shopperGPT Overview and Limited Time 30-Day Trial Offer

What is shopperGPT?

shopperGPT is a Generative AI (GenAI) cloud platform tailored for online retailers, designed to seamlessly integrate into existing e-commerce systems through APIs. This platform can be embedded directly into a retailer’s search bar or customized for other parts of the user experience, delivering intelligent and highly personalized shopping experiences.

Key APIs and Capabilities

  • Hyper-personalization API: This API leverages AI to analyze customer behavior, preferences, and past interactions to deliver 1-to-1 personalized shopping experiences. It dynamically adjusts product recommendations and content in real-time to match individual preferences, ensuring each shopper receives tailored product suggestions.
  • Recommendation Engine API: This engine suggests products based on user profiles, behavior, trends, and similar user patterns. It intelligently surfaces products a user may be interested in by analyzing their browsing, searching, and purchasing history, driving higher engagement and conversion rates.
  • Natural Language Processing (NLP) Search API: The NLP search enables users to interact with the platform using conversational queries. It understands complex, multi-part queries in everyday language, returning relevant product results with high accuracy, enhancing the shopping experience.
  • Precise Color Search API: This feature allows users to search for products based on specific colors. By analyzing color attributes, it matches products to the precise shade or color group a user is looking for, particularly useful in fashion, home decor, and lifestyle categories.
  • Image Similarity Search API: Users can search for products by uploading an image, and the system will return visually similar items. This visual search capability uses advanced image recognition to identify product characteristics such as shape, style, and texture, streamlining product discovery based on visual references.
  • Underlying Technology The shopperGPT platform is powered by visualAI's foundational AI models, which are built for e-commerce optimization. It includes:
  • Lightweight LLM (Large Language Model): This powers the platform’s natural language understanding and recommendation systems, providing fast and efficient processing of customer queries and data. An option for a DLM (Domain-Specific Language Model) is also available for larger strategic retailers.
  • Retrieval Augmented Generation (RAG): This mechanism enhances response accuracy by retrieving and generating responses based on a vast repository of relevant data, improving the relevance and precision of product recommendations, customer reviews, and search results.
  • Embeddings Engine: This engine generates product vectors, which are dense representations of product features like color, style, and material. These vectors power the recommendation engine, NLP, and visual search, enabling the platform to return the most relevant results.
  • Data Repository for Analytics: The platform also includes a robust analytics system that gathers and processes user interaction data. This repository allows retailers to gain insights into customer behavior, improving decision-making for marketing, inventory management, and user experience optimization.

In summary, shopperGPT is a comprehensive, AI-driven platform designed to optimize e-commerce product discovery and personalization, offering a suite of powerful APIs that integrate smoothly into existing systems while providing deep insights into user behavior and product engagement.

shopperGPT Limited Time Offer

visualAI is offering for a limited time a 30-day free trial pilot phase, which includes:
  • Cooperative platform integration of the shopperGPT hyper-personalization and GenAI search APIs with H&M’s existing online properties.
  • Secure product data inspection, AI-enhancement, and augmentation, ensuring the most accurate product matches based on natural language queries.
  • AI models for hyper-personalization, product recommendations, natural language search, and color/image similarity search.

Our typical approach is to conduct an A/B Proof of Concept (PoC) on an English-language online property. The platform can support multiple languages, and upon initial deployment success, we can develop a rollout plan to expand support across your other properties.

KPI Review and Expected Outcomes: Together, we will review KPIs impacted by this integration, focusing on:

  • Client engagement and satisfaction
  • Time on site
  • Click-through rates (CTRs)
  • Revenue growth

shopperGPT Expected Impact on KPIs

Here’s what we’ve assembled regarding the impact of massively accelerated product discovery, based on available market data from a number of research reports: This does not include the impact of hyper-personalization, natural language, precise color or image similarity search, which all have unique and additional impact on the below metrics.

We’ve validated that shopperGPT accelerates the time to product discovery by 10-20x. As a result, the impact on an e-commerce site should be substantial, affecting multiple key metrics that drive both customer satisfaction and financial performance:

  • Increased Conversion Rates: Faster product discovery directly reduces customer frustration and helps them find what they need more quickly. This improved user experience could lead to a significant boost in conversion rates. An increase of 20-30% in conversion rates is a realistic expectation, as more users are likely to complete purchases when the process is streamlined and efficient.
  • Higher Customer Satisfaction and Loyalty: Speeding up product discovery makes the shopping experience more convenient and enjoyable, which can lead to higher customer satisfaction scores. Satisfied customers are more likely to return to the site, increasing customer retention and loyalty. The reduction in time spent searching could decrease churn by 10-15%, as users become more likely to stick with a retailer that provides a fast, efficient experience.
  • Increase in Cart Size: When customers can easily find products they’re interested in, they’re more likely to browse and add additional items to their cart. This could result in an increase in the average cart size by 5-10%, driven by the improved ability to explore relevant options.
  • Reduced Bounce Rate: A faster time to product discovery can significantly lower bounce rates. If users find what they’re looking for within a few interactions, they’re less likely to leave the site in frustration. A 10-20% reduction in bounce rate is possible, as fewer shoppers will abandon the site before completing their search.
  • Enhanced User Engagement: Although faster discovery may reduce the time a user spends on the site per session, the quality of engagement could improve. Customers would be more likely to interact with recommended products and explore additional categories, increasing the overall depth of their engagement. This could lead to higher click-through rates (CTR) on product recommendations by as much as 15-20%.
  • Operational Efficiency: By streamlining product discovery, shopperGPT could reduce the strain on customer support services, such as chatbots or help desks, as fewer users need assistance in finding products. This could decrease operational costs and enhance profitability.

Summary

Accelerating the time to product discovery by 10-20x would likely result in a 20-30% increase in conversion rates, a 5-10% increase in cart size, and a 10-20% reduction in both churn and bounce rates. These improvements collectively position the e-commerce site for significant growth in both customer satisfaction and revenue, making the shopping experience faster and more enjoyable for users.