Precision farming is the application of spatial management technologies to the monitoring and control of crop production. The suite of technologies includes electronic applications such as global positioning systems (GPS), yield monitors, remote sensing technologies, geographic information systems (GIS), and variable rate technologies (VRT) that use controllers on application equipment to vary input amounts across farm fields. Farmers can use these technologies to exploit information about spatial variability in farm fields to improve profitability by varying inputs with crop needs in different areas of farm fields. One precision farming technology that is showing considerable potential in cotton production is soil electrical conductivity (EC) mapping. Soil EC mapping can be used to characterize soil differences within crop production fields and can be related to specific soil properties that affect crop yield. Potential uses of soil EC maps in cotton production include management of nutrients and certain pests in soils of farm fields. Soil EC maps also may be used to identify management zones in fields for variable rate application of inputs and remediation of field drainage issues in farm fields. Currently, there is little information on costs of using soil EC information for alternative variable rate decisions in cotton production. The objective of this research was to evaluate the costs and returns from investment in soil EC mapping technology for making variable rate input application decisions in cotton production. The CPAIDA (Cotton Precision Agriculture Investment Decision Aid) computer program will be used to evaluate farmer investment in soil EC mapping technology. CPAIDA utilizes a combination of partial budgeting, breakeven analysis, and sensitivity analysis techniques to evaluate the input cost savings and yield gains required to pay for investment in precision technologies such as soil EC mapping. Factors to be considered in the cost analysis include equipment costs, labor time to collect and analyze the EC data, farm size, and the number of input decisions over which the soil EC costs can be spread.