List of Google Recommendations AI Customers
Google
1600 Amphitheatre Parkway,
Mountain View, 94043, CA,
United States
Mountain View, 94043, CA,
United States
1 650-253-0000
Communications
190820
$402.8B
Since 2010, our global team of researchers has been studying Google Recommendations AI customers around the world, aggregating massive amounts of data points that form the basis of our forecast assumptions and perhaps the rise and fall of certain vendors and their products on a quarterly basis.
Each quarter our research team identifies companies that have purchased Google Recommendations AI for Personalization and Product Recommendations from public (Press Releases, Customer References, Testimonials, Case Studies and Success Stories) and proprietary sources, including the customer size, industry, location, implementation status, partner involvement, LOB Key Stakeholders and related IT decision-makers contact details.
Companies using Google Recommendations AI for Personalization and Product Recommendations include: Estee Lauder, a United States based Consumer Packaged Goods organisation with 40470 employees and revenues of $14.33 billion, Bennet, a Italy based Retail organisation with 8000 employees and revenues of $1.91 billion, Stradivarius Romania, a Romania based Retail organisation with 1942 employees and revenues of $650.0 million, LightInTheBox, a Singapore based Retail organisation with 971 employees and revenues of $503.0 million, IHOP, a United States based Retail organisation with 5000 employees and revenues of $480.0 million and many others.
Contact us if you need a completed and verified list of companies using Google Recommendations AI, including the breakdown by industry (21 Verticals), Geography (Region, Country, State, City), Company Size (Revenue, Employees, Asset) and related IT Decision Makers, Key Stakeholders, business and technology executives responsible for the software purchases.
The Google Recommendations AI customer wins are being incorporated in our Enterprise Applications Buyer Insight and Technographics Customer Database which has over 100 data fields that detail company usage of software systems and their digital transformation initiatives. Apps Run The World wants to become your No. 1 technographic data source!
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| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Application | Category | When | SI | Insight |
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Bennet | Retail | 8000 | $1.9B | Italy | Google Recommendations AI | Personalization and Product Recommendations | 2022 | n/a |
In 2022, Bennet implemented Google Recommendations AI to power on-site personalization on its website. The deployment aligns with the Personalization and Product Recommendations category and targets on-site merchandising and personalized customer browsing on Bennet's Italian e-commerce presence.
The implementation of Google Recommendations AI centered on catalog ingestion, model training, and real-time inference capabilities. Configuration emphasized personalized ranking and item-to-item recommendations to surface relevant SKUs during browsing and add-to-cart flows, using Google Recommendations AI model workflows for candidate generation and ranking.
Architecture was implemented as a recommendation service feeding Bennet's storefront, with product catalog feeds synchronized to the recommendation models and inference delivered at page render time to product pages and category pages. The Google Recommendations AI instance is integrated directly into the website experience to deliver contextual suggestions and maintain SKU mapping between Bennet's catalog and the recommendation engine.
Operationally the rollout focused on e-commerce and merchandising teams, with phased deployment across product categories on the Bennet site in Italy. Governance practices included catalog synchronization routines and periodic model retraining to align recommendations with current assortment, positioning Google Recommendations AI as the core personalization engine for Bennet's online product discovery.
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Candere By Kalyan Jewellers | Retail | 50 | $5M | India | Google Recommendations AI | Personalization and Product Recommendations | 2022 | n/a |
In 2022, Candere By Kalyan Jewellers implemented Google Recommendations AI on their public e-commerce website. Google Recommendations AI in the Personalization and Product Recommendations category was provisioned as a cloud-hosted recommendation service to deliver on-site personalization and product merchandising for the company’s online storefront.
The implementation used catalog ingestion and user event ingestion pipelines to feed Google Recommendations AI models, with real-time inference endpoints embedded in product detail pages, category listings, and cart interactions. Configuration emphasized model tuning, merchandising rules, and experimentation controls to govern recommendation relevance, with operational ownership assigned to e-commerce and merchandising teams. Integrations were focused on the website front-end and site event streams to enable personalized recommendation workflows without introducing additional named third-party systems.
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Carrefour Egypt | Retail | 7000 | $422M | Egypt | Google Recommendations AI | Personalization and Product Recommendations | 2023 | n/a |
In 2023, Carrefour Egypt deployed Google Recommendations AI on its ecommerce website. Google Recommendations AI is provisioned as the Personalization and Product Recommendations engine for on-site product discovery, personalized product ranking, and contextual merchandising. Carrefour Egypt uses Google Recommendations AI to support ecommerce product discovery and merchandising workflows on its site serving Egypt.
The implementation integrates the Recommendations AI runtime via API calls from the storefront, consuming a product catalog feed and user interaction signals to generate real-time recommendations and ranking. Functional capabilities implemented include product-to-product recommendations, personalized ranking for search and category listings, and catalog ingestion to support model training and periodic retraining. Operational scope focuses on the online retail storefront and merchandising teams, with governance centered on catalog feed management, personalization rule configuration, and monitoring of recommendation quality.
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Country Road | Professional Services | 10 | $1M | United States | Google Recommendations AI | Personalization and Product Recommendations | 2022 | n/a |
In 2022, Country Road deployed Google Recommendations AI on its website. The 2022 implementation uses Google Recommendations AI in the Personalization and Product Recommendations category to deliver on-site product suggestions and personalized ranking for customers browsing the online catalog.
The implementation architecture pairs front-end recommendation widgets embedded in the website with server-side catalog ingestion and event collection that feed Google Recommendations AI for model training and real-time inference. Functional capabilities implemented include catalog schema mapping, user event capture for views and add-to-cart signals, automated model training and personalized ranking, and inference endpoints that serve contextual product recommendations.
Operational coverage is focused on the Country Road website and impacts merchandising and marketing workflows around product discovery and on-site personalization. Governance measures center on catalog attribute curation, configuration of recommendation parameters and retraining cadence, and instrumentation of site events to ensure continuous model input and maintenance.
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Estee Lauder | Consumer Packaged Goods | 40470 | $14.3B | United States | Google Recommendations AI | Personalization and Product Recommendations | 2023 | n/a |
In 2023, Estee Lauder implemented Google Recommendations AI to power Personalization and Product Recommendations on its website. The deployment uses Google Recommendations AI as a cloud native recommendation service that delivers real time personalized product suggestions to web storefront touchpoints and commerce pages.
The implementation includes standard recommendation workflows aligned to the Personalization and Product Recommendations category, including catalog ingestion and feature mapping, eventing of user interactions for model training, automated model training and tuning, and a real time serving layer for personalized ranking. Configuration emphasizes item metadata, session and user signal capture, and recommendation slot configuration to support product detail, category, and cross sell placements.
Integration work focused on embedding Google Recommendations AI into Estee Lauder online commerce touchpoints, routing catalog updates and clickstream events into the recommendation pipeline, and exposing the recommendations via the storefront front end. Operational coverage is centered on the corporate ecommerce site and associated merchandising workflows, with data flows leveraging the vendor provided serving and model management endpoints.
Governance and rollout were organized around ecommerce and digital merchandising teams, using phased activation and control points for recommendation slots and merchandising overrides. Implementation practices emphasize catalog hygiene, event quality monitoring, and iterative model tuning to maintain relevance in product recommendations.
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Retail | 14 | $6M | Greece | Google Recommendations AI | Personalization and Product Recommendations | 2022 | n/a |
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Retail | 5000 | $480M | United States | Google Recommendations AI | Personalization and Product Recommendations | 2023 | n/a |
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Retail | 100 | $10M | United States | Google Recommendations AI | Personalization and Product Recommendations | 2022 | n/a |
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Retail | 971 | $503M | Singapore | Google Recommendations AI | Personalization and Product Recommendations | 2022 | n/a |
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Media | 10 | $1M | United States | Google Recommendations AI | Personalization and Product Recommendations | 2022 | n/a |
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Showing 1 to 10 of 18 entries
Buyer Intent: Companies Evaluating Google Recommendations AI
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| Logo | Company | Industry | Employees | Revenue | Country | Evaluated | ||
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FAQ - APPS RUN THE WORLD Google Recommendations AI Coverage
Google Recommendations AI is a Personalization and Product Recommendations solution from Google.
Companies worldwide use Google Recommendations AI, from small firms to large enterprises across 21+ industries.
Organizations such as Estee Lauder, Bennet, Stradivarius Romania, LightInTheBox and IHOP are recorded users of
Google Recommendations AI for Personalization and Product Recommendations.
Companies using Google Recommendations AI are most concentrated in Consumer Packaged Goods and Retail, with adoption spanning over 21 industries.
Companies using Google Recommendations AI are most concentrated in United States, Italy and Romania, with adoption tracked across 195 countries worldwide. This global distribution highlights the popularity of Google Recommendations AI across Americas, EMEA, and APAC.
Companies using Google Recommendations AI range from small businesses with 0-100 employees - 38.89%, to mid-sized firms with 101-1,000 employees - 33.33%, large organizations with 1,001-10,000 employees - 22.22%, and global enterprises with 10,000+ employees - 5.56%.
Customers of Google Recommendations AI include firms across all revenue levels — from $0-100M, to $101M-$1B, $1B-$10B, and $10B+ global corporations.
Contact APPS RUN THE WORLD to access the full verified Google Recommendations AI customer database with detailed Firmographics such as industry, geography, revenue, and employee breakdowns as well as key decision makers in charge of Personalization and Product Recommendations.