This study assesses the performance of three objective techniques—Cressman's inverse-distance weighting, Shepard's method, and Gandin's optimal interpolation (OI)—for gauge-based daily precipitation analyses over global land areas. The assessments are conducted using quality-controlled daily precipitation reports from approximately 16,000 stations collected by the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC). The techniques are evaluated through intercomparisons and cross-validation tests over various regions with different station network densities. The results show that all three techniques can generate useful daily precipitation analyses with biases generally less than 1% over most parts of the globe. However, the OI method consistently outperforms the other two techniques, exhibiting better correlation and smaller biases. The Cressman method tends to produce smoother precipitation fields with larger rain areas, while the Shepard method compares reasonably well with the OI. The quality of the analyses degrades as the station network density decreases, but the OI technique remains relatively stable even in regions with sparse gauges. The study highlights the importance of selecting an appropriate objective technique to ensure reliable and accurate precipitation analyses, especially in regions with varying network densities.This study assesses the performance of three objective techniques—Cressman's inverse-distance weighting, Shepard's method, and Gandin's optimal interpolation (OI)—for gauge-based daily precipitation analyses over global land areas. The assessments are conducted using quality-controlled daily precipitation reports from approximately 16,000 stations collected by the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC). The techniques are evaluated through intercomparisons and cross-validation tests over various regions with different station network densities. The results show that all three techniques can generate useful daily precipitation analyses with biases generally less than 1% over most parts of the globe. However, the OI method consistently outperforms the other two techniques, exhibiting better correlation and smaller biases. The Cressman method tends to produce smoother precipitation fields with larger rain areas, while the Shepard method compares reasonably well with the OI. The quality of the analyses degrades as the station network density decreases, but the OI technique remains relatively stable even in regions with sparse gauges. The study highlights the importance of selecting an appropriate objective technique to ensure reliable and accurate precipitation analyses, especially in regions with varying network densities.