Data vs. Findings vs. Insights: The Differences Explained

This article explains the differences between data, findings, and insights. Data refers to unanalyzed user observations, while findings capture patterns among data points. Insights are the actionable opportunities based on research and business goals. Understanding these terms and having a shared vocabulary is important for effective communication in research analysis. Data lacks significance individually and requires analysis to become information. The first level of analysis yields findings, which are patterns among a specific set of data points. The final level of analysis produces insights, which explain observed patterns and identify actionable opportunities.

Raw Data Lacks Context

Data refers to unanalyzed observations about users, such as transcripts, notes, metrics, or survey output. It lacks significance individually and requires analysis to become useful information. Findings capture patterns among data points, while insights provide a deeper understanding by explaining observed patterns and suggesting actionable opportunities. A shared vocabulary and understanding of data, findings, and insights are crucial for communicating research analysis effectively. Researchers should strive to create insights, which identify opportunities for improving business goals.