How to use domestic large models for market trend analysis and user behavior insights?

When it is necessary to use domestic large models for market trend analysis and user behavior insights, it is usually possible to quickly extract key trends and user behavior characteristics by integrating multi-source data (such as industry reports, social media content, and consumption data) and leveraging the natural language understanding and multimodal analysis capabilities of large models. In terms of market trend analysis, domestic large models are suitable for processing unstructured data (such as user reviews and news updates), identifying industry hotspots (such as changes in consumer preferences and policy impacts) through topic clustering and sentiment tendency analysis; for user behavior insights, user interaction data (such as click paths and dwell time) can be combined, and the sequence analysis capabilities of large models can be used to挖掘 behavioral motivations (such as purchasing decision factors and demand pain points). Enterprises can prioritize domestic large models that support real-time data access, customize analysis dimensions (such as regional differences and crowd segmentation) in combination with business scenarios, and optimize model output through small-sample verification to enhance the practicality of market trend prediction and user behavior insights.