Architecture Design of GenAI Chatbox Sales Interaction System Based on Big Data

In response to the bottleneck problems of large-scale data processing and response speed faced by modern enterprises in customer service and sales, this paper introduces the GenAI Chatbox sales interaction system based on big data and generative artificial intelligence (GenAI) technology, aiming to improve sales efficiency through intelligent sales interaction. First, the GenAI Chatbox sales interaction system is built based on data collection and preprocessing, personalized recommendation system, and generative dialogue system. The system uses big data technology to mine customer behavior, purchasing habits, historical transaction records, etc., and extract potential customer needs and market trends. Secondly, based on the GenAI model, the system can automatically generate personalized sales responses through NLP (Natural Language Processing) technology when receiving user inquiries, and provide real-time sales recommendations and solutions. Finally, the LSTM (Long Short Term Memory) algorithm is used to continuously optimize the Chatbox, constantly learn and adapt to changes in customer needs, so as to improve the accuracy of interaction and customer experience. By introducing big data analysis and GenAI technology, the sales interaction system can effectively improve the work efficiency of the sales team, reduce manual intervention, and optimize customer service processes. Precision@10 ranges from 0.75 to 0.90, Recall@10 ranges from 0.70 to 0.85, and each user receives 10 recommended products, with the actual number of purchased products ranging from 7 to 12. The GenAI Chatbox sales interaction system can not only improve the sales efficiency of enterprises, but also provide customers with more personalized and efficient services.