CXSimulator: A User Behavior Simulation using LLM Embeddings for Web-Marketing Campaign Assessment

This paper presents the Customer Experience (CX) Simulator, a We focus on the potential of LLMs to solve this issue. LLMs have novel framework designed to assess the effects of untested webmarketing been applied not only for natural language processing tasks [12] but campaigns through user behavior simulations. The proposed also for common sense reasoning in multi-modal data [34]. We believe framework leverages large language models (LLMs) to represent that the ability of LLMs, especially to represent the high-level various events in a user's behavioral history, such as viewing an semantics of complex event descriptions with compact embedded item, applying a coupon, or purchasing an item, as semantic embedding vectors (i.e., LLM embeddings) [15], can also be advantageous for vectors. We train a model to predict transitions between events web marketing applications from their LLM embeddings, which can even generalize to unseen In this work, we propose a novel framework named CXSimulator events by learning from diverse training data.