Targeting shoppers in an online shopping environment

• US 20050096997A1
• Filed: 10/31/2003
• Published: 05/05/2005
• Est. Priority Date: 10/31/2003
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Jain, Vivek, Kothari, Ravi
• Application Number:
  US10/699,173
• Publication Number:
  US 20050096997A1
• Time in Patent Office: Days
• US Class Current: 705/26.1
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]

Abstract

Within an online shopping environment, a hosting server supports shoppers and merchants from whom the shoppers purchase goods or services. The hosting server enables an individual user to shop or browse the merchant sites and also enables a group of users to coordinate their shopping or browsing activities. A set of profiling tools build separate profiles based on individual and group shopper activity, as well as the interaction of an individual shopper with one or more groups of shoppers. A targeting tool uses the shopper profiles and information regarding previous promotions (if any) from a promotions library to make recommendations to individual shoppers and shopper groups based also on parameters specified by the merchant/s. The recommendations are directed to shoppers, in accordance with algorithms stored in a repository.

Claims

1-42. -42. (canceled)

43. A method for targeting shoppers participating in online shopping with at least one merchant, said method comprising the steps of:

collecting data regarding choices of individual shoppers when shopping individually;

collecting data regarding the choices of individual shoppers when participating in group shopping;

determining a shopper-group interaction measure from individual shopper data and group shopper data;

determining targeted information on a basis of said shopper-group interaction measure; and

sending said targeted information to one or more targeted shoppers.

44. The method of claim 43, wherein said shopper-group interaction measure is determined based on any of:

a shopper affinity index,

a leadership index,

a conformity index, and

an assertiveness index.

45. The method of claim 44, wherein said shopper affinity index is determined from a number of times a shopper has voted with other members of a group of shoppers.

46. The method of claim 44, wherein said shopper affinity index is determined from a number of times a shopper'"'"'s proposal has been voted for by other members of a group of shoppers.

47. The method of claim 44, wherein said shopper affinity index is determined from a number of times a shopper has been invited by, or issued an invitation to other members of a group of shoppers.

48. The method of claim 44, wherein said shopper affinity index is determined from a number of shopping groups that a shopper is a commonly member of with other shoppers.

49. The method of claim 44, wherein said leadership index is determined from records of purchaser recommendations of said shopper and a number of times other shoppers in a group of shoppers have followed such a recommendation.

50. The method of claim 44, wherein said conformity index is determined from a voting record of said shopper regarding purchase proposals with reference to agreeing with a majority or lead shopper'"'"'s vote within a group of shoppers.

51. The method of claim 44, wherein said assertiveness index is determined from a voting record of said shopper regarding purchase proposal with reference to disagreeing with a majority of lead shopper'"'"'s vote within a group of shoppers.

52. The method of claim 44, wherein said indices are a function of a shopper parameter specified by said merchant.

53. The method of claim 43, wherein said targeted information is determined by any of:

a rule specified by said merchant, and

an adaptive algorithmic rule.

54. The method of claim 53, wherein said rule specified by said merchant and said adaptive algorithmic rule further determine which are to be said targeted shoppers.

55. The method of claim 53, wherein said rule specified by said merchant is based on a particular promotion of goods or services by said merchant.

56. The method of claim 53, wherein said adaptive algorithmic rule learns from any of:

a shopper affinity index,

a leadership index,

a conformity index, and

an assertiveness index,

and wherein the indices are determined from said shopper-group interaction measure.

57. The method of claim 56, wherein said adaptive algorithmic rule further learns from said shopper-group interaction measure to decide whether to target information to a group or to individual shoppers.

58. A method for targeting shoppers participating in online shopping with at least one merchant, said method comprising the steps of:

collecting data regarding choices of individual shoppers when shopping individually;

determining an individual shopping behavior measure from the individual shopper data;

collecting data regarding the choices of individual shoppers when participating in group shopping;

determining a group shopping behavior measure from the group shopping data;

determining a shopper-group interaction measure from said individual shopper data and said group shopper data;

determining targeted information based on said individual shopping behavior measure, said group shopping behavior measure, and said shopper-group interaction measure; and

sending said targeted information to one or more targeted shoppers.

59. The method of claim 58, wherein said targeted information is determined by any of:

a rule specified by said merchant, and

an adaptive algorithmic rule.

60. The method of claim 59, wherein said rule specified by said merchant and said adaptive algorithmic rule further determine which are to be said targeted shoppers.

61. The method of claim 59, wherein said rule specified by said merchant is based on a particular promotion of goods or services by a said merchant.

62. The method of claim 59, wherein said adaptive algorithmic rule learns from any of:

a shopper affinity index,

a leadership index,

a conformity index, and

an assertiveness index,

and wherein said indices are determined from said shopper-group interaction measure.

63. The method of claim 59, wherein said adaptive algorithmic rule further learns from said shopper-group interaction measure to decide whether to target information to a group or to individual shoppers.

64. The method of claim 63, wherein said group shopping measure is determined by any of:

a group compatibility and agreement index,

a maturity index,

a group youthfulness index, and

a group harmony index.

65. The method of claim 64, wherein said group compatibility and agreement index is calculated based on a time series of group shopping history and said individual shopping behavior measure to give an indication of either assimilation leading to targeting information to a group, or lack of assimilation leading to targeting information to individual shoppers.

66. The method of claim 65, wherein said individual shopping behavior measure comprises information on demographics, income, purchase history, navigation history, and preferences.

67. The method of claim 59, wherein said adaptive algorithmic rule further learns from a shopping context measure derived from the individual shopper data.

68. An online shopping system comprising:

a plurality of shopper terminals;

at least one merchant site; and

a shopping server system connected to said shopper terminals and said merchant sites by a communications link, and wherein said server system includes;

an input/output interface;

a memory unit operable for collecting and storing data via said input/output interface regarding choices of individual shoppers when shopping individually, and data regarding choices of individual shoppers when participating in group shopping;

a processor operable for determining a shopper-group interaction measure from the individual shopper data and the group shopper data, and determining targeting information based on of said shopper group interaction measure; and

wherein said input/output interface sends said targeted information to one or more targeted shoppers.

69. An online shopping server for interacting with a plurality of shoppers and at least one merchant, comprising:

an input/output interface;

a memory unit operable for collecting and storing data via said input/output interface regarding choices of individual shoppers when shopping individually, and data regarding the choices of individual shoppers when participating in group shopping;

a processor operable for determining a shopper-group interaction measure from the individual shopper data and the group shopper data, and determines targeting information on the basis of said shopper group interaction measure;

and wherein said input/output interface sends said targeted information to one or more targeted shoppers.

70. The server of claim 69, wherein said processor is operable for determining said shopper-group interaction measure based on any of:

a shopper affinity index,

a leadership index,

a conformity index, and

an assertiveness index.

71. The server of claim 70, wherein said processor is operable for determining affinity index from a number of times a shopper has voted with other members of a group of shoppers.

72. The server of claim 70, wherein said processor is operable for determining shopper affinity index from a number of times a shopper'"'"'s proposal has been voted for by other members of a group of shoppers.

73. The server of claim 70, wherein said processor is operable for determining said shopper affinity index from a number of times a shopper has been invited by, or issued an invitation to other members of a group of shoppers.

74. The server of claim 70, wherein said processor is operable for determining said shopper affinity index from a number of shopping groups that a shopper is a commonly member of with other shoppers.

75. The server of claim 70, wherein said processor is operable for determining said leadership index from records of purchaser recommendations of a shopper and a number of times other shoppers in a group of shoppers have followed such a recommendation.

76. The server of claim 70, wherein said processor is operable for determining said conformity index from a voting record of a shopper regarding purchase proposals with reference to agreeing with a majority or lead shopper'"'"'s vote within a group of shoppers.

77. The server of claim 70, wherein said processor is operable for determining said assertiveness index from a voting record of a shopper regarding purchase proposal with reference to disagreeing with a majority of lead shopper'"'"'s vote within a group of shoppers.

78. The server of claim 70, wherein the indices are determined by said processor as a function of a shopper parameter specified by a merchant input via said input/output interface.

79. The server of claim 69, wherein said processor is operable for determining said targeted information based on any of:

a rule specified by a merchant input via said input/output interface, and

an adaptive algorithmic rule stored in said memory unit.

80. The server of claim 79, wherein said processor is operable for determining which are to be said targeted shoppers based on a merchant rule and said adaptive algorithmic rule.

81. The server of claim 79, wherein said merchant rule is based on a particular promotion of goods or services by said merchant.

82. The server of claim 79, wherein said adaptive algorithmic rule learns from any of:

a shopper affinity index,

a leadership index,

a conformity index, and

an assertiveness index,

and wherein the indices are determined by said processor from said shopper-group interaction measure.

83. The server of claim 80, wherein said processor applying said adaptive algorithmic rule further learns from the group shopping measure to decide whether to target information to a group or to individual shoppers.

84. A program storage device readable by computer, tangibly embodying a program of instructions executable by the computer to perform a method for targeting shoppers participating in online shopping with at least one merchant, said method comprising:

collecting data regarding choices of individual shoppers when shopping individually;

collecting data regarding choices of individual shoppers when participating in group shopping;

determining a shopper-group interaction measure from the individual shopper data and said group shopper data;

determining targeted information based on said shopper-group interaction measure; and

sending said targeted information to one or more targeted shoppers.