Tracking concentrations of regional airborne pollen is valuable for a variety of fields including plant and animal ecology as well as human health. However, current methods for directly measuring regional pollen concentrations are labor-intensive, requiring special equipment and manual counting by professionals leading to sparse data availability in select locations. Here, we use publicly available Google Trends data to evaluate whether searches for the term "pollen" can be used to approximate local observed early-season pollen concentrations as reported by the National Allergy Bureau across 25 U.S. regions from 2012-2017, in the context of site-specific characteristics. Our findings reveal that two major factors impact the ability of internet search data to approximate observed pollen: (1) volume/availability of internet search data, which is tied to local population size and media use; and (2) signal intensity of the seasonal peak in searches. Notably, in regions and years where internet search data was abundant, we found strong correlations between local search patterns and observed pollen, thus revealing a potential source of daily pollen data across the U.S. where observational pollen data are not reliably available.