Not all data is complete, and often brands won’t have a full view on the customers. One of the more common attributes brands aren’t sure about is the gender of all their customers. Using some basic logic, Lexer can generate inferred gender attributes to enrich your first party data.
Lexer’s inferred gender attribute takes a customer’s first name, and compares it against a list of first names associated with either a male or female gender.
In the event a name could be either male or female, for example Taylor, we would then look to a brand's dominant branding to associate just one. So, if we saw Taylor within a female dominant brand’s data, we would infer they are female.
We find the accuracy of this method to sit at about 80%.
If you’d like to add this attribute to your customer data get in contact with your Lexer Success Manager.
Updated 18 days ago