Method and system for building a consumer decision tree in a hierarchical decision tree structure based on in-store behavior analysis
First Claim
1. A method for building a consumer decision tree based on in-store purchase behavior analysis by the measurement of a set of consumer behavior metrics,comprising the following steps of:
- a) capturing a plurality of input images of consumers by at least a means for capturing images in a store area,b) processing the plurality of input images in order to analyze the behavior of the consumers,c) measuring decision activities of the consumers tied to product categories based on the behavior analysis,d) creating a plurality of datasets by accumulating the decision activities, whereby decision activity is measured based on the actual in-store purchase behavior of the consumers including interaction with products and travel paths to categories, as opposed to using intercepts or panels to develop them, ande) constructing a hierarchical decision tree structure, clustering the consumer behavior data based on the measurement of the decision activities by the consumers, which comprises nodes and edges,wherein a node represents in-store purchase behavior of the consumer,wherein the number of nodes is predefined, andwherein an edge represents the transition of the decision activities.
17 Assignments
0 Petitions
Accused Products
Abstract
The present invention is a system and method for determining the hierarchical purchase decision process of consumers in front of a product category. The decision path of consumers is obtained by combining behavior data with the category layout and transaction data based on observed actual in-store purchase behavior using a set of video cameras and software for extracting sequence and timing of each consumer'"'"'s decision process. A hierarchical decision tree structure comprises nodes and edges, wherein a node represents the state-of-mind of the consumer, the number of nodes is predefined, and an edge represents the transition of the decision. The decisions for each product group are captured down to the product attribute level and analyzed by demographic group. The outcome provides relative importance of each product attribute in the purchase decision process, and helps retailers and manufacturers to evaluate the layout of the category and customize it for key segment.
91 Citations
20 Claims
-
1. A method for building a consumer decision tree based on in-store purchase behavior analysis by the measurement of a set of consumer behavior metrics,
comprising the following steps of: -
a) capturing a plurality of input images of consumers by at least a means for capturing images in a store area, b) processing the plurality of input images in order to analyze the behavior of the consumers, c) measuring decision activities of the consumers tied to product categories based on the behavior analysis, d) creating a plurality of datasets by accumulating the decision activities, whereby decision activity is measured based on the actual in-store purchase behavior of the consumers including interaction with products and travel paths to categories, as opposed to using intercepts or panels to develop them, and e) constructing a hierarchical decision tree structure, clustering the consumer behavior data based on the measurement of the decision activities by the consumers, which comprises nodes and edges, wherein a node represents in-store purchase behavior of the consumer, wherein the number of nodes is predefined, and wherein an edge represents the transition of the decision activities. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19)
-
-
20. An apparatus for building a consumer decision tree based on in-store purchase behavior analysis by the measurement of a set of consumer behavior metrics, comprising:
-
a) at least a means for capturing images that captures a plurality of input images of consumers in a store area, b) at least a computer programmed to execute the following steps of; processing the plurality of input images in order to analyze the behavior of the consumers, measuring decision activities of the consumers tied to product categories based on the behavior analysis, creating a plurality of datasets by accumulating the decision activities, whereby decision activity is measured based on the actual in-store purchase behavior of the consumers including interaction with products and travel paths to categories, as opposed to using intercepts or panels to develop them, and constructing a hierarchical decision tree structure, clustering the consumer behavior data based on the measurement of the decision activities by the consumers, which comprises nodes and edges, wherein a node represents in-store purchase behavior of the consumer, wherein the number of nodes is predefined, and wherein an edge represents the transition of the decision activities.
-
Specification
-
- Resources
-
Current AssigneeVideomining Corporation
-
Original AssigneeVideomining Corporation
-
InventorsJung, Namsoon, Baboo, Priya, Mummareddy, Satish, Sharma, Rajeev, Saurabh, Varij
-
Primary Examiner(s)CHANG, LI WU
-
Application NumberUS12/583,080Time in Patent Office1,328 DaysField of SearchNoneUS Class Current706/20CPC Class CodesG06Q 30/0201 Market modelling; Market an...G06Q 30/0282 Rating or review of busines...G06Q 30/06 Buying, selling or leasing ...
