Generative AI in Retail: Use Cases, Examples & Benefits in 2024
Retail businesses constantly strive to enhance customer experiences and loyalty. This requires the production of attractive and various contents, good marketing efforts, and great customer service efforts. By leveraging generative AI, retailers can resolve most of these issues with automation and creativity, particularly in improving their ability to analyze customer data for more personalized customer experiences.
In this article, we explain the examples and benefits of generative AI in retail.
7 Use Cases of Generative AI in Retail
1- Product and display design
Generative AI can create new product designs based on the analysis of current market trends and customer interactions, consumer preferences, and historic sales data. The AI model can generate multiple variations, allowing companies to shortlist the most appealing options. For instance, creating designs for clothing, furniture, or electronics can be an option.
Figure 1. Product design can be the number one use case of generative AI in retail
Source: Towards Data Science1
Or personalizing the display options according to customer choice is another option. The video below shows an example of the AI generated 3D models that can be implemented in product displays.
If interested in more, you can check our article on the use of generative AI for fashion.
2- Automated content generation
Retailers can use AI to create descriptions for their products, promotional content for social media, blog posts, and other content that improves SEO and drives customer engagement.
Figure 2. ChatGPT content creation is an example of using generative AI in retail
3- Personalized marketing
AI can generate personalized customer experiences through the marketing content for individual customers, such as emails or ads. These are produced on the basis of the customer data such as past purchasing behavior and preferences. AI can predict what kind of promotional content will most appeal to each customer, increasing the effectiveness of marketing campaigns.
4- Product recommendations
Using generative models, AI can suggest new or alternative products to customers that they might be interested in, based on their buying history and preferences. It can also anticipate their future needs and preferences, thereby improving the shopping experience.
5- Inventory management & supply chain optimization
Generative AI can help forecast demand for products, generating predictions based on historical sales data, trends, seasonality, and other factors. This can improve inventory management, reducing instances of overstock or stockouts.
Generative AI can be an important tech to invest for many supply chain operations, including but not limited to:
- Demand forecasting
- Supplier risk assessment
- Anomaly detection
- Transportation and routing optimization
To explore more, check out our article on the use of generative AI in the supply chain.
6- Virtual shopping assistants
Generative AI can power conversational virtual assistants that help customers in their shopping journey, generating responses to their queries and guiding them through the purchasing process.
Learn more about virtual assistants from our article on this topic.
7- Customer service automation
The use of generative AI and contact center AI technologies such as conversational AI, large language models (LLMs), and chatbots can automate and increase the efficiency of human customer service representatives.
We have many articles on the different applications of the generative AI models in customer service. You can explore them in detail:
- Automation in Customer Service: Use Cases, Benefits, Best Practices
- 10 Use Cases of Conversational AI for Customer Service
- ChatGPT for Customer Service: 7 Use Cases & Benefits
- Top 9 Customer Service Chatbot Use Cases
Generative AI Applications in the Retail Industry
eBay shows one of the biggest examples of using generative AI in retail. eBay ShopBot serves as a personal shopping assistant, assisting customers in navigating through eBay’s extensive array of over a billion listings to discover the most attractive deals.2 Customers can engage with the ShopBot using text, voice, or even by sharing a photo to indicate what they’re searching for. To enhance its understanding of the user’s requirements, the bot initiates further conversations, allowing it to offer tailored suggestions.
Shopify is another company implementing generative AI in retail solutions. Shopify Magic employs automatic text generation to automate the content creation process.3 Leveraging artificial intelligence, it takes the information and generates suggestions for various content types. This includes product descriptions, email subject lines, and headers for an online store.
Benefits of Generative AI for the Retail Industry
- Efficiency and cost reduction: Generative AI in retail can automate various tasks such as content creation, customer service, and inventory management. This saves time, reduces labor costs, and allows businesses to focus more on strategic decision-making and other important tasks.
- Increased personalization: Generative AI can create highly personalized content and recommendations for individual customers. This can enhance customer experience, increases customer loyalty, and can lead to higher sales.
- Improved customer service: By using generative AI in retail, businesses can provide 24/7 customer service. AI-powered chatbots can respond to customer queries in real time, resolve issues, and provide information. Thus, it helps to improve customer satisfaction.
- Innovation and product development: Generative AI can provide new product designs or variations based on market trends and customer preferences, fostering innovation and potentially leading to more successful products.
If you have questions or need help in finding vendors, don’t hesitate to contact us:
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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