Tchibo brews up 10x faster customer insights with AlloyDB for PostgreSQL

In today’s competitive retail world, understanding your customers and making data-driven decisions is key to success. Tchibo, one of the world’s leading retailers, has demonstrated this by leveraging the power of Google Cloud AlloyDB for PostgreSQL. This case study takes you through Tchibo’s 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’s explore this inspiring success story!

Tchibo and the transition to AlloyDB

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.

In this guest post from Henning Kosmalla and Dominik Nowatschin, we learn how Tchibo’s migration accelerated feedback analysis by 10x, empowering Tchibo’s teams to react quickly to customer needs and reinforcing the company’s commitment to customer-centric innovation.

“At Tchibo, we're not just about coffee — we're constantly finding new ways to connect with our customers.”

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—from clothing to kitchenware—that offer “a new world every week.”

Nhưng không phải lúc nào cũng suôn sẻ. Những thách thức toàn cầu ngày càng gia tăng, từ lạm phát đến những kỳ vọng mới do AI điều khiển của khách hàng, đòi hỏi Tchibo phải đưa ra các quyết định dựa trên dữ liệu một cách nhanh chóng để duy trì tính cạnh tranh. Giải pháp cơ sở dữ liệu đám mây trước đây của Tchibo có thể xử lý việc truy xuất dữ liệu cơ bản, nhưng nó không thể theo kịp quy mô và độ phức tạp của dữ liệu mà họ dựa vào trên cả ba kênh bán hàng của mình. Khi nhu cầu dữ liệu tăng lên, doanh nghiệp phải đối mặt với một số vấn đề: tốc độ truy vấn chậm lại, điều này làm chậm trễ việc truy cập dữ liệu khách hàng, Tchibo phải chịu đựng việc phản hồi tốn nhiều công sức và gặp khó khăn trong việc trích xuất thông tin chi tiết hữu ích từ các nguồn dữ liệu đa dạng.

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’s why Tchibo turned to AlloyDB—to power insights that put customers at the center of every decision the business makes.

How AlloyDB Finds the Perfect Blend of Speed ​​and Scale

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’s 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, “How do customers feel about our new coffee pods?” with concise, actionable summaries.

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’s how AlloyDB supports specific needs:

• 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. “return all reviews with positive sentiment”) as well as nearest neighbor (NN) searches using embedded columns to add depth and relevance to the data.
• Query Interpretation: When an agent asks a Customer Voice assistant a question, a large language model (LLM) — currently Claude 3.5 Sonnet on Vertex AI — interprets the query, identifying core topics like product or category to provide a relevant, targeted answer.
• 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.
• 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.

Deliver data perfectly to drive decision making with AlooyDB

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.

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’s commitment to staying connected to customer needs and preferences in real time.

Furthermore, AlloyDB’s fully managed operations reduced operational costs, simplifying Tchibo’s 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.

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.

Conclusion

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 Google Cloud 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.

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 Gimasys – Google Cloud Premier Partner for detailed advice.