to resolve post-purchase queries. One of the eCommerce businesses that implemented AI solutions for improving customer service is Sephora. With an AI-powered chatbot, the leading beauty retail chain provides information about products, helps customers to resolve their problems, or even offers beauty tips. 

Artificial intelligence transforms customer service with chatbots that can free up customer service employees to focus on more complex issues. In one of the projects, we helped a French fashion store leverage pre-trained machine learning models for NLP and data embedding. In such a way, we created a bot that delivers responses within less than 10 seconds for 99% of user queries. Our efforts resulted in significantly improved customer experience.

# Data Analytics, # Web development
High-Load Support AI Chatbot for an Online Fashion Store

Highlights Client Our client is a B2C eCommerce company operating in the fashion niche. The organization sells a wide…

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Detection and Prevention of Fraudulent Activities 

eBay uses generative AI tools to detect fraudulent activity on its marketplace. AI algorithms employ machine learning techniques to detect potentially malicious bidding patterns, suspicious listings, and other activities that can fall out of normal activity patterns that usually present in the store. 

With the help of generative AI, eBay is better equipped to defend users against different types of fraud by constantly adapting to new fraud strategies. For example, eBay uses techniques like anomaly detection and risk scoring in its fraud detection systems to examine enormous volumes of transactional data and identify potentially suspicious activity. These AI models have the capacity to learn from fresh data, which enables them to keep ahead of new risks and adjust to changing fraud patterns.

Implementation of Hyper Personalization Strategies

The major fashion eCommerce store H&M goes beyond traditional personalization and introduces the possibility to create custom clothes designs. This functionality is available in H&M’s Creative Studio and is supported by generative AI technology. 

In a nutshell, the feature works as follows: shoppers type a text description of the design they want. Then, generative AI algorithms recognize the text using natural language processing and create an image based on the description. This approach helps engage customers like never before and creates a strong bond between a brand and its audience. 

Multi-Channel Sentiment and Voice of Customer (VoC) Analysis

Walmart leverages generative AI in many ways with creating review summaries as one of the most prominent applications of this technology. This eCommerce business relies on this technology to examine what consumers think about the brand, what their sentiment towards certain products and services is, what features of the eCommerce store they enjoy, and more. 

Such an approach can be aimed at discovering customer sentiment from multiple channels, including customer feedback on a website, responses to targeted marketing campaigns, or social media posts. All that helps Walmart to improve its decision-making processes and outline priority product features for enhancing customer satisfaction from interaction with the brand.

Implementing Dynamic Pricing Mechanisms

Zalando, a European fashion marketplace, makes their prices respond to the demand thanks to generative AI that scrutinizes tons of pricing on other eCommerce websites. The company achieved dynamic pricing by training AI models to draw actionable insights from market trends, competitor prices, and consumer sentiment. 

Zalando’s dynamic pricing system, powered by artificial intelligence, facilitates real-time analysis and predictive analytics in retail. These capabilities are essential for modifying prices in response to prevailing market conditions. As a result, individualized pricing takes into account the preferences and buying habits of the consumer and optimizes revenues. 

Visual Search, Product Discovery and AR Shopping Experiences

Decathlon, a sporting goods retailer, opted for integrating generative AI into its website for visual product discovery. The solution allows consumers to navigate through products in the online store with a search that can process and recognize pictures. To take advantage of this functionality, Decathlon’s customers need to take a photo of products they are interested in, upload the photo to the website, and browse similar products that appear in the results.

Decathlon reported that such an approach to the implementation of generative AI helped to achieve a 250% increase in click-through rates and a 330% improvement in customer engagement. 

Best-Matched Influencers Identification and Campaign Optimization 

eCommerce businesses can leverage generative AI to identify the influencers that will be the most suitable for marketing campaigns. AI helps with analyzing vast amounts of customer data and social media trends to find influencers whose audience matches the brand’s target market. Plus, generative AI models can predict the potential reach and outcomes of a campaign with a specific influencer, allowing for data-driven selection.

AI tools can enhance the campaign’s optimization after an influencer has been selected. Influencers can benefit from AI’s ability to adapt ad targeting based on campaign data, create content specifically for their target audience, and even track effectiveness in real time. 

Looking for insights into how to unlock retail success with artificial intelligence? 

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The Future of eCommerce and The Place of GenAI

The competition in eCommerce becomes harder, the processes shift to more complex ones, and customer preferences change dynamically – these are just some of the major factors that influence how the industry will transform soon. Many retailers will need new solutions powered by AI. If you want to be sure that you choose one of the best eCommerce website development companies for your eCommerce project, check if the vendor can keep up with the following trends.

Trends of generative AI in eCommerce

The Rise of Omnichannel Retailing

The 2020 survey from Statista says that about half of eCommerce decision-makers in North America and Europe said omnichannel tactics would be irreplaceable for business. Indeed, the omnichannel strategy is a necessity for a retail business to survive. It benefits the whole industry by creating a seamless and unified customer experience across all channels, boosting engagement and sales.

With generative AI, omnichannel can experience significant enhancements, just like any other aspect of eCommerce. Those can include:

  • Personalized Customer Experience: With a unified network of eCommerce channels, generative AI gets access to great volumes of customer data for analysis at once. Online sales, in-store purchases, or social media deals can be scrapped with AI tools for a big sales picture. Based on this data, eCommerce businesses can develop tailored recommendations, personalized marketing messages, and customized landing pages.
  • Seamless Integration: Generative AI can also combine customer information from different channels and serve consumer needs both in-store and online. For instance, store employees can see the information about the client in the system while in-store and offer discounts for specific products shoppers viewed online.
  • Enhanced Virtual Assistance: With all the information held by AI, intelligent chatbots can know each customer better and provide consistent customer service in a natural tone of voice and a personalized manner.

We know how omnichannel experience can change the business. SPD technology created an aggregated merchant portal for BlackHawk Networks, integrating multiple platforms into one and automated processes across channels. This resulted in a universal platform that attracted 8000 existing businesses thanks to its flexibility and unified customer experience.

Subscription-Based eCommerce

It is reported that the market for subscription eCommerce expands at a rate of over 100% annually. The essence of subscription-based eCommerce is making shopping easier, letting you place the order once, and receive the package with goods regularly. Since generative AI is perfect for automation and generation of insights, this type of retail can be improved thanks to:

  • Personalized Subscriptions: With the analysis of customers’ purchase and browsing history, AI can suggest alternative subscription packages or boxes to those that consumers have previously ordered. These boxes can contain products that correspond to individual tastes and needs, which contributes to fostering customer loyalty.
  • Content Generation: Marketing efforts with generative AI for subscription-based retail can result in relevant newsletters or promo campaigns that contain individualized recipes, fashion recommendations, or nutritional plans. 
  • Customer Retention: AI is capable of collecting data on customer engagement and sales frequency. That means businesses can see when some shoppers are at risk of churn. To make customers stay with the brand, this technology helps figure out what opportunities can lead to retention: be it personalized offers, reminders, or limited-time discounts.

Sustainability and Ethical Commerce

Eco-friendliness has become a global trend, which means eCommerce businesses need to adapt their processes to this trend fast to stay competitive. According to Statista, almost eight in ten consumers worldwide preferred a more sustainable delivery option for their online orders in 2023. Luckily, if you opt for custom AI solutions development services for your store, generative AI brings the following benefits to the table: 

  • Sustainable Practices: Since generative AI can accurately forecast demand, it also simplifies the processes within supply chain and inventory as well as makes them more transparent. That leads to reduced waste, and thus, more eco-friendly practices.
  • Ethical Sourcing: AI is able to track a product’s origin and verify that it complies with ethical requirements. In order to suggest the most environmentally sound choices, it can also evaluate the data from suppliers.
  • Consumer Education: GenAI may produce educational content that informs readers about a brand’s ethical and sustainable business practices.
Serhii Leleko: AI&ML Engineer at SPD Technology

Serhii Leleko

AI&ML Engineer at SPD Technology

“AI in eCommerce can bring optimized supply chains and inventory management to reduce waste, promote eco-friendly product recommendations, automate sustainable practices, and create a more efficient ecosystem. At the same time, addressing data quality and privacy concerns, as well as ensuring fairness and eliminating bias, are the most common challenges that businesses face on the way to generative AI adoption.”

Global Expansion and Cross-Border Selling 

Global retail sales are expected to reach about $32.8 trillion by 2026, an increase from roughly $26.4 trillion in 2021. So, if you are looking for eCommerce software development services to conquer not only the local market but the global one as well, consider choosing the vendor, who can also integrate generative AI into your future selling platform.

This AI technology allows you to enter new markets thanks to:

  • Localized Content and Marketing: Generative AI can analyze where your shoppers are from and show them localized product descriptions, marketing banners, and currencies. Plus, AI can adjust relevant marketing messages according to the culture of the customers’ region.
  • Market Analysis: GenAI is capable of analyzing consumer behavior and worldwide market trends, enabling businesses to receive insights for scrutinizing their approaches for different geographies, spot untapped markets, and improve pricing tactics.
  • Regulatory Compliance: AI can navigate through rules and regulations to make sure that the business complies with required laws.

We, at SPD Technology, have extensive experience working with different regulatory frameworks as well. Our team ensured GDPR compliance for a range of projects as well as delivered PCI DSS-compliant financial platforms, took care of OFAC for eCommerce merchant onboarding, and HIPAA for medical services. Our team prioritizes the importance of ensuring the safety and privacy of customer data and making businesses trustworthy.

Robotics and Automation in Order Fulfillment

Robotic process automation (RPA) can make sure that warehousing operations can be optimized to the extent that you can reduce cost and speed up order processing. Inventory data can be provided by IoT sensors installed on shelves, while orders are filled and restocked by robots.

The role of generative AI in this venture can bring even more advantages to RPA, namely:

  • Warehouse Automation: Predictions of demand, automation of inventory management, packing, and shipments bring efficiency to warehousing processes and significantly reduce human errors and operational time.
  • Predictive Maintenance: Generative AI collects data from sensors and monitors important equipment metrics. Based on this data, AI can suggest when it is time to perform maintenance measures.
  • Customer Order Incitement: According to the report, 92% of customers were eager to try or had already tried an interactive display in stores that offered them fashion advice, suggested products, and encouraged purchases.

Conclusion

Generative AI in eCommerce is already bringing significant benefits to many businesses. eCommerce giants like Amazon, Walmart, and Target use GenAI for supply chain management, multi-channel sentiment analysis, and real-time analytics respectively. At the same time, H&M utilizes GenAI for custom designs, while Sephora helps its shoppers receive efficient online assistance from chatbots. Other companies elevate their business competitiveness thanks to product customizations, large market research, content generation, localization, and fraud prevention with this top-notch technology.

The use of GenAI in the future promises even more benefits. It can be integrated with omnichannel strategies, improve subscription-based eCommerce, promote sustainability and eco-friendliness, ensure expansion to new markets with automated localization, and improve warehousing with RPA. 

So, if you want to stand on the path of eCommerce innovation, don’t hesitate to grasp the power of GenAI now. For the case you need assistance with leveraging eCommerce and AI/ML technologies, we have extensive expertise to help you out.

FAQ

  • What Is Generative AI in Retail and eCommerce?

    Generative AI is transforming retail and eCommerce by automating content creation and personalizing the customer journey. It can generate unique product descriptions, tailor product images to specific demographics, and even recommend complementary items based on customer preferences. This not only streamlines operations and reduces costs, but also improves customer engagement and conversion rates.