Retail customer engagement zones

Patent metadata

Field	Value
Publication number	US-2016140589-A1
Application number	US-201414542232-A
Country	US
Kind code	A1
Filing date	Nov 14, 2014
Priority date	Nov 14, 2014
Publication date	May 19, 2016
Grant date	—

Abstract

A method and system that receives, as input data in a processor of a computer, an identification and location of a retail entity. Map data relevant for the retail entity is received and the retail entity is located on the map data. Data identifying at least one of a product, a product set, and a service or services is received as input data. A listing is received of one or more competitors that offer the product or one or more products of the product set or the service as a competitor of the retail entity for the product, product set or service. The one or more competitors are located on the map data. An affinity for consumers is calculated for the product, product set, or service for the retail entity and each of the one or more competitors.

First claim

Having thus described our invention, what we claim as new and desire to secure by Letters Patent is as follows:

1 . A method comprising:
receiving, as input data in a processor of a computer, an identification and a location of a retail entity; retrieving map data relevant for said retail entity and locating said retail entity on said map data; receiving, as input data, data identifying at least one of a product, a product set, and a service or services; retrieving a listing of one or more competitors that offer said product or one or more products of said product set or said service(s) as a competitor of said retail entity for said product, product set or service(s) and locating said one or more competitors on said map data; and calculating an affinity for consumers for said product, product set, or service(s) for said retail entity and each of said one or more competitors.

2 . The method of claim 1 , wherein said affinity comprises a calculation of one of:
a probability that a consumer will purchase said product or said service(s) or a product of said product set from said retail entity or from a competitor; and a probability that a consumer will visit said retail entity within a preset time period.

3 . The method of claim 1 , further comprising:
receiving an identification of a specific consumer; generating at least one engagement zone for said specific consumer and said product, product set, or service(s) for said retail entity and said one or more competitors, said engagement zone comprising an area determined to warrant a marketing action directed to said specific consumer to attempt to persuade said specific consumer to visit said retail entity to possibly purchase an item at said retail entity rather than from a competitor; receiving input data indicative of a location of said specific consumer; and determining whether said specific consumer's location is within an engagement zone.

4 . The method of claim 3 , further comprising;
if a marketing action is determined as appropriate, generating a marketing message in a context of said product/product set/service(s) and of said contextual data; retrieving from a memory a transmission method to be used for transmitting a marketing action directed to said specific consumer; and transmitting said marketing action to said specific consumer using said transmission method.

5 . The method of claim 4 , further comprising;
monitoring whether said specific customer responds to said marketing action within a preset time period; and storing information indicative of said specific customer's response to said marketing action.

6 . The method of claim 1 , wherein said affinity comprises a calculation of a radius between said retail entity and each said competitor indicative of relative amounts of said product or product set or service(s) purchased at said retail entity and each said competitor;
wherein said radius is distorted based on one or more of:
features of said map data,
a measure of convenience to travel to said retail entity or each competitor, and
contextual data, said contextual data comprising data indicative of events or conditions that possibly would influence retail sales at said retail entity.

7 . The method of claim 6 , wherein said contextual data comprises one or more of:
data reflecting temporal conditions or events; data related to potential shoppers; and data related specifically to said each competitor.

8 . The method of claim 6 , further comprising:
calculating a probability function that a specific customer will visit said retail entity; and providing output data for displaying said probability function on a map display based on said map data.

9 . The method of claim 1 , wherein said calculating said affinity comprises:
retrieving data from a history of location traces of a specific customer to determine travel paths of said specific customer; superimposing said travel paths on said map data; using a history of previous visits of said specific customer to said retail entity to determine a likelihood that said specific customer will visit said retail entity within a specified time period based upon detecting a current location of said specific customer; and providing output data for displaying said likelihood on a map display based on said map data.

10 . The method of claim 9 , further comprising:
receiving updated contextual data associated with said specific customer, said contextual data comprising data indicative of events or conditions that possibly would influence a decision by said specific customer to purchase at said retail entity.

11 . The method of claim 10 , wherein said updated contextual data associated with said specific customer comprises a current location of said specific customer, said method further comprising:
determining whether said current location is within an engagement zone that warrants a marketing action directed to said specific customer; if a marketing action is determined to be appropriate, generating a marketing action in view of said updated contextual data; retrieving from a memory a transmission method to transmit said marketing action to said specific customer at said current location; monitoring whether said specific customer responds to said marketing action; and storing a response of said specific customer to said marketing action.

12 . The method of claim 1 , as embodied in a set of computer-readable instructions tangibly embodied in a non-transitive storage medium.

13 . The method of claim 1 , wherein said affinity is calculated for a specific consumer.

14 . The method of claim 1 , wherein said affinity is calculated as directed to:
a specific consumer or consumer group; a specific product or product set or service(s); a specific location of said consumer or consumer group; and a specific time or time interval.

15 . A method, comprising:
receiving, as input data into a processor, an identification of a customer; retrieving map data for a retail entity in a location of said customer and locating said retail entity on said map data; retrieving a history of previous location traces for said customer, said location traces including an indication of a date and a time; determining at least one recurring travel route of said customer, based on said location traces; and superimposing said at least one recurring travel route of said customer on said map data.

16 . The method of claim 15 , further comprising:
receiving, as an input parameter, an identification of one of a product, a product set, and a service or services; retrieving data for one or more competitors for said identified product, product set, or service or services; and superimposing said one or more competitors on said map data.

17 . The method of claim 16 , further comprising:
receiving data indicating a current location of said customer; and determining whether said current location warrants a marketing action to be directed to said customer.

18 . The method of claim 17 , further comprising:
if a marketing event is determined as appropriate, generating said marketing event; retrieving from a memory a transmission method to be used for transmitting a marketing action directed to said specific customer at said current location; and transmitting said marketing action to said specific consumer using said transmission method.

19 . The method of claim 18 , further comprising;
monitoring whether said specific customer responds to said marketing action wit

Assignees

• IBM

Inventors

• Deshpande Ajay Ashok
• Hendrix Kimberly D
• Mcfaddin Herbert Scott
• Narayanaswami Chandrasekhar

Classifications

• G06Q30/0205 Primary

  based on location or geographical consideration · CPC title

• G06Q30/0201

  Market modelling; Market analysis; Collecting market data · CPC title