AUTOMATICALLY DETECTING LOST SALES

• US 20140039950A1
• Filed: 08/03/2012
• Published: 02/06/2014
• Est. Priority Date: 08/03/2012
• Status: Abandoned Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Gatti, Maira Athanazio de Cerqueira, de Paula, Rogerio Abreu, APPEL, ANA PAULA
• Application Number:
  US13/566,253
• Publication Number:
  US 20140039950A1
• Time in Patent Office: Days
• US Class Current: 705/7.11
• CPC Class Codes: G06F 18/24 Classification techniques
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 30/00 Commerce
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06V 20/41 Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items segmenting video sequences G06V20/49
• CPC Class Codes: G06V 20/44 Event detection
• CPC Class Codes: G06V 40/70 Multimodal biometrics, e.g. combining information from different biometric modalities

Abstract

One embodiment of a method for detecting a lost sale due to an out-of-shelf condition in a retail environment includes automatically detecting when a customer fails to purchase an expected product, based at least in part on an observation of a current behavior of the customer in the retail environment and on a purchasing history of the customer, and inferring, based on the automatically detecting, that the expected product is out-of-shelf.

Claims

1. A method for detecting a lost sale due to an out-of-shelf condition in a retail environment, the method comprising:

automatically detecting when a customer fails to purchase an expected product during a current visit to the retail environment, based at least in part on an observation of a behavior of the customer during the current visit and on a purchasing history of the customer, wherein the behavior indicates that the customer wishes to purchase the expected product during the current visit and the purchasing history identifies the expected product as a product that the customer purchased during a past visit to the retail environment; and

inferring, based on the automatically detecting, that the expected product is out-of-shelf, without necessarily being out-of-stock;

wherein at least one of the automatically detecting or the inferring is performed using a processor.

2. The method of claim 1, wherein the automatically detecting comprises:

identifying a first set of products stocked in a first section of the retail environment in which the customer stops during the current visit;

identifying the expected product in the first set of products and in the purchasing history of the customer;

identifying a purchase made by the customer during the current visit in the retail environment; and

detecting that the purchase does not include the expected product.

3. The method of claim 2, wherein the identifying the first set of products comprises:

tracking a movement of the customer through the retail environment;

detecting when the customer stops in the first section of the retail environment; and

retrieving a list of products stocked in the first section of the retail environment from an inventory system of the retail environment.

4. The method of claim 3, wherein the tracking comprises:

capturing identifying data that uniquely identifies the customer from a plurality of physical locations within the retail environment; and

correlating the identifying data in order to construct a trajectory that traces the movement of the customer through the retail environment.

5. The method of claim 4, wherein the identifying data comprises a plurality of images of the customer.

6. The method of claim 4, wherein the identifying data comprises biometric data of the customer.

7. The method of claim 6, wherein the biometric data comprises a fingerprint of the customer.

8. The method of claim 6, wherein the biometric data comprises an ocular feature of the customer.

9. The method of claim 6, wherein the biometric data comprises a gait of the customer.

10. The method of claim 6, wherein the biometric data comprises a gesture of the customer.

11. The method of claim 1, further comprising:

retrieving the purchasing history from a customer database comprising a plurality of customer profiles.

12. The method of claim 11, wherein the retrieving comprises:

capturing identifying data that uniquely identifies the customer from at least one physical location within the retail environment;

detecting a profile from the plurality of customer profiles that matches the identifying data; and

extracting the purchasing history from the profile.

13. The method of claim 12, wherein the identifying data comprises a plurality of images of the customer.

14. The method of claim 12, wherein the identifying data comprises biometric data of the customer.

15. The method of claim 14, wherein the biometric data comprises a fingerprint of the customer.

16. The method of claim 14, wherein the biometric data comprises an ocular feature of the customer.

17. The method of claim 14, wherein the biometric data comprises a gait of the customer.

18. The method of claim 12, wherein the identifying data is captured by a radio frequency identification system.

19. The method of claim 1, further comprising:

sending an alert indicating that the expected product is believed to be out-of-shelf.

20. A method for detecting a lost sale due to an out-of-shelf condition in a retail environment, the method comprising:

detecting an entry of a customer into a retail environment;

determining an identity of the customer;

retrieving a purchasing history associated with the customer, in accordance with the identity;

tracking a movement of the customer through the retail environment;

detecting when the customer stops in a section of the retail environment after the entry, in accordance with the tracking;

identifying a product that is both stocked in the section of the retail environment and that appears in the purchasing history as having been purchased by the customer during a past visit to the retail environment;

detecting an exit of the customer from the retail environment;

inferring that the customer wished to purchase the product during a current visit to the retail environment occurring between a time of the entry and a time of the exit, based at least in part on the tracking, the detecting when the customer stops, and the identifying;

reviewing a purchase made by the customer during the current visit to the retail environment; and

inferring that the product is out-of-shelf when the product is not part of the purchase,

wherein at least one of;

the detecting the entry, the determining, the retrieving, the tracking, the detecting when the customer stops, the identifying, the detecting the exit, the inferring that the customer wished to purchase the product, the reviewing, or the inferring is performed using a processor.