GenAI-assisted shopping experiences enable customers to find what they want faster, increasing loyalty, and boosting revenue and average order value. Discover how you can get started with a Generative AI Personalization Agent to provide conversational shopping assistance.
The impact of GenAI on the retail sector by 2029
Of consumers expect personalization to make navigation easier both in-store and online
Of retailers plan to invest in generative AI in the next 18 months
Of retail executives view GenAI as instrumental to their business revenue growth
Retail has been a driving industry in the area of personalization for customers. New Generative AI use cases are allowing brands to provide seamless browsing and shopping experiences to customers, bringing the offline experience online.
Advanced Query Understanding: Employ sophisticated natural language processing to comprehend detailed and broad queries, ensuring accurate and relevant search results for specific product attributes and descriptions.
Semantic Search Capability: Enable the search engine to understand the context and meaning behind queries, returning products that match the intent of the search, even with non-product-specific language.
An AI-powered browse feature: Use machine learning to select the optimal ordering of products on your site. Over time, the AI learns the preferred product ordering for each customer using historical data.
Context-Based Suggestions: Offer content tailored to the user’s current mood and context, such as seasonal recommendations relevant to their location.
Image-Based Search: Implement object recognition technology to allow shoppers to search using images, providing instant results for visually similar or complementary items in the product catalog.
Personalized Search Results: Customize search results based on individual shopper behavior, such as previous clicks, purchases, and browsing history, offering a tailored shopping experience.
Real-Time Product Discovery: Utilize AI to deliver fast and relevant product matches, enhancing the overall efficiency of the search process and improving customer satisfaction.
Predictive Search Suggestions: Offer intelligent, real-time search suggestions as users type, predicting their needs and helping them find products more quickly.
Comprehensive Analytics and Insights: Provide detailed analytics and insights into search behavior, helping retailers understand trends, popular searches, and areas for improvement to continually refine the shopping experience.
Increased average order value due to customers seeing more accurate recommendations
Increased revenue due to higher average order value and faster browsing + checkout processes
Improved customer loyalty with personalization that continues to become more tailored to each customer
We’ve developed a range of packages to help you make progress on your Generative AI journey, no matter where your business currently is. Datatonic’s Personalization Agent enables you to rapidly build a custom solution to start seeing real results fast.
Develop your GenAI roadmap by looking into what your business needs the most and how this could be solved with potential Generative AI use cases.
Assess if your GenAI use case is ready for production across reliability, scalability + security best practices.
Prove the value of your concept within a reduced scope, gather requirements and create a production roadmap.
Productionize your GenAI solution using architecture, security and CI/CD best practices.
Drive adoption through production support encompassing model lifecycle management, monitoring and improvement.
Datatonic has several Generative AI solutions, ranging from workshops to explore the possibilities with GenAI on Google Cloud, to a full custom Generative AI model implementation, and managed GenOps platform.