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Delivering Promotions based on Analysis of a Shopper's Digital Capture

IP.com Disclosure Number: IPCOM000247057D
Publication Date: 2016-Jul-31
Document File: 3 page(s) / 85K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a method of selecting and delivering promotions to an anonymous shopper (i.e., a shopper not identified as associated with a loyalty program) based on the analysis of a contextual digital capture of the shopper at checkout.

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This is the abbreviated version, containing approximately 47% of the total text.

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Delivering Promotions based on Analysis of a Shopper's Digital Capture

Generating promotions (e.g., coupons, discounts, etc.) for a shopper is a common practice. Methods exist that provide promotions to shoppers based on the associated location, which can be either in proximity to a store or in proximity to a specific

product/aisle in the store. Methods of generating coupons at checkout based on the products just purchased or a loyalty program (e.g., entering pin, scanning loyalty card, biometric identification, etc.) also exist.

Presently, when the shopper is anonymous, unknown to the point of sale (POS) system or not identified as associated with a store loyalty program, the capabilities to generate promotions for future shopping are limited to what is in the shopping basket. During the checkout process, it is known that POS devices can obtain a digital capture (e.g., photograph, video, audio) of the shopper. The analysis of such captures may produce information relevant to promotions. However, methods that combine this analysis with a predictive model to generate promotions do not exist in the art.

The novel contribution is a method to capture textual, visual, and audio inputs from a POS device, analyze that input, and then extract explicit (e.g., demographics, mood, etc.) and implicit (e.g., contextual inputs from the dialog) cues to deliver user-specific promotions at checkout.

The method of selecting and delivering promotions to an anonymous shopper (i.e., a shopper not identified as associated with a loyalty program) is performed by analyzing a contextual digital capture of the shopper during the checkout process. First, the method, triggered when the shopper begins checkout, captures a digital object of the shopper, which may include a photograph, a video, or a video/audio combination. Next, through the checkout process, the method analyzes the captured object to identify:

• The mood of the shopper
• An association to one or more entities

• The demographics
• One or more topics of interest

Finally, using a predictive model, the method selects promotions related to the identified elements.

To implement the method in a preferred embodiment:

1. Pre-configuration: the shopper may have the option to opt out of digital capture and analysis

2. The method is triggered when the shopper arrives at a checkout station 3. The method, running on the POS device, captures a digital object of the shopper. The digital capture may be one of the following. Note that in case of video or video/audio, the method may continue capturing until the checkout process is complete.

A. Photograph of the shopper


B. Video of the shopper

    C. Video/audio combination of the shopper 4. Using image/video/audio recognition capabilities of a cognitive system, the method analyzes the digital capture. The analysis is focused on extracting the following elements:

1


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A. The mood of the shopper (e.g., happy, satisfied, frustrated, disappointed, etc.)...