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Method and system for using data analytics to leverage consumer purchasing patterns to support charity organizations

IP.com Disclosure Number: IPCOM000238684D
Publication Date: 2014-Sep-11
Document File: 3 page(s) / 50K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed are a method and system that use data analytics to evaluate consumer purchasing patterns along with consumer profiles to mutually improve sales, provide service to charities, and improve convenience to consumers.

This text was extracted from a PDF file.
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Method and system for using data analytics to leverage consumer purchasing patterns to support charity organizations

Charities often require a wide variety of supplies in order to function , many of which are donated by supporters. Most often this comes in the form of monetary donations , which then requires the charity to use the money to purchase the needed items , which takes additional time and resources. A method is needed to simplify the donation process and reduce the need for additional resources.

The novel contribution is a method and system that employ data analytics to evaluate consumer buying patterns along with consumer profiles to mutually improve sales , provide service to charities, and improve convenience to consumers. This methodology provides the ability to match consumers with charities registered for support through the store in an effort to have the consumer purchase the needed items .

Described below are various embodiments available to implement this invention including methods for matching up charities to consumers , incentives for participating, methodologies for executing the process, and providing records and documentation of the transaction. In the primary embodiment of this system, a charity sends a list of requested items to local grocery or department stores that then enters the list into a database and makes the list accessible to consumers .

In a separate function, consumers that are identified as potential supporters of charities are also entered into the database. Consumers are identified as supporters based on an analysis of the consumer's historical buying patterns and associated profile . In the most obvious implementation, a consumer creates a profile that includes a list of charities that the consumer is willing to support. However, to get maximum benefit it is preferable to identify consumers without requiring users to take a manual step to register favorite charities. The system uses data analytics to analyze the consumer's purchasing patterns against criteria, which identifies the consumer as a strong candidate for charities that are registered with the store .

In order to quantify the potential for participation in charity purchasing a scoring system , referred to as a Charity Support Factor (CSF), is established based on the person's buying history and profile. The CSF can be based on a minimum cutoff value above

which the consumer is considered a candidate for being notified of charity opportunities . Consider an example in which the cutoff value is 100. If a consumer designates a supported charity in a profile, this might automatically give the consumer a CSF score
of 100 for that charity. If the consumer specifies a charity in a profile , and then actually donates to that charity, the score increases (e.g., to 120). Alternatively, if the consumer did not enter a charity in a profile, but purchased goods for the charity, then the score might automatically increase to 100. A consumer...