System and method for identifying attributes of a population using spend level data

A system comprising:

• a processor for identifying attributes of a population using spend level data,
• a tangible, non-transitory memory configured to communicate with the processor,
• the tangible, non-transitory memory having instructions stored thereon that, in response to execution by the processor, cause the processor to perform operations comprising:
• passively collect, by the processor, the spend level data integral to information processed with a transaction of a plurality of customers, wherein the plurality of customers comprises a first customer;
• aggregate, by the processor, the collected spend level data for a plurality of customers;
• cluster, by the processor, the first customer with a subset of the plurality of customers, based on the aggregated spend level data of the first customer, wherein the clustering comprises:
• assigning, by the processor, a weighted percentile to the spend level data of the first customer within a subset of a plurality of merchant category codes based on the volume of spend by each customer in each merchant category code of the subset of merchant category codes, wherein a merchant category code is assigned to each merchant and is based on the predominant business activity of the merchant;
• selecting, by the processor, a weight percentile for each merchant category code across the subset of the plurality of merchant category codes;
• and
• grouping, by the processor, the first customer with other customers based upon the customers' assigned weighted percentile proximity to the selected weight percentile for each merchant across the subset of the plurality of merchant category codes;
• append, by the processor, the clustered data with customer characteristic data;
• analyze, by the processor, the appended clustered data;
• and
• draw, by the processor, inferences about cluster members based on the analyzing.

An article of manufacture including a non-transitory, tangible computer readable storage medium having instructions stored thereon that, in response to execution by a computer-based system for identifying attributes of a population using spend level data, cause the computer-based system to perform operations comprising:

• passively collect, by the computer-based system, the spend level data integral to information processed with a transaction of a plurality of customers, wherein the plurality of customers comprises a first customer;
• aggregate, by the computer-based system, the collected spend level data for a plurality of customers;
• and
• cluster, by the computer-based system, the first customer with a subset of the plurality of customers, based on the aggregated spend level data of the first customer, wherein the clustering comprises:
• assigning, by the computer-based system, a weighted percentile to the spend level data of the first customer within a subset of a plurality of merchant category codes based on the volume of spend by each customer each merchant category code of the subset of merchant category codes, wherein a merchant category code is assigned to each merchant and is based on the predominant business activity of the merchant;
• selecting, by the computer-based system, a weight percentile for each merchant category code across the subset of the plurality of merchant category codes;
• and
• grouping, by the computer-based system, the first customer with other customers based upon the customers' assigned weighted percentile proximity to the selected weight percentile for each merchant across the subject of the plurality of merchant category codes;
• append, by the computer-based system, the clustered data with customer characteristic data;
• analyze, by the computer-based system, the appended clustered data;
• and
• draw, by the computer-based system, inferences about cluster members based on the analyzing.