{"id":21439,"date":"2025-02-26T16:12:07","date_gmt":"2025-02-26T09:12:07","guid":{"rendered":"https:\/\/gcloudvn.com\/?p=21439"},"modified":"2025-02-26T16:12:07","modified_gmt":"2025-02-26T09:12:07","slug":"tchibo-brews-up-10x-faster-customer-insights-with-alloydb-for-postgresql","status":"publish","type":"post","link":"https:\/\/gcloudvn.com\/en\/kienthuc\/tchibo-brews-up-10x-faster-customer-insights-with-alloydb-for-postgresql\/","title":{"rendered":"Tchibo brews up 10x faster customer insights with AlloyDB for PostgreSQL"},"content":{"rendered":"<p>In today\u2019s competitive retail world, understanding your customers and making data-driven decisions is key to success. Tchibo, one of the world\u2019s leading retailers, has demonstrated this by leveraging the power of Google Cloud AlloyDB for PostgreSQL. This case study takes you through Tchibo\u2019s journey to transform their database system, from the challenges they faced to the impressive results they achieved. In particular, you will see how Tchibo increased the speed of collecting customer insights by 10x, helping them make faster and more effective business decisions. Let\u2019s explore this inspiring success story!<\/p>\n<p><a href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/tchibo-brews-up-10x-faster-customer-insights-with-alloydb-for-postgresql\/attachment\/thang-72024-2025-02-26t103400-885\/\" rel=\"attachment wp-att-21446\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-21446\" src=\"https:\/\/gcloudvn.com\/wp-content\/uploads\/2025\/02\/Thang-72024-2025-02-26T103400.885.jpg\" alt=\"\" width=\"600\" height=\"375\" srcset=\"https:\/\/gcloudvn.com\/wp-content\/uploads\/2025\/02\/Thang-72024-2025-02-26T103400.885.jpg 600w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2025\/02\/Thang-72024-2025-02-26T103400.885-18x12.jpg 18w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><\/a><\/p>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_80 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/tchibo-brews-up-10x-faster-customer-insights-with-alloydb-for-postgresql\/#Tchibo_va_qua_trinh_chuyen_doi_sang_AlloyDB\" >Tchibo and the transition to AlloyDB<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/tchibo-brews-up-10x-faster-customer-insights-with-alloydb-for-postgresql\/#Cach_AlloyDB_tim_kiem_su_ket_hop_hoan_hao_giua_toc_do_va_quy_mo\" >How AlloyDB Finds the Perfect Blend of Speed \u200b\u200band Scale<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/tchibo-brews-up-10x-faster-customer-insights-with-alloydb-for-postgresql\/#Cung_cap_du_lieu_mot_cach_hoan_hao_de_thuc_day_qua_trinh_ra_quyet_dinh_cung_AlooyDB\" >Deliver data perfectly to drive decision making with AlooyDB<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/tchibo-brews-up-10x-faster-customer-insights-with-alloydb-for-postgresql\/#Ket_luan\" >Conclusion<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"Tchibo_va_qua_trinh_chuyen_doi_sang_AlloyDB\"><\/span>Tchibo and the transition to AlloyDB<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">Tchibo, a popular coffee retailer and lifestyle brand based in Germany, needed a faster, smarter way to manage and interpret large volumes of customer feedback across its diverse products and sales channels. To meet this need, they adopted the AlloyDB for PostgreSQL database, leveraging its advanced analytics and AI capabilities to streamline data retrieval and deliver real-time insights.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In this guest post from Henning Kosmalla and Dominik Nowatschin, we learn how Tchibo\u2019s migration accelerated feedback analysis by 10x, empowering Tchibo\u2019s teams to react quickly to customer needs and reinforcing the company\u2019s commitment to customer-centric innovation.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">\u201cAt Tchibo, we're not just about coffee \u2014 we're constantly finding new ways to connect with our customers.\u201d<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Tchibo has evolved from a coffee-focused business into an omnichannel retail model, spanning its own stores, e-commerce, and grocery store aisles. This setup allows them to cater to a diverse customer base, each with their own needs and preferences, while also offering an ever-growing selection of non-food items\u2014from clothing to kitchenware\u2014that offer \u201ca new world every week.\u201d<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Nh\u01b0ng kh\u00f4ng ph\u1ea3i l\u00fac n\u00e0o c\u0169ng su\u00f4n s\u1ebb. Nh\u1eefng th\u00e1ch th\u1ee9c to\u00e0n c\u1ea7u ng\u00e0y c\u00e0ng gia t\u0103ng, t\u1eeb l\u1ea1m ph\u00e1t \u0111\u1ebfn nh\u1eefng k\u1ef3 v\u1ecdng m\u1edbi do AI \u0111i\u1ec1u khi\u1ec3n c\u1ee7a kh\u00e1ch h\u00e0ng, \u0111\u00f2i h\u1ecfi Tchibo ph\u1ea3i \u0111\u01b0a ra c\u00e1c quy\u1ebft \u0111\u1ecbnh d\u1ef1a tr\u00ean d\u1eef li\u1ec7u m\u1ed9t c\u00e1ch nhanh ch\u00f3ng \u0111\u1ec3 duy tr\u00ec t\u00ednh c\u1ea1nh tranh. Gi\u1ea3i ph\u00e1p c\u01a1 s\u1edf d\u1eef li\u1ec7u \u0111\u00e1m m\u00e2y tr\u01b0\u1edbc \u0111\u00e2y c\u1ee7a Tchibo c\u00f3 th\u1ec3 x\u1eed l\u00fd vi\u1ec7c truy xu\u1ea5t d\u1eef li\u1ec7u c\u01a1 b\u1ea3n, nh\u01b0ng n\u00f3 kh\u00f4ng th\u1ec3 theo k\u1ecbp quy m\u00f4 v\u00e0 \u0111\u1ed9 ph\u1ee9c t\u1ea1p c\u1ee7a d\u1eef li\u1ec7u m\u00e0 h\u1ecd d\u1ef1a v\u00e0o tr\u00ean c\u1ea3 ba k\u00eanh b\u00e1n h\u00e0ng c\u1ee7a m\u00ecnh. Khi nhu c\u1ea7u d\u1eef li\u1ec7u t\u0103ng l\u00ean, doanh nghi\u1ec7p ph\u1ea3i \u0111\u1ed1i m\u1eb7t v\u1edbi m\u1ed9t s\u1ed1 v\u1ea5n \u0111\u1ec1: t\u1ed1c \u0111\u1ed9 truy v\u1ea5n ch\u1eadm l\u1ea1i, \u0111i\u1ec1u n\u00e0y l\u00e0m ch\u1eadm tr\u1ec5 vi\u1ec7c truy c\u1eadp d\u1eef li\u1ec7u kh\u00e1ch h\u00e0ng, Tchibo ph\u1ea3i ch\u1ecbu \u0111\u1ef1ng vi\u1ec7c ph\u1ea3n h\u1ed3i t\u1ed1n nhi\u1ec1u c\u00f4ng s\u1ee9c v\u00e0 g\u1eb7p kh\u00f3 kh\u0103n trong vi\u1ec7c tr\u00edch xu\u1ea5t th\u00f4ng tin chi ti\u1ebft h\u1eefu \u00edch t\u1eeb c\u00e1c ngu\u1ed3n d\u1eef li\u1ec7u \u0111a d\u1ea1ng.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Queries often took more than 10 seconds, even for simple insights. And compiling customer feedback reports required up to three days of manual work to sort, categorize, and analyze. Tchibo also lacked the flexibility to support advanced, AI-driven applications. This limited their ability to deploy innovative tools like retrieval-augmented generation (RAG) workflows, which combine structured and unstructured data to gain deeper context in AI queries. That\u2019s why Tchibo turned to AlloyDB\u2014to power insights that put customers at the center of every decision the business makes.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Cach_AlloyDB_tim_kiem_su_ket_hop_hoan_hao_giua_toc_do_va_quy_mo\"><\/span><b>How AlloyDB Finds the Perfect Blend of Speed \u200b\u200band Scale<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">AlloyDB provided a powerful solution to the limitations Tchibo faced with its legacy database. Advanced analytics, built-in vector search, and a familiar PostgreSQL platform provided the speed, adaptability, and usability businesses needed to deliver insights as fast and fresh as coffee. One of Tchibo\u2019s most impactful applications, Customer Voice, gives employees instant access to relevant customer feedback. The tool aggregates data from product reviews and other sources into actionable summaries, answering questions like, \u201cHow do customers feel about our new coffee pods?\u201d with concise, actionable summaries.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">AlloyDB serves as the foundation of the Customer Voice application, managing a complete data pipeline to support real-time feedback analysis. Its architecture efficiently handles data storage, search, and query processing, so Tchibo teams can gain fresh insights from customer insights. Here\u2019s how AlloyDB supports specific needs:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Data Storage: AlloyDB organizes customer feedback and product descriptions in a flexible structure that supports both standard and advanced queries. This setup allows Tchibo to run traditional queries (e.g. \u201creturn all reviews with positive sentiment\u201d) as well as nearest neighbor (NN) searches using embedded columns to add depth and relevance to the data.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Query Interpretation: When an agent asks a Customer Voice assistant a question, a large language model (LLM) \u2014 currently Claude 3.5 Sonnet on Vertex AI \u2014 interprets the query, identifying core topics like product or category to provide a relevant, targeted answer.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Retrieval and filtering: AlloyDB combines structured queries, NN searches, and re-ranking\/filtering steps to retrieve relevant reviews. LLM further enriches the data with clustering and summary statistics, providing a complete view of customer sentiment.<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">Presentation: Customer Voice delivers these insights through a streamlined interface that highlights individual reviews, key statistics, and summaries, making it easy for employees to act on the information.<\/span><\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Cung_cap_du_lieu_mot_cach_hoan_hao_de_thuc_day_qua_trinh_ra_quyet_dinh_cung_AlooyDB\"><\/span><b>Deliver data perfectly to drive decision making with AlooyDB<\/b><span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><span style=\"font-weight: 400;\">AlloyDB transformed Tchibo's approach to data by enabling faster, deeper, and more scalable access to the customer feedback and analytics they rely on to make decisions.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Supporting high-performance analytics and RAG workflows, AlloyDB now delivers near-instant insights. Complex queries that previously took up to 10 seconds now return results in about a second, enabling faster data-driven decisions across teams. Generating detailed customer feedback reports that previously took days of manual effort now takes seconds with AlloyDB. This leap has reinforced Tchibo\u2019s commitment to staying connected to customer needs and preferences in real time.<\/span><\/p>\n<p><span style=\"font-weight: 400;\"><a href=\"https:\/\/gcloudvn.com\/en\/kienthuc\/tchibo-brews-up-10x-faster-customer-insights-with-alloydb-for-postgresql\/attachment\/thang-72024-2025-02-26t103513-001\/\" rel=\"attachment wp-att-21445\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter size-full wp-image-21445\" src=\"https:\/\/gcloudvn.com\/wp-content\/uploads\/2025\/02\/Thang-72024-2025-02-26T103513.001.jpg\" alt=\"\" width=\"600\" height=\"375\" srcset=\"https:\/\/gcloudvn.com\/wp-content\/uploads\/2025\/02\/Thang-72024-2025-02-26T103513.001.jpg 600w, https:\/\/gcloudvn.com\/wp-content\/uploads\/2025\/02\/Thang-72024-2025-02-26T103513.001-18x12.jpg 18w\" sizes=\"auto, (max-width: 600px) 100vw, 600px\" \/><\/a>Furthermore, AlloyDB\u2019s fully managed operations reduced operational costs, simplifying Tchibo\u2019s ability to scale as data demands increased. While continuity was not a primary concern for businesses when choosing AlloyDB, its 99.99% availability SLA provided valuable reliability to support long-term goals.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">In addition to Customer Voice, AlloyDB also supports broader AI initiatives, such as internal chatbots for intranet queries, giving Tchibo the flexibility to scale different retrieval augmentation (RAG) use cases efficiently across the organization. In the future, Google is exploring the extensibility of AlloyDB to integrate more structured and unstructured data into its analytics. Working with Google Cloud, Tchibo is in a position to explore new data solutions to deliver richer insights, driving growth and innovation at Tchibo.<\/span><\/p>\n<h2><span class=\"ez-toc-section\" id=\"Ket_luan\"><\/span>Conclusion<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p data-sourcepos=\"1:1-1:366\">In short, Tchibo's success story is a clear testament to the power of digital transformation and the application of modern technology in business operations. By choosing <a href=\"https:\/\/gcloudvn.com\/en\/google-cloud-platform\/\">Google Cloud<\/a> AlloyDB for PostgreSQL, Tchibo not only solves the problem of database performance but also opens up opportunities to exploit customer data more comprehensively and efficiently.<\/p>\n<p data-sourcepos=\"3:1-3:459\">Collecting customer insights 10 times faster has helped Tchibo make faster, more agile and more accurate business decisions, thereby improving customer experience and increasing competitive advantage in the market. This is a valuable lesson for businesses, especially in the retail sector, about the importance of investing in data infrastructure and applying advanced technology solutions for sustainable development. If your business needs to learn more about AlloyDB or learn about applications that can change your business, please contact <a href=\"https:\/\/gcloudvn.com\/en\/\">Gimasys<\/a> \u2013 Google Cloud Premier Partner for detailed advice.<\/p>\n<p>&nbsp;<\/p>","protected":false},"excerpt":{"rendered":"<p>Trong th\u1ebf gi\u1edbi b\u00e1n l\u1ebb c\u1ea1nh tranh kh\u1ed1c li\u1ec7t ng\u00e0y nay, vi\u1ec7c hi\u1ec3u r\u00f5 kh\u00e1ch h\u00e0ng v\u00e0 \u0111\u01b0a ra quy\u1ebft \u0111\u1ecbnh d\u1ef1a tr\u00ean d\u1eef li\u1ec7u l\u00e0 y\u1ebfu t\u1ed1 then ch\u1ed1t \u0111\u1ec3 th\u00e0nh c\u00f4ng. Tchibo, m\u1ed9t trong nh\u1eefng nh\u00e0 b\u00e1n l\u1ebb&hellip;<\/p>","protected":false},"author":2,"featured_media":21445,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"inline_featured_image":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-21439","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-kienthuc","entry","has-media"],"_links":{"self":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts\/21439","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/comments?post=21439"}],"version-history":[{"count":0,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/posts\/21439\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/media\/21445"}],"wp:attachment":[{"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/media?parent=21439"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/categories?post=21439"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/gcloudvn.com\/en\/wp-json\/wp\/v2\/tags?post=21439"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}