Enhance the customer experience with the help of an intelligent ChatBot
Wine advice using artificial intelligence
An established wine retailer wants to offer its customers easy and well-founded guidance when choosing wines — both in online shops and in stationary stores. The wide range of products combined with the frequent uncertainty among customers represents a particular challenge. Classic filter mechanisms and purely technical optimizations fall short here. Together with Etribes, an AI-based sommelier was therefore developed, which is based on comprehensive wine knowledge and provides individual, contextual recommendations. Particular attention was paid to seamless integration into the existing system landscape in order to create an intelligent, data-based customer experience that specifically improves the shopping experience.
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The aim of the project was to create an intelligent recommendation solution that seamlessly integrates into the wine retailer's digital ecosystem. Based on OpenAI technology, fine-tuned using wine knowledge databases, an architecture was built that is based on millions of wine data sets and structured knowledge. Customers can ask specific questions — such as the right wine accompaniment for a dish or about specific taste profiles — and receive well-founded answers in real time.
Technology implementation and integration
Etribes took over the design, implementation, monitoring and operation of the AI solution, with particular emphasis on user guidance and precise data preparation. The AI has been so fine-tuned that it not only reliably answers standard questions, but also interprets sophisticated search queries based on wine styles, aromas or preferences in a meaningful way. The minimally invasive integration into the company's existing architecture enabled the tool to be launched efficiently and without major hurdles.
Added value for customers and retailers
The introduction of the AI sommelier improves the customer experience in the long term: Customers receive personalized recommendations, while the wine retailer benefits from increased interaction and more targeted purchase decisions. The solution is particularly helpful where personal advice is not always available — whether in a local shop or when searching for the right wine online.
Ready for use prototypes in 5 weeks
Customer journey & use case concept:
Potential areas of application were identified as part of the online, offline and omnichannel journey. Based on this, a shortlist of relevant use cases was developed for the later test phase in the shop. Finally, specific recommendations for integrating these use cases into the existing shop design were developed.
Development and implementation:
Development of a service to connect to OpenAI that provides chatbot functionalities via clearly defined APIs. Product data is converted into embeddings using a large language model (LLM) and indexed in a vector database. In addition, an interactive chat interface was implemented in the frontend, which enables seamless user communication.
Handover & maintenance:
The last step was to create the documentation, which contains all relevant information about the project. The results were then handed over to the internal teams. Optionally, a maintenance and maintenance phase can also be provided. This includes necessary and regular updates, bug fixing and support for technical questions or problems.
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