In this project, we use pre-trained AI models to gain insights into website audiences, enabling targeted communication strategies. Our aim is to analyse and understand audiences by processing website content through various AI models. By extracting text, summarising it, detecting emotions, identifying key themes, and predicting audience segments, we can determine how different narratives might resonate with various audience groups. This approach helps tailor messages to meet specific goals and connect more effectively with audiences.
The process involves several key functions: extracting text from URLs, summarising content, analysing emotions, classifying text into categories, extracting keywords, and predicting audience segments. These functions work together to provide a comprehensive overview of each webpage. We compile the results into a structured format and save them as a CSV file, offering a valuable resource for refining content strategies and understanding audience segments. For detailed implementation, the complete code is available in a Jupyter Notebook in this GitHub repository, with further explanations presented in this blog