# LLM-Driven E-Commerce Marketing Content Optimization: Balancing Creativity and Conversion

arXiv: https://arxiv.org/abs/2505.23809 · HTML: https://mlsanity.com/paper/2505.23809/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- Builds on 33 of its 57 references that are in the map.
- First posted on arXiv 27 May 2025.

## Builds on (most cited first, 30 of 33)

- [LLM Maybe LongLM: Self-Extend LLM Context Window Without Tuning](https://mlsanity.com/paper/2401.01325/) (2024)
- [Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey](https://mlsanity.com/paper/2412.20367/) (2024)
- [LLM-based NLG Evaluation: Current Status and Challenges](https://mlsanity.com/paper/2402.01383/) (2024)
- [Time Series Modeling for Heart Rate Prediction: From ARIMA to Transformers](https://mlsanity.com/paper/2406.12199/) (2024)
- [From Mind to Machine: The Rise of Manus AI as a Fully Autonomous Digital Agent](https://mlsanity.com/paper/2505.02024/) (2025)
- [Harnessing Earnings Reports for Stock Predictions: A QLoRA-Enhanced LLM Approach](https://mlsanity.com/paper/2408.06634/) (2024)
- [Deep Learning-based Anomaly Detection and Log Analysis for Computer Networks](https://mlsanity.com/paper/2407.05639/) (2024)
- [Research on Splicing Image Detection Algorithms Based on Natural Image Statistical Characteristics](https://mlsanity.com/paper/2404.16296/) (2024)
- [Enhance Image-to-Image Generation with LLaVA-generated Prompts](https://mlsanity.com/paper/2406.01956/) (2024)
- [Attention Mechanism and Context Modeling System for Text Mining Machine Translation](https://mlsanity.com/paper/2408.04216/) (2024)
- [A Neural Matrix Decomposition Recommender System Model based on the Multimodal Large Language Model](https://mlsanity.com/paper/2407.08942/) (2024)
- [Machine Learning-Based Research on the Adaptability of Adolescents to Online Education](https://mlsanity.com/paper/2408.16849/) (2024)
- [DRAL: Deep Reinforcement Adaptive Learning for Multi-UAVs Navigation in Unknown Indoor Environment](https://mlsanity.com/paper/2409.03930/) (2024)
- [Deep Learning for Weather Forecasting: A CNN-LSTM Hybrid Model for Predicting Historical Temperature Data](https://mlsanity.com/paper/2410.14963/) (2024)
- [Real-Time Prediction for Athletes' Psychological States Using BERT-XGBoost: Enhancing Human-Computer Interaction](https://mlsanity.com/paper/2412.05816/) (2024)
- [Data Augmentation Through Random Style Replacement](https://mlsanity.com/paper/2504.10563/) (2025)
- [Contextual Bandits for Unbounded Context Distributions](https://mlsanity.com/paper/2408.09655/) (2024)
- [Research on Effectiveness Evaluation and Optimization of Baseball Teaching Method Based on Machine Learning](https://mlsanity.com/paper/2411.15721/) (2024)
- [Multidimensional precipitation index prediction based on CNN-LSTM hybrid framework](https://mlsanity.com/paper/2504.20442/) (2025)
- [Personalized Risks and Regulatory Strategies of Large Language Models in Digital Advertising](https://mlsanity.com/paper/2505.04665/) (2025)
- [User Behavior Analysis in Privacy Protection with Large Language Models: A Study on Privacy Preferences with Limited Data](https://mlsanity.com/paper/2505.06305/) (2025)
- [CCi-YOLOv8n: Enhanced Fire Detection with CARAFE and Context-Guided Modules](https://mlsanity.com/paper/2411.11011/) (2024)
- [Accurate Prediction of Temperature Indicators in Eastern China Using a Multi-Scale CNN-LSTM-Attention model](https://mlsanity.com/paper/2412.07997/) (2024)
- [Optimized Path Planning for Logistics Robots Using Ant Colony Algorithm under Multiple Constraints](https://mlsanity.com/paper/2504.05339/) (2025)
- [Psychological Health Knowledge-Enhanced LLM-based Social Network Crisis Intervention Text Transfer Recognition Method](https://mlsanity.com/paper/2504.07983/) (2025)
- [II-NVM: Enhancing Map Accuracy and Consistency with Normal Vector-Assisted Mapping](https://mlsanity.com/paper/2504.08204/) (2025)
- [Avocado Price Prediction Using a Hybrid Deep Learning Model: TCN-MLP-Attention Architecture](https://mlsanity.com/paper/2505.09907/) (2025)
- [CTLformer: A Hybrid Denoising Model Combining Convolutional Layers and Self-Attention for Enhanced CT Image Reconstruction](https://mlsanity.com/paper/2505.12203/) (2025)
- [A CT Image Classification Network Framework for Lung Tumors Based on Pre-trained MobileNetV2 Model and Transfer learning, And Its Application and Market Analysis in the Medical field](https://mlsanity.com/paper/2501.04996/) (2025)
- [Research on Personalized Medical Intervention Strategy Generation System based on Group Relative Policy Optimization and Time-Series Data Fusion](https://mlsanity.com/paper/2504.18631/) (2025)

## Built on by (most cited first, 7 of 7)

- [Meta-Learning for Cold-Start Personalization in Prompt-Tuned LLMs](https://mlsanity.com/paper/2507.16672/) (2025)
- [RLHF Fine-Tuning of LLMs for Alignment with Implicit User Feedback in Conversational Recommenders](https://mlsanity.com/paper/2508.05289/) (2025)
- [Credit Risk Analysis for SMEs Using Graph Neural Networks in Supply Chain](https://mlsanity.com/paper/2507.07854/) (2025)
- [LLM-Augmented Symptom Analysis for Cardiovascular Disease Risk Prediction: A Clinical NLP](https://mlsanity.com/paper/2507.11052/) (2025)
- [Valley3: Scaling Omni Foundation Models for E-commerce](https://mlsanity.com/paper/2605.01278/) (2026)
- [Multimodal Foundation Model-Driven User Interest Modeling and Behavior Analysis on Short Video Platforms](https://mlsanity.com/paper/2509.04751/) (2025)
- [LLM-Based Intelligent Notification Composition: From Static Personalization to Context-Aware Persuasive Messaging](https://mlsanity.com/paper/2605.16264/) (2026)

## Abstract (arXiv)

As e-commerce competition intensifies, balancing creative content with conversion effectiveness becomes critical. Leveraging LLMs' language generation capabilities, we propose a framework that integrates prompt engineering, multi-objective fine-tuning, and post-processing to generate marketing copy that is both engaging and conversion-driven. Our fine-tuning method combines sentiment adjustment, diversity enhancement, and CTA embedding. Through offline evaluations and online A/B tests across categories, our approach achieves a 12.5 % increase in CTR and an 8.3 % increase in CVR while maintaining content novelty. This provides a practical solution for automated copy generation and suggests paths for future multimodal, real-time personalization.