Results from mock bull buying activity using eye tracking technology shared
Experiment finds order in which data are listed in a sale catalog matter.
September 11, 2024
The bull decision is one of the most consequential decisions a cattle operation makes, Dr. Charley Martinez, University of Tennessee assistant professor and extension specialist in the Department of Agricultural and Resource Economics, told attendees at the Beef Improvement Federation (BIF) Symposium.
Martinez stated that bull selection is challenging because bulls have an outsized “footprint” relative to their impact on a herd. A bad purchase can hamper a herd long term, and a producer’s “search space” is huge when it comes to looking for bulls. Additionally, lots of traits matter for overall profitability.
Martinez and colleagues conducted a multi-year behavioral experiment to determine how producers use the data they are given at a bull sale to make purchasing decisions. To do this, Martinez enrolled producers in the experiment and showed them videos and various data that would commonly be available in sale catalogs. The data available varied and included bulls with or without EPDs (expected progeny differences), and EPDs with or without associated percentile ranks.
The producers in the study were asked to guess the sale price of each bull. Key findings showed that producers who utilize EPDs or GE-EPDs (genomic-enhanced EPDs) along with percentile ranks were more likely to accurately determine the sale price of bulls. Using novel eye movement tracking software, Martinez and colleagues were able to determine what prospective buyers look at when making purchasing decisions.
Results from this study suggest that the order in which data, such as EPDs and indexes, are listed in a sale catalog matter in terms of the amount of time a prospective buyer looks at them. Martinez stated that producers face information overload when confronted with most sale catalogs. The results from his work help inform what pieces of data buyers look at now and how to better present data to encourage use of tools such as indexes.
Watch the full presentation here.
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