Uncovering the “value” of a good or service in economic terms is very complex for land transactions. This difficulty comes because a wider variety of criteria must be considered in order to accurately determine land valuation. At the same time, the perspective through which different types of land buyers value land varies widely according to their intention for the land.
Several key elements historically made determining the land value a complicated endeavor. This includes different types of land buyers, varied land valuation methods, complex information about land located across many different sources, different geographies and climates, and other unpredictable factors.
With CIBO, stakeholders across agriculture are now able to blend publicly available data with science-driven insights for a new valuation process that gives stakeholders who aren’t familiar with a piece of land comprehensive data about it. With this new and common language for understanding it, anyone evaluating U.S. farmland can enjoy an unprecedented scale and depth of information about each parcel.
It was clear that an entirely new approach was needed to empower any type of buyer to accurately and objectively determine a land parcel’s true value. CIBO’s breakthrough approach combines machine learning, modeling, and simulation capabilities to combine the most accurate aspects of each existing valuation method with our own proprietary insights and take into account more variables from the public, private, and proprietary data sources than any other method. The result is in-depth and scalable farmland information easily available to anyone who needs it.