SYSTEMS AND METHODS FOR TRACKING CONSUMER SPEND BEHAVIORS
Technologies for determining spending behavior of a consumer in a category of interest are disclosed. The spending behavior is based on tracking payment vehicle transactions across a number of merchants. Temporal and geographic parameters are considered to determine if a payment vehicle transaction falls within the category of interest. Based on the payment vehicle transactions and the temporal and geographic parameters, Share of Wallet (SOW) can be determined.
1 . A categorized consumer expenditure tracking method, the method comprising:
receiving, at an expenditure tracking server, transactional data obtained from a plurality of merchants associated with an entity;
identifying, using the expenditure tracking server and within the transactional data, consumer spending behavior at a plurality of time points surrounding an event hosted by the entity;
determining, using the expenditure tracking server, one or more trends in the consumer spending behavior at each of the plurality of time points across the plurality of merchants; and
performing an action based on the determined one or more trends in the consumer spending behavior.
2 . The method of claim 1 , wherein the plurality of time points comprise: a first time window corresponding to a period before the event, a second time window corresponding to a period during the event, and a third time window corresponding to a period after the event.
3 . The method of claim 1 , wherein the one or more trends correspond to an increase or decrease, at each of the plurality of time points, in transaction volume for at least one of: a merchant category, a merchant location, a product type; and a product location.
4 . The method of claim 1 , further comprising:
delineating a geographical area surrounding a venue associated with the entity,
identifying which of the plurality of merchants are not contained within the geographical area; and
ignoring the transactional data from each of the plurality of merchants not contained within the geographical area.
5 . The method of claim 4 , further comprising:
delineating a time window within the plurality of time points;
identifying the transactional data received outside of the time window; and
ignoring the transactional data associated with each of the plurality of merchants contained within the geographical area but received outside of the time window.
6 . The method of claim 5 , wherein the performing the action comprises generating a share of wallet model that identifies, for each of the plurality of merchants contained within the geographical area and generating the transactional data during the time window, a percentage of consumer spend based on an aggregate consumer spend across all of the plurality of merchants and across all of the plurality of time points.
7 . The method of claim 1 , wherein the performing the action comprises performing a resource allocation action associated with the one or more merchants.
8 . A system for consumer spend tracking, the system comprising:
one or more processors; and
a non-transitory computer readable medium having instructions stored thereon which when executed by at least one of the one or more processors cause the at least one of the one or more processors to perform a method comprising:
receiving, at an expenditure tracking server, transactional data obtained from a plurality of merchants associated with an entity;
identifying, using the expenditure tracking server and within the transactional data, consumer spending behavior at a plurality of time points surrounding an event hosted by the entity;
determining, using the expenditure tracking server, one or more trends in the consumer spending behavior at each of the plurality of time points across the plurality of merchants; and
performing an action based on the determined one or more trends in the consumer spending behavior.
9 . The system of claim 8 , wherein the plurality of time points comprise: a first time window corresponding to a period before the event, a second time window corresponding to a period during the event, and a third time window corresponding to a period after the event.
10 . The system of claim 8 , wherein the one or more trends correspond to an increase or decrease, at each of the plurality of time points, in transaction volume for at least one of: a merchant category, a merchant location, a product type; and a product location.
11 . The system of claim 8 , further comprising:
delineating a geographical area surrounding a venue associated with the entity,
identifying which of the plurality of merchants are not contained within the geographical area; and
ignoring the transactional data from each of the plurality of merchants not contained within the geographical area.
12 . The system of claim 11 , further comprising:
delineating a time window within the plurality of time points;
identifying the transactional data received outside of the time window; and
ignoring the transactional data associated with each of the plurality of merchants contained within the geographical area but received outside of the time window.
13 . The system of claim 12 , wherein the performing the action comprises generating a share of wallet model that identifies, for each of the plurality of merchants contained within the geographical area and generating the transactional data during the time window, a percentage of consumer spend based on an aggregate consumer spend across all of the plurality of merchants and across all of the plurality of time points.
14 . The system of claim 8 , wherein the performing the action comprises performing a resource allocation action associated with the one or more merchants.
15 . A non-transitory computer-readable medium for categorized consumer expenditure tracking, the non-transitory computer-readable medium storing instructions which, when executed by one or more processors, cause the one or more processors to perform a method comprising:
receiving, at an expenditure tracking server, transactional data obtained from a plurality of merchants associated with an entity;
identifying, using the expenditure tracking server and within the transactional data, consumer spending behavior at a plurality of time points surrounding an event hosted by the entity;
determining, using the expenditure tracking server, one or more trends in the consumer spending behavior at each of the plurality of time points across the plurality of merchants; and
performing an action based on the determined one or more trends in the consumer spending behavior.
16 . The non-transitory computer-readable medium of claim 15 , wherein the plurality of time points comprise: a first time window corresponding to a period before the event, a second time window corresponding to a period during the event, and a third time window corresponding to a period after the event.
17 . The non-transitory computer-readable medium of claim 15 , wherein the one or more trends correspond to an increase or decrease, at each of the plurality of time points, in transaction volume for at least one of: a merchant category, a merchant location, a product type; and a product location.
18 . The non-transitory computer-readable medium of claim 15 , further comprising:
delineating a geographical area surrounding a venue associated with the entity,
identifying which of the plurality of merchants are not contained within the geographical area; and
ignoring the transactional data from each of the plurality of merchants not contained within the geographical area.
19 . The non-transitory computer-readable medium of claim 18 , further comprising:
delineating a time window within the plurality of time points;
identifying the transactional data received outside of the time window; and
ignoring the transactional data associated with each of the plurality of merchants contained within the geographical area but received outside of the time window.
20 . The non-transitory computer-readable medium of claim 19 , wherein the performing the action comprises generating a share of wallet model that identifies, for each of the plurality of merchants contained within the geographical area and generating the transactional data during the time window, a percentage of consumer spend based on an aggregate consumer spend across all of the plurality of merchants and across all of the plurality of time points.