Using biometric data for a customer to improve upsale ad cross-sale of items

• US 9,031,858 B2
• Filed: 09/26/2007
• Issued: 05/12/2015
• Est. Priority Date: 04/03/2007
• Status: Expired due to Fees

• Current Assignee: Daedalus Blue LLC
• Original Assignee: International Business Machines Corporation
• Inventors: Angell, Robert Lee, Kraemer, James R.
• Primary Examiner(s): Brown, Alvin L
• Application Number:
  US11/861,729
• Publication Number:
  US 20080249867A1
• Time in Patent Office: 2,785 Days
• Field of Search: 705/14
• US Class Current: 705/14
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0225 Avoiding frauds
• CPC Class Codes: G06Q 30/0226 Incentive systems for frequent usage, e.g. frequent flyer miles programs or point systems
• CPC Class Codes: G06Q 30/0236 Incentive or reward received by requiring registration or ID from user
• CPC Class Codes: G06Q 30/0255 based on user history
• CPC Class Codes: G06Q 30/0271 Personalized advertisement
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions

Abstract

A computer implemented method, apparatus, and computer usable program code for generating customized marketing messages to increase purchases by a customer. In one embodiment, an item selected by the customer is identified to form a selected item. Biometric readings for the customer are received from a set of biometric devices associated with a retail facility to form the biometric data. The biometric data is data regarding a set of physiological responses of the customer. A set of items is selected from a list of items associated with the selected item using the biometric data for the customer to form a set of promoted items. A customized marketing message for the customer is generated using a set of personalized marketing message criteria for the customer. The customized marketing message comprises a marketing message for the set of promoted items.

Claims

1. A computer implemented method for generating customized marketing messages to increase purchases by a customer, the computer implemented method comprising:

receiving external data associated with the customer from a set of detectors located externally to a retail facility to form external data;

identifying an item selected by the customer to form a selected item;

receiving, by a processor, biometric readings for the customer from a set of biometric devices associated with the retail facility to form biometric data, wherein the biometric data is data regarding a set of physiological responses of the customer;

processing the external data with the biometric data to form dynamic data;

analyzing the dynamic data using a set of data models to identify personalized marketing message criteria for the customer;

selecting a set of items from a list of items associated with the selected item using the dynamic data for the customer to form a set of promoted items; and

generating a customized marketing message for the customer using the personalized marketing message criteria and the set of promoted items, wherein the customized marketing message comprises a marketing message promoting a sale of the set of promoted items.

2. The computer implemented method of claim 1 wherein the customer is a customer in a set of customers and further comprising:

receiving data associated with the set of customers from detectors associated with the retail facility to form detection data;

processing the detection data for the set of customers to form grouping data for the customer;

analyzing the biometric data with the grouping data to form the dynamic data;

analyzing the dynamic data using a set of data models to identify the personalized marketing message criteria for the customer;

selecting the set of items from the list of items associated with the selected item using the dynamic data for the customer to form the set of promoted items; and

generating the customized marketing message for the customer using the personalized marketing message criteria and the set of promoted items.

3. The computer implemented method of claim 2 wherein the grouping data identifies a grouping category for the customer, and wherein the grouping category is selected from a group consisting of parents with children, teenagers, children, minors unaccompanied by adults, minors accompanied by adults, grandparents with grandchildren, senior citizens, couples, friends, coworkers, a customer with a pet, and a customer shopping alone, and further comprising:

identifying items in the list of items associated with the selected item that are frequently purchased by customers in the grouping category for the customer to form a set of frequently purchased items; and

using the biometric data to identify items in the set of frequently purchased items to market to the customer to form the set of promoted items.

4. The computer implemented method of claim 1 further comprising:

receiving external marketing data from a set of sources to form current events data;

processing the current events data with the biometric data to form the dynamic data;

analyzing the dynamic data using a set of data models to identify the personalized marketing message criteria for the customer;

selecting the set of items from the list of items associated with the selected item using the dynamic data for the customer to form the set of promoted items; and

generating the customized marketing message for the customer using the personalized marketing message criteria, wherein the customized marketing message provides an incentive to purchase at least one item in the set of promoted items.

5. The computer implemented method of claim 4 further comprising:

responsive to a determination that the current events data indicates an event of interest to the customer occurs within a predetermined period of time, identifying items in the list of items associated with the selected item and the event of interest to form a set of items of interest to the customer; and

using the biometric data to identify items in a set of items of interest to market to the customer to form the set of promoted items.

6. The computer implemented method of claim 1 further comprising:

receiving data associated with the customer from a set of cameras associated with the retail facility to form detection data for the customer;

processing the detection data, by a smart detection engine, to form event data, wherein the event data describes events associated with the customer;

analyzing the event data to identify patterns of events to form customer behavior data;

processing the customer behavior data with the biometric data to form the dynamic data;

analyzing the dynamic data using a set of data models to identify the personalized marketing message criteria for the customer;

identifying items in the list of items associated with the selected item using the dynamic data to form the set of promoted items, wherein the customer behavior data and the biometric data indicates an interest of the customer in receiving marketing messages associated with at least one item in the set of promoted items; and

generating the customized marketing message for the customer using the personalized marketing message criteria and the set of promoted items.