Soil constraints, such as soil sodicity, salinity and acidity, are one cause of yield loss for grain growers globally. A first step towards reducing the associated yield gap is the identification of the area affected and the soil constraint/s responsible for the yield loss. Within a single field, persistent spatial variation of crop growth that repeats year after year is likely due to some form of soil constraint. Vegetation indices derived from satellite imagery can provide a valuable alternative to yield maps for assessing these persistent patterns. The variation identified from remote-sensing data can be compared with soil data from the field to help identify which soil constraints are potentially causing yield differences. This application note describes ConstraintID (www.constraintid.com.au), a web-based software tool that makes it easy for growers to use and interact with remote-sensing data to (1) reveal the persistent long-term variation of crop growth within their fields, (2) devise targeted soil sampling plans and (3) interpret the resulting soil data in view of critical values for certain soil constraints.