SMALL data promises to measure results better while:

SMALL data focuses on collecting less, but more relevant, data to gain deeper insights. This approach prioritizes quality over quantity, allowing for more precise analysis and actionable intelligence. By reducing the volume of data, marketers can avoid being overwhelmed by irrelevant information and concentrate on the metrics that truly drive results. Processing huge amounts of data and collecting huge amounts of data are characteristics of "big data," which often presents challenges in terms of analysis and interpretation. Querying data from different sources is a common practice in both small and big data analytics, but it doesn't inherently define the "small data" approach to better measurement.