Consumer Vitality focuses on consumers. Consumer Vitality was developed using a geographically intensive, data-driven algorithm including Precisely’s Spectrum Spatial technology to capture geographies’ desirability relative to its local neighbours, cross-country companions and everything in between. By including multiple levels and types of geography, the Consumer Vitality algorithm considers macro and micro socio-economic and geo-economic factors and trends. Consumer Vitality then combines these scores into a final score through a nested linear weighting schema.
The Consumer Vitality score is normalized to a national average of 100, with higher scores reflecting more desirable areas. However, DAs that have a score of 100 do not necessarily have the same underlying statistics everywhere in the country. This is a core strength of Consumer Vitality in that the score accounts for the importance of context and relativity. Areas with very similar descriptive statistics can have different levels of desirability.
Consumer Vitality measures a true sense of desirability that matches the complex way humans interpret it. In addition to filling a business-wide knowledge gap, this multi-level algorithm also makes Consumer Vitality more robust to noise because of the intensive volume of calculations and geographical multidimensionality.