F1 Score is the harmonic mean of precision (what percentage of predicted matches are correct) and recall (what percentage of true matches are found). DarkMath's 86.44% F1 means we find most true matches while avoiding false merges, a 19.82% improvement over competitors who sacrifice precision for recall or vice versa.
A 78.96% match rate means DarkMath successfully resolved 78.96% of record pairs that should be linked. Competitors at 61.36% are missing nearly 40% of valid connections, fragmenting customer views and leaving revenue on the table.
When a competitor creates a "household" with 994 members, something is deeply wrong. These mega-clusters occur when overly permissive matching rules merge unrelated records, apartment buildings, common names, or simply errors compounding. DarkMath's maximum household size of 37 reflects real-world limits, ensuring your analytics aren't corrupted by false aggregations.
Finding 4.3 million duplicates that competitors missed means those competitors' customers are unknowingly marketing to the same people multiple times, calculating incorrect lifetime values, and making decisions on corrupted data. A 26.91% reduction represents massive operational savings.
