Grupo Casas Bahia, an omnichannel retail conglomerate in Brazil, expanded its marketplace from thousands to millions of items and needed a more resilient search and recommendations layer.The company adopted Google Cloud Retail Search and Recommendations AI under Retail API to improve catalog updates, search relevance, and recommendation quality across its ecommerce brands.
Use case type
Shopping recommendations
This category uses AI to suggest products or offers based on customer behavior, preferences, and context. It helps improve product discovery and supports more relevant shopping experiences.
36
36
6
20 mo
Adoption over time
Documented cases per month
By case publish month · completed months only
29 cases documented across 37 months (Jul 23 – Jul 26), peaking at 4 in January 2024.
3 earlier cases before Jul 23 not shown
Each column counts every documented case of this type by its publish month, across the full corpus. The in-progress current month is excluded from columns and surfaced separately, and cases published before the charted window are summarized as earlier cases instead of plotted.
Company examples
Use cases of this type
10 shown from 36 use cases
CN2U.AI uses Gemini 2.5 Flash on Vertex AI to improve cross-border ecommerce search & recommendations
CN2U.AI is a cross-border ecommerce platform for international shoppers buying products from China at local prices or below.The company implemented chat-based product discovery and personalized recommendations powered by Gemini 2.5 Flash on Vertex AI to support multilingual search and persona-aware recommendations across more than 2 million products.The solution uses explainable, LLM-generated personas and contextual signals to rewrite queries in real time and improve discovery quality across Asia, Europe, and North America.
Strava delivers personalized insights through Athlete Intelligence powered by Claude in Amazon Bedrock.The feature helps users understand complex workout data such as pace, power, distance, and segments in a friendly, encouraging brand voice.Strava worked with AWS generative AI experts to select Claude Haiku and used Amazon Bedrock Guardrails to improve content safety and quality.
invos Group, a FinTech and MarTech company in Taiwan, leverages Google Cloud technologies including Vertex AI, Cloud SQL, and Google Kubernetes Engine to automate offline retail sales receipt data processing.
Wayfair leverages Google Cloud Gemini models and Gemini Enterprise Agent Platform to automate product catalog enrichment and enhance the home shopping experience.They co-develop Google's Universal Commerce Protocol to enable seamless, secure AI-agent based commerce interactions across platforms.The AI-powered Muse design tool and Discover tab improve personalized product discovery with photo-realistic room designs and natural language interaction.Wayfair improved product cataloging speed by 67%, enabling faster onboarding and richer information for 30M+ products.
Wesfarmers partners with Google Cloud to deploy agentic AI for enhanced retail customer experience and operational productivity
Wesfarmers, an Australian retail conglomerate, is collaborating with Google Cloud to deploy agentic AI solutions across its retail brands such as Kmart, Officeworks, Priceline, and OnePass.The initiative aims to create personalized shopping experiences, enhance AI-powered customer support, and empower employees with advanced AI tools.This multi-year collaboration includes AI upskilling programs tailored for various employee roles to facilitate confident and responsible AI use.
Frontier Firms Redefine Efficiency and Innovation Across Industries
This article explores how leading organizations—termed 'Frontier Firms'—are leveraging Microsoft technologies to transform business operations and outcomes across the automotive, manufacturing, and retail sectors. Mercedes-Benz uses a global production data platform in the Microsoft Cloud to optimize 30 car plants, enabling real-time analytics and energy savings. Dow implemented autonomous AI agents for shipping invoice analysis, reducing process times and identifying hidden losses in logistics. Ralph Lauren launched Ask Ralph, an Azure OpenAI-powered conversational agent offering styling advice and personal shopping recommendations, allowing customers to interact with the brand in new ways. These examples showcase adoption of AI agents, digital twins, IoT, and Copilot Studio to drive gains in efficiency, customer engagement, and sustainability. The article presents measurable impacts including millions in projected cost savings, energy reductions, and enhanced supply chain management. It highlights a trend toward custom, agentic AI solutions embedded across business functions, illustrating industry leadership in AI-first transformation.The piece also summarises an IDC study showing return on AI investments is three times higher for early adopters, and projects rapid growth in agentic AI adoption. As budgets for AI grow, these firms exemplify best practices in integrating AI to deliver concrete business results while overcoming challenges in security, scale, and ethics.
Walmart enhances retail experience with AI-powered Sparky assistant
Walmart has launched 'Sparky', an AI assistant integrated within its app to transform customer shopping experiences. Built using Microsoft Azure OpenAI Service, Sparky provides features such as summarizing product reviews, offering product recommendations, and helping users plan purchases. It will also support automated reordering of essentials and booking services, making routine tasks effortless for customers. Walmart previously released 'Wally', an AI assistant for its merchants. This rollout is part of ongoing AI investment and automation across Walmart's operations, aiming to streamline retail processes, increase customer engagement, and maintain Walmart's leadership in technological innovation. The move aligns with broader industry adoption, as other large retailers are advancing similar solutions. The article highlights Sparky's current functionality and future goals for deeper AI integration in retail.
Crédit Agricole and MAIF Enhance Insurance Services with Zelros AI Platform
Zelros developed an AI-powered platform for bank advisors and insurance agents, focused on personalizing customer interactions and improving workflow efficiencies. The platform leverages Microsoft Azure, deploying specialized AI and LLM models to enable secure, real-time recommendations for financial product distribution. Recognized as a Microsoft Partner of the Year, Zelros has secured adoption by major French insurance organizations.Crédit Agricole North of France saw measurable improvements in cross-selling and advisor performance. MAIF implemented the platform to diversify products and support advisors and managers with AI-enabled decision support. BPCE Assurances improved employee experiences with Zelros AI capabilities.The platform provides real-time recommendations and automates tasks for agents, supports both digital and in-person customer engagement, and ensures compliance and security through Azure.Zelros’ ecosystem approach makes it appealing for a variety of leading insurance and banking organizations. Its low-code, API-first architecture accelerates integration, with responsible AI principles ensuring high IT standards.
Walmart revolutionizes retail merchandising with generative AI assistant
Walmart implemented a generative AI assistant, named 'Wally,' using Azure AI and Azure OpenAI Service to improve merchant decision-making on product assortment, pricing, and inventory replenishment. The assistant integrates with Walmart's internal systems, enabling merchants to ask natural language questions and receive contextual, data-driven insights in real time. This eliminates the need for manual dashboard analysis and reduces reliance on analysts, speeding up operations. Wally reasons across various data inputs to provide consistent and agile decision support tailored to retail workflows. The deployment focuses on augmenting employee capabilities, leading to a more responsive and efficient merchandising process. The project addresses operational inefficiencies, inconsistency in decisions, and the time merchants spent gathering and analyzing data. It is part of Walmart’s broader strategy of infusing AI and automation into retail operations to boost responsiveness and profitability.
Common questions
Shopping recommendations at a glance
- How many shopping recommendations use cases are documented?
- The AI Use Case Hub documents 36 real shopping recommendations deployments across 6 industries, with 36 detailed company examples you can browse.
- Which industries adopt shopping recommendations the most?
- Shopping recommendations is most common in Retail (83%), Consumer & Food (6%) and Insurance (3%).
- Which countries lead in shopping recommendations?
- United States leads documented shopping recommendations deployments, followed by United Kingdom and Canada.
- What technologies are used for shopping recommendations?
- Teams most often build shopping recommendations with Azure OpenAI, Azure AI and Copilot.
- What AI capabilities power shopping recommendations?
- Across the documented deployments, the most common capability patterns are Agent (50%), Copilot (22%) and Vision (19%).
- What results do companies report from shopping recommendations?
- Across the 36 deployments reporting outcomes, companies most often cite customer experience & trust (92%), new product / capability (61%) and speed & agility (36%). Where impact is quantified, the strongest evidence is in other quantified impact: a median +28% across 5 reported metrics.