Four Innovative Applications of Generative AI in Retail
August 16, 2024
Generative AI is a cutting-edge technology capable of “creating” based on past learning. It can generate realistic virtual images, write articles, develop software code, compose poetry, create audio and visual content, and much more. This technology is already being widely adopted across various industries. For example, in healthcare, Generative AI assists in drug development, while in the entertainment industry, it can generate game environments and characters, creating entirely new experiences. The applications of Generative AI are vast, and its potential is limitless.
Applications of Generative AI in Retail
Generative AI is already making a significant impact in the retail industry, benefiting both business owners and consumers. By addressing the crucial needs for personalization and innovation, this technology can precisely meet customer demands, offering unprecedented experiences while helping businesses optimize operational efficiency.
- Personalized Recommendations
Most shopping websites recommend products based on our browsing history and purchase records, and Generative AI can go a step further by creating personalized shopping lists for each individual. In the context of fashion retail, for example, Generative AI can analyze not only a customer’s purchase history but also their style preferences, generating unique outfit suggestions that enhance customer satisfaction and conversion rates. - Virtual Fitting:
Leading fashion brands are using Generative AI to create online virtual fitting rooms. Customers no longer need to visit physical stores; instead, they can input their measurements—such as waist size, height, and shoulder width—into the online system. Generative AI then creates a 3D model that matches these measurements. Customers can try on various outfits using this virtual model, even uploading their own photos to allow the system to more accurately simulate the fitting. Customers can view the fit and overall look from different angles, helping them make the best purchase decisions.
This virtual fitting feature not only helps online shoppers find items that fit them well but also significantly reduces return rates due to sizing issues, creating a win-win situation for both consumers and retailers. - Product Design
A well-known athletic shoe brand uses Generative AI to design products. By feeding the AI data on current fashion trends, material options, biomechanics, and more, the AI generates various design options. The design team then reviews these AI-generated suggestions to create shoes that are comfortable, durable, and aesthetically aligned with current trends. - Marketing Content Generation
One of the most common applications of Generative AI in retail is marketing content generation. Whether it is product descriptions, blog posts, social media updates, or other marketing visuals and text, AI can produce engaging content that resonates with audiences based on big data, such as trends, customer preferences, and frequently searched keywords. Additionally, Generative AI can tailor marketing content to the specific characteristics of different target markets, adjusting tone and language as needed. This makes marketing strategies more precise and effective, allowing teams to focus more on strategic planning and creative ideation.
Similar to the 80/20 rule, we can delegate 80% of routine tasks to AI, while reserving the remaining 20% for critical planning tasks, ensuring the team focuses on “high-value, important but not urgent tasks,” thereby achieving greater efficiency.
Challenges of Generative AI
Despite its broad applications, Generative AI in retail faces some challenges:
- Data Quality and Privacy: High-quality data is needed to train models, and customer data privacy and security must be ensured.
- Content Quality Control: The generated content may sometimes be inconsistent with reality or have unstable quality.
- Ethical and Legal Issues: If the generated information contains false or misleading elements that are not verified and corrected, there could be legal risks.
Generative AI will continue to drive innovation and transformation in retail, from enabling smarter customer interactions, creating real-time personalized shopping experiences to dynamically adjusting marketing strategies based on market changes, producing product packaging and promotional videos, and even developing no-code tools that allow retailers to easily enhance operational efficiency, and more.
