How Generative AI in Retail Industry is Redefining Customer Engagement

Last Updated on December 7, 2023 by SPN Editor

The retail industry is witnessing a significant transformation with the integration of Artificial Intelligence (AI). The Generative AI in retail market is projected to reach a staggering US$ 23,426.3 million by 2026, growing at a Compound Annual Growth Rate (CAGR) of 33.7% during the forecast period. This growth is primarily driven by the transition of retailers from traditional methods to AI-enabled solutions.

A Forbes article reveals that 83% of businesses today consider AI as a strategic priority, and 84% believe that AI will help them maintain or gain a competitive edge. The benefits of Generative AI in retail operations, such as improved quality, faster decision-making, operational agility, and enhanced customer experience, are becoming increasingly evident. These factors, coupled with the extraordinary advantages of AI-powered data analytics, are expected to fuel the demand for Generative AI in the retail market in the coming years.

A report by Fortune Business Insights™ titled “Artificial Intelligence (AI) in Retail Market Size, Share & Industry Analysis, By Offering (Solutions, Services), By Function (Operations-Focused, Customer-Facing), By Technology (Computer Vision, Machine Learning, Natural Language Processing, and Others), and Regional Forecast, 2019-2026” provides a comprehensive analysis of the Generative AI in retail market. The market was valued at US$ 2,306.8 million in 2018.

The increasing adoption of AI-powered chatbots by retail brands for customer engagement is expected to drive the market’s growth. Retail brands can handle multiple queries simultaneously using chatbots, eliminating the need for a large workforce. The positive impact of AI on customer relations and sales is expected to increase the demand for Generative AI in retail.

Moreover, the configuration of close-ended chatbots to answer shopping-related questions, provide quick support and suggestions, and offer better problem resolution is likely to enhance customer loyalty. These factors are expected to accelerate the generative AI in retail market share in the future.

The emergence of virtual trial rooms and ongoing developments across retail supply chains are expected to bolster the market’s growth. Virtual trial rooms allow buyers to try on different outfits without physically wearing them, using digital mirrors. Furthermore, AI enables shoppers to experiment with their outfits through a touch-based interface. These advancements are expected to drive the Generative AI in retail market trend during the forecast period.

For example, Fitiquette, an online fashion platform, leverages innovative technology that enables customers to virtually try on outfits in a 3D environment tailored to their precise body measurements. The virtual fitting room provides a comprehensive 360-degree perspective of how a garment fits and drapes on the customer’s actual body shape.

Generative AI has emerged as a transformative force in the realm of customer experience (CX). Robin Gomez, who heads Customer Care Innovation at Radial, elaborates on how Generative AI is molding the retail sector and enriching the shopping journey.

A host of retailers and brands are enthusiastic about harnessing the capabilities of OpenAI’s ChatGPT, which made its debut in November 2022. They aim to craft an AI-focused customer experience that not only augments their revenue but also caters to the escalating demands of consumers.

While Generative AI has the potential to be a transformative tool, there are still doubts surrounding its deployment. Businesses need to find an equilibrium between enhancing the customer experience and ensuring transparent operations, ethical compliance, and data dependability.

Fresh insights from McKinsey and Company underscore that incorporating AI-powered forecasting into supply chain processes can cut down order errors by 20% to 50%. This amalgamation enables retailers and brands to have immediate access to product availability data, thereby facilitating efficient operations.

Retailers can employ AI in a variety of ways to refine the shopping experience, be it in-store or online. Take for instance Lowe’s, a hardware retail store, which rolled out its inaugural set of LoweBots. These automated machines are programmed to navigate the store, aid customers with basic tasks like item search, and assist with inventory management to provide real-time stock updates.

Chatbots can also deliver responses in various languages. This not only enables employees to serve more customers but also allows them to devote more time to enhancing the overall customer experience. Ideally, customer care representatives should be able to utilize this data to assist customers with BOPIS orders and provide details about the customer’s local store.

Generative AI is instrumental in delivering proactive customer care by offering customized recommendations and instant responses throughout the shopping journey. For example, if a customer is on the lookout for a pair of shorts for their forthcoming summer vacation, the chatbot can provide details on popular items, new arrivals, promotional codes, delivery schedules, and sizing information to help the customer make a well-informed decision. Conversational AI can provide customers with immediate updates and quality feedback, crafting a personalized interaction that meets their expectations.

Implementation of Generative AI in Retail industry

Retailers are leveraging AI technologies in a multitude of ways to boost their operations and customer experience:

Customer Interaction: AI and machine learning are employed to enhance customer interaction during the online and in-store shopping journey. This encompasses crafting personalized shopping experiences and offering purchase suggestions.

Data Management: AI aids in refining data processes and insights. Retailers must comprehend the application of the technology and ensure data privacy and security.

Flexible Pricing: AI empowers retailers to devise flexible pricing strategies for optimal profit margins.

Supply Chain Optimization: Generative AI in retail can tackle challenges such as disrupted supply chains, decreased discretionary spending, and a sudden surge in demand for contactless deliveries. It provides predictive demand forecasting, supply visibility, and the capacity to react to real-time demand signals.

Inventory Management: Examples of applications of Generative AI in retail include robotic warehouse pickers and automated checkout systems. These have a significant financial impact but necessitate more effort to implement.

Product Planning and Development: AI can also prove advantageous in product planning and development, distribution agent support, and identifying market deals and discounts.

The incorporation of AI should be viewed as a component of a long-term transformation plan that will benefit the customer.

Generative AI in Retail industry to Enhance Customer Experience

Retailers are harnessing the power of AI in a myriad of ways to augment their operations and enrich the customer experience:

Designing Products and Displays: Generative AI in retail industry can generate innovative product designs by analyzing current market trends, consumer preferences, and historical sales data. This can be applied to a wide range of products, including clothing, furniture, or electronics.

Generating Automated Content: Retailers are utilizing AI to generate content for their products, including descriptions, promotional content for social media, blog posts, and other SEO-enhancing content. This not only improves their online presence but also drives customer engagement.

Creating Personalized Marketing Strategies: AI is being used to create personalized marketing content for individual customers, such as emails or ads. This content is generated based on customer data, including past purchasing behavior and preferences, leading to a more personalized customer experience.

Offering Product Recommendations: Generative AI in retail can suggest new or alternative products to customers based on their buying history and preferences. This not only enhances the shopping experience but also increases the likelihood of repeat purchases.

Optimizing Inventory Management & Supply Chain: Generative AI can forecast product demand, generating predictions based on historical sales data, trends, seasonality, and other factors. This can significantly improve inventory management, reducing instances of overstock or stockouts.

Providing In-Store Assistance: A prime example of how Generative AI in retail can enhance the in-store shopping experience is Zara’s AI robots. The retailer introduced these robots to avoid long lines and reduce customer waiting times after adopting the Buy Online, Pick-Up in Store concept.

Delivering Personalized Shopping Experience: A clothing retailer reported a 25% increase in sales after implementing AI personalization. The AI strategy offers product recommendations based on customers’ browsing and purchase history, leading to a more personalized and satisfying shopping experience.

Companies Leveraging Generative AI in Retail Industry

Rue Gilt Groupe’s Tailored Suggestions: Rue Gilt Groupe leverages the power of artificial intelligence and machine learning to curate product suggestions for its customers.

Anaplan’s Forecasting Intelligence Platform: Anaplan’s solution merges big data and analytics to assist retailers in retaining their existing clientele and discovering new ones.

Clarifai’s Image Recognition: Clarifai employs AI-powered image recognition to combat the issue of counterfeiting.

Chatbots and Voice Recognition Systems: Technologies such as chatbots and established AI voice recognition systems, like Amazon’s Alexa, are being amalgamated with other devices to boost customer service.

Insights from Predictive Sales: AI algorithms enable companies to sift through vast amounts of data derived from consumer online activity to offer insights into “predictive sales”.

Automated Warehouse Management: The use of robotic warehouse pickers and automated checkout systems are examples of how AI is being utilized in the retail sector.

Customized Marketing: AI can create personalized customer experiences by tailoring marketing content for individual customers, including emails or advertisements.

Inventory Control & Supply Chain Enhancement: Generative AI can aid in predicting product demand by generating forecasts based on historical sales data, trends, seasonal variations, and other factors.

Benefits of Generative AI in Retail Sector

The market for Generative AI in retail sector is projected to surge from $5 billion to over $31 billion by 2028. Artificial Intelligence (AI) is set to revolutionize the retail sector in numerous ways:

Automation: AI significantly contributes to the automation of tasks traditionally performed by humans, freeing up employees to focus more on customer service.

Loss Prevention: AI technologies provide secure scanning methods, aiding in loss prevention efforts.

Sustainability: Generative AI in retail can play a pivotal role in driving sustainability initiatives within the retail sector.

Cost Efficiency: By automating in-store processes, AI can help retailers cut down on operating costs.

Supply Chain Enhancement: Generative AI in retail has the potential to optimize supply chains, boosting efficiency and enhancing customer satisfaction.

Enhanced Customer Engagement and Satisfaction: AI can assist retailers in delivering an optimal customer experience, from shortening shopping times with automated checkouts to providing personalized discounts.

Real-time Inventory Monitoring: Generative AI in retail can facilitate real-time inventory tracking and the digitization of shop displays and fitting rooms.

Future of Generative AI in Retail Industry

Artificial Intelligence (AI) is poised to revolutionize the retail industry, enhancing business efficiency and customer focus. As technology advances, retail entities are keen to comprehend how Generative AI in retail sector.

Here are some anticipated trends and impacts of Generative AI in retail industry:

Automation Surge: AI is projected to automate numerous tasks, enabling specialists to concentrate on problem-solving and fostering a more customer-oriented approach.

AI Adoption: The incorporation of AI in the retail sector has seen a substantial rise over recent years. Presently, over a quarter (28%) of retail firms utilize AI in various facets, a significant leap from just 4% in 2016.

Emergence of New Professions: The fusion of AI with traditional roles is expected to give rise to new professions, such as AI prompt engineers who interact with AI for optimal outcomes.

Customer Intelligence and Inventory Management: Retail industry leaders anticipate that AI will have its most significant impact on customer intelligence (53%), inventory management (50%), and customer service chatbots (49%) in the next two years.

Seamless Integration: The integration of AI into the retail industry heralds a period of unparalleled efficiency, personalization, and innovation. As AI-powered solutions become more embedded in the shopping experience, the boundaries between the digital and physical realms will blur, resulting in a seamlessly integrated retail environment.

Investment Priority: As per technology research firm Gartner, AI was forecasted to be among the top five investment priorities for over 30% of CIOs by 2020, both within and outside the retail sector.