概觀
AWS 零售能力合作夥伴提供尖端的產業技術解決方案和專家諮詢服務，讓零售商能夠在整個企業實現現代化並推動創新。他們的解決方案與服務涵蓋關鍵領域，例如客戶參與、供應鏈、數位商務、實體商店、資料分析和洞察，以及核心商業應用程式。這些經驗證的 AWS 合作夥伴提供久經考驗的解決方案與服務，可加速零售商的數位轉型之旅，使他們能夠維持競爭優勢並提供卓越的客戶體驗，從而促進消費者忠誠度和成長。
AWS 能力合作夥伴計畫旨在透過嫻熟的 AWS 技術專業知識和可靠的客戶成功經驗來識別、驗證和推廣 AWS 合作夥伴。 這些 AWS 合作夥伴已通過根植於 AWS Well-Architected Framework 的嚴格技術驗證，可在雲端設計、建置和操作可靠、安全和高效的解決方案。
依類別搜尋 AWS 零售能力合作夥伴
AWS 零售能力合作夥伴可讓零售商能夠在整個企業中加速其數位轉型，包括行銷、銷售、供應鏈、店鋪營運、財務和 IT。這些 AWS 合作夥伴的技術精通程度已經過驗證，且在下列其中一個或多個專業類別中已有零售客戶成功案例。
與 AWS 零售能力合作夥伴交流
AWS 零售能力合作夥伴提供採用 AWS 技術且創新的最佳零售解決方案和服務，以實現客戶參與、供應鏈、數位商務、商店、資料洞察和核心應用程式現代化。善用其產業和 AWS 專業知識，以及經驗證的客戶成功案例，加速您的轉型並提供卓越的購物體驗。
其他資源
探索更多的 AWS 零售合作夥伴解決方案和資源。
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Retail
Projeto Vitrine, da Natura, Unifica Plataforma de Pedidos para Cerca de 1 Milhão de Consultoras
BrazilDurante o processo de integração com a Avon, a Natura reconheceu uma oportunidade: evoluir a plataforma de captação de pedidos de forma a beneficiar as consultoras de ambas as marcas. Assim nasceu o Projeto Vitrine. Diferente das vitrines comuns de comércio eletrônico, esta plataforma foi cuidadosamente customizada para atender ao perfil individual de cada consultora, proporcionando uma experiência única e personalizada. Com a parceria AWS da CI&T, aliada à expertise da AWS, a Natura lançou com sucesso uma nova plataforma que não apenas serve mais de 1 milhão de consultoras, mas também se integra perfeitamente ao seu sistema legado de captação de pedidos. Este foi mais um passo significativo rumo à inovação e à excelência no atendimento, reafirmando o compromisso da Natura em impulsionar o crescimento e o sucesso de todas as suas consultoras.
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Retail
Darede revoluciona ofertas do Houpa com arquitetura serverless AWS
BrazilFundada em 2018, a startup Houpa, tem como missão levar a moda de todos para todos. Chegou inovando o jeito de comprar e vender roupas no atacado. Seu modelo de negócio foi validado pela quantidade de usuários cadastrados, pelo volume de transações realizadas, pela eficiência e facilidade de compra e venda que a solução entregava. Chegou a mais de 57 mil usuários cadastrados em sua plataforma entre marcas, multimarcas e consumidores finais. No meio do caminho a startup enfrentou a chamada “dor do crescimento” e, para adequar sua infraestrutura à velocidade de seu negócio, contou com o apoio da Parceiro AWS Darede para modernização de seu ambiente na nuvem AWS para uma arquitetura serverless.
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Retail
Mercado Libre Reshapes Retail Media with AWS Partner Mutt Data and Stability AI in Amazon Bedrock
ArgentinaMercado Libre has partnered with AWS Partner Mutt Data to address the challenge of producing high-performing banner ads with generative artificial intelligence (AI), for dozens of thousands of smaller sellers. Mercado Libre developed GenAds, an innovative solution that automates the creation of compelling product images, streamlining the process for sellers and enhancing their market presence with image-generating AI. Through GenAds, Mercado Libre helped small sellers through image generation for advertising, enabling sellers of all sizes to attract customers, increase click-through rates (CTR) by an average of 25%, and boost sales effectively.
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Retail
VMEngine and AWS Help Yeppon to 40% Savings and 30% Faster Web Performance
ItalyItalian ecommerce company Yeppon sells a range of goods from electronics to clothes and has a total inventory of over 400,000 items. In 7 years, it grew its sales from €1 million to €38.5 million but needed to improve its website to support its growth. The company turned to AWS Partner VMEngine for help with optimization, security, and automating processes to improve scalability. The migration cut 40 percent from IT costs while speeding up website performance by 30 percent.
*這些範例解決方案是零售能力使用案例範例，並未詳盡列出零售能力解決方案。
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Pivotree 提供的倉儲管理系統 (WMS) (18:32)Fluent Commerce 的 Fluent 訂單管理 (15:04)JBS Dev 的零售業 GenAI Quick Start POC (14:42)建構商的營收優化搜索與產品探索 (23:39)King Arthur 烘焙公司利用 AWS 上的 Talkdesk 將聯絡中心轉變為增長驅動力利用 AWS 上的 SAS Intelligent Planning 實現零售需求規劃現代化 (3:28)統一零售：AWS 及其合作夥伴開拓全通路體驗 (4:59)Pivotree SKU Build 透過 Amazon Bedrock 轉換產品資料，以實現無障礙商務。(2:32)XGEN AI 藉助生成式 AI 與 Amazon Bedrock 轉型電子商務 (3:02)利用 AWS 上的 JBS Dev、AI/ML 和生成式 AI 實現零售業現代化 (2:24)利用 Last Yard 的現代貨架邊促銷活動，在購買時轉化購物者 (1:50)Peak AI 如何從 AWS 零售合作夥伴能力獲得受益 (2:06)
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Justin Swagler, 2025年4月16日Physical retailing – driving 80 percent of all US sales – is undergoing a “Renaissance”; a modernization revolution focused on transforming both shopper experience and operations. To achieve this, stores are re-investing heavily in technology, from point-of-sale systems and inventory management to IoT devices and computer vision solutions. Yet these investments often create what IDC [...]
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Justin Swagler, Richard Elberger, 2025年4月3日With physical stores still accounting for 80 percent of sales, the pressure to optimize in-store operations has never been more intense. The rise of ecommerce hasn’t just changed shopping habits—it’s created an urgent need for physical stores to deliver smarter, more efficient store experiences while reducing their technology footprint. Physical store companies commonly face the [...]
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Jason Schamp, Andrew Painter, Moulee Natarajan, 2025年3月21日Retail customers are improving the in-store customer experience through personalization by connecting their remote stores to AWS using SD-WAN. For the largest specialty consumer electronics retailer in North America, Best Buy Co., Inc., connecting stores to cloud-based workloads has shortened application response times. It allows stores to sync up-to-date inventory, view real-time supply chain information [...]
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Rajashree Rane, 2025年3月21日I’m still thinking back to this past January, when Amazon Web Services (AWS) hosted 95 of EMEA’s leading retailers and partners in New York for its Future of Retail event. Retail giants such as Max Mara Fashion Group, ASICS, S-Group, and Illum attended to share their digital transformation journeys and future vision for the industry. [...]
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Aman Shanbhag, Michael Lue, Vineet Kacchawaha, 2025年3月11日In this post, we walk through how to build the FoodSavr solution (fictitious name used for the purposes of this post) using Amazon Rekognition Custom Labels to detect the ingredients and generate personalized recipes using Anthropic’s Claude 3.0 on Amazon Bedrock. We demonstrate an end-to-end architecture where a user can upload an image of their fridge, and using the ingredients found there (detected by Amazon Rekognition), the solution will give them a list of recipes (generated by Amazon Bedrock). The architecture also recognizes missing ingredients and provides the user with a list of nearby grocery stores.