Data catalog

Offline purchase count quintile

Ranks individuals into five tiers based on their total number of purchase offline observed.

The Faraday Identity Graph contains 1,500+ consumer attributes that can be used by brands, software platforms, and data science teams. Each attribute can be appended in batch or in real time. Also, Faraday supports creating propensity, recommender, and cluster models based on this data.

Technical details

These technical details describe how Faraday represents this attribute internally.

PropertyValueAPI value
API name
offline_purchase_count_quintile
CategoryFinancialfig/financial
UnitQuintilequintile
Type Integerlong
Statistical type Ordinalordinal
Allowed valuesNot applicablenull
Deprecation Not deprecatedfalse
Directionality Higher percentage means higher relative spending in this activity.

Interpretation table

For enumerable attributes, a mapping from values to their interpretations. The key type matches the attribute's data type, and the value is always a string interpretation.

ValueInterpretation
10-20%
221-40%
341-60%
461-80%
581-100%