What is it about?

This paper discusses a new method for creating fictional detailed user profiles based on real users, known as personas, by analyzing the click data from users of existing business software. Instead of relying on traditional surveys and interviews, this method uses techniques like clustering and machine learning to semi-automatically identify user behaviors and challenges (pain points) from log data. This approach provides insights into how users interact with the software and what improvements are needed.

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Why is it important?

Understanding how users interact with software is crucial for making it more user-friendly and effective. Traditional methods of gathering this information can be time-consuming and expensive. This new method offers a more efficient and data-driven way to create accurate and useful personas. By identifying pain points directly from user behavior, software developers can better address user needs and enhance the overall user experience, especially in the business-to-business (B2B) sector where user feedback is often harder to obtain.

Read the Original

This page is a summary of: Development of Data-driven Persona Including User Behavior and Pain Point through Clustering with User Log of B2B Software, April 2024, ACM (Association for Computing Machinery),
DOI: 10.1145/3641822.3641870.
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