Generative AI in Retail: Use Cases, Examples & Benefits

Retail businesses strive to enhance customer experiences and loyalty. This requires producing attractive content in various formats, effective marketing efforts, and exceptional customer service.

With generative AI, retailers can resolve most of these issues through automation, particularly by enhancing their ability to analyze customer data for more personalized customer experiences.

See 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 historical sales data. The AI model can generate multiple variations, allowing companies to shortlist the most appealing options. 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

Personalizing the display options according to customer choice is another option. The video below demonstrates an example of AI-generated 3D models that can be integrated into product displays.

For more information, you can check our article on the use of generative AI in fashion.

2- Automated content generation

Generative AI produces marketing content at scale, including product descriptions, email campaigns, social media posts, and advertising copy. This automation allows retailers to maintain consistent brand voice while personalizing messages for different customer segments and channels.

Figure 2. ChatGPT content creation is an example of using generative AI in retail

For more information, we have articles on AI content generation and SEO optimization.

3- Personalized marketing

AI can generate personalized customer experiences through the marketing content for individual customers, such as emails or ads. These are produced based on customer data, including 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.

Explore how generative AI can improve marketing strategies from our article.

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 product demand, 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 essential tech to invest in 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 using generative AI in the supply chain.

6- Visual Search and Virtual Try-On

AI-powered visual search allows customers to find products by uploading images, while virtual try-on technology lets them see how products will look before purchasing. These technologies reduce uncertainty in online shopping and improve customer confidence.

Generative AI can also power conversational virtual assistants that assist customers throughout 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

AI-powered chatbots and virtual assistants handle customer inquiries, provide product information, and guide customers through the purchasing process. Advanced systems can understand context and provide human-like responses while escalating complex issues to human agents.

Modern AI customer service systems maintain conversation context, understand customer intent, and provide relevant product recommendations during support interactions.3

Generative AI Applications in the Retail Industry

1- eBay

eBay shows one of the biggest examples of using generative AI in retail. eBay ShopBot serves as a personal shopping assistant, helping customers navigate eBay’s extensive array of over a billion listings to find 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.

2- Shopify

Shopify is another company that is implementing generative AI in its 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.

3-Stitch Fix: Personalized Styling Recommendations

Stitch Fix uses generative AI to create personalized style profiles for each customer. The AI analyzes customer feedback, purchase history, style preferences, and even social media activity to recommend clothing and accessories. The system generates detailed style profiles that help human stylists make better selections, resulting in higher customer satisfaction and lower return rates.

4- The North Face: Interactive Shopping Assistant

The North Face uses IBM’s Watson-powered AI to offer a conversational shopping assistant on its website. The AI assistant asks customers a series of questions about their preferences, planned activities, and intended usage for outdoor gear, and then generates product recommendations based on the responses. By leveraging generative AI, The North Face enhances the online shopping experience, making it more interactive and tailored to individual needs.

5- Sephora Virtual Artist

Sephora’s Virtual Artist app uses facial recognition and AR technology to let customers try on makeup virtually. The AI analyzes facial features, skin tone, and lighting conditions to provide realistic previews of how different products will look. Customers can experiment with various combinations before making purchases.

6- Peter Sheppard Footwear

This luxury retailer implemented AI chatbots on their Shopify website to match the level of personalized service provided in their physical stores. The AI system includes product recommendations, sizing advice, and care instructions while maintaining the brand’s premium service standards.

Benefits of Generative AI for the Retail Industry

1. 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 enables businesses to focus more on strategic decision-making and other key tasks.
2. 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.
3. Improved customer service: By utilizing generative AI in retail, businesses can offer 24/7 customer support. AI-powered chatbots can respond to customer queries in real time, resolve issues, and provide information. Thus, it helps to improve customer satisfaction.
4. 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.

FAQ

External Links

• 1. “How to Build an AI Fashion Designer | by Fathy Rashad.” Towards Data Science
• 2. Say “Hello” to eBay ShopBot Beta.
• 3. Verifying your connection....