Obviousness

Obviousness Analysis of U.S. Patent No. 12,026,731 under 35 U.S.C. § 103

This analysis identifies combinations of prior art references that would render the independent claims of U.S. Patent No. 12,026,731 (hereinafter the '731 patent) obvious to a person having ordinary skill in the art (POSA). The '731 patent generally describes a system, method, and non-transitory computer-readable storage medium for monitoring and analyzing the behavior of people in a retail store (or other location) using information monitoring devices and various software modules, including demographic intelligence and tracking, to provide personalized marketing and advertising.

A POSA in the field of the '731 patent at the time of its priority date (July 19, 2013) would be someone with a Bachelor's degree in computer science, electrical engineering, or a related field, coupled with several years of experience in developing and implementing retail technology, data analytics, or marketing systems. Such a person would be familiar with various sensing technologies, data processing, and common algorithms for demographic analysis and tracking.

The background of the '731 patent clearly articulates the problem it seeks to solve: "Brick-and-mortar retailers are challenged with providing the consumer with a richer experience than they can obtain online, in order to increase in-store sales, and stay in business. Delivering the right message to the right time to a customer that influences purchasing is one of brick-and-mortar retail's biggest impediments." Furthermore, it notes, "Brick-and-mortar retailers do not have this ability today [to use data driven practices to provide optimized messaging]." This established problem space provides a strong motivation for a POSA to combine existing technologies to enhance in-store personalized marketing.

Combination 1: U.S. Patent No. 8,630,917 ('917) in view of U.S. Patent Application Publication No. 2012/0323671 ('671)

This combination would render the independent claims of the '731 patent obvious.

• U.S. Patent No. 8,630,917 ('917): This patent discloses a system and method for providing in-store targeted marketing. It utilizes sensors to detect the presence of a consumer's mobile device, identifies the consumer (potentially using a stored consumer profile that can include demographics), tracks their location within the store, and delivers targeted content (advertisements or coupons) to their mobile device or a nearby display screen based on their profile and location. Thus, '917 teaches the fundamental concepts of a system, method, server, information monitoring devices (sensors for mobile devices), databases, a tracking module (mobile device tracking), and the use of demographic information from a profile.

• U.S. Patent Application Publication No. 2012/0323671 ('671): This publication details a system and method for shopper-specific in-store advertising using video cameras and facial recognition to identify a shopper's demographic information (age, gender). It also tracks the shopper's path through the store and their dwell time in different areas. Based on this collected data, the system presents targeted advertisements on digital displays within the store. '671 therefore explicitly teaches a detailed "demographic intelligence module" (facial recognition for age and gender) and an alternative or complementary "tracking module" (video-based path and dwell time tracking).

• Motivation for Combination: A POSA, striving to enhance the accuracy and richness of consumer data for in-store targeted marketing, would have been motivated to combine the mobile device tracking capabilities and profile-based demographics of '917 with the advanced camera-based demographic intelligence and video tracking of '671. The '731 patent's background highlights the inadequacy of current retail data. '917 provides one stream of data (mobile device presence and profile demographics), while '671 provides another (visual demographics and granular movement patterns). Combining these disparate, yet complementary, data sources would lead to a more comprehensive understanding of a shopper's real-time behavior and demographics, enabling more precise targeting and personalization. This directly addresses the stated problem in '731 of delivering the "right message to the right customer at the right time." The '731 patent itself explicitly states that its "demographic intelligence module utilizes algorithms known in the art (such as Intel AIM Suite or SightCorp Crowdsight) to determine a person's gender, approximate age, and sentiment (such as based upon video images captured by cameras or other information monitoring device)." The '671 publication provides these exact camera-based demographic and movement tracking features, making its integration into a system like '917 an obvious improvement for a POSA seeking to build a more robust personalized marketing system.

Combination 2: U.S. Patent No. 8,630,917 ('917) or U.S. Patent Application Publication No. 2012/0323671 ('671) in view of U.S. Patent No. 9,031,883 ('883)

This combination would also render the independent claims of the '731 patent obvious.

• U.S. Patent No. 8,630,917 ('917) or U.S. Patent Application Publication No. 2012/0323671 ('671): As described above, these references provide core systems for real-time in-store tracking and demographic analysis for targeted advertising.

• U.S. Patent No. 9,031,883 ('883): This patent focuses on a system that tracks a user's location via their mobile device and sends them relevant offers. It describes creating a user profile which can include demographic data. Crucially, the system analyzes the user's location, profile, and historical data to determine which offers to send.

• Motivation for Combination: A POSA would be motivated to integrate the historical data analysis taught by '883 into the real-time in-store marketing systems of either '917 or '671. While '917 mentions a "stored consumer profile" and '671 tracks path and dwell time, '883 explicitly emphasizes leveraging a broader set of "historical data" (e.g., location history, purchase history) for determining relevant offers. The '731 patent itself explicitly aims to provide a "content rich shopping experience not previously offered...Based off of demographic information, previous purchase history, and online and offline browsing history." This clearly underscores the recognized utility of historical data for personalization. Therefore, a POSA would find it obvious to apply the concept of using historical user data (as taught by '883) to further enhance the personalization of real-time messages generated by systems like '917 or '671. This combination would yield a more effective and "smarter" personalized marketing system, fulfilling a clear market need for enhanced data-driven retail strategies.

Addressing the Independent Claims of US12026731:

Both combinations, driven by the motivation to improve personalized marketing in brick-and-mortar retail, would lead to the obviousness of the '731 patent's independent claims.

• Independent Claim 1 (A System for In-Store Customer Analysis): The combination of '917 and '671 directly teaches all the elements of Claim 1. Both disclose a server, databases, and information monitoring devices (sensors in '917, cameras in '671, both covered by '731's definition). '917 provides a tracking module via mobile device detection, and demographic information via profiles. '671 explicitly provides a demographic intelligence module (facial recognition for age/gender) and a tracking module (video-based path/dwell time). A POSA would combine these to create a system that gathers information and analyzes it using these modules, as taught by both prior art references.
• Independent Claim 2 (A Method for In-Store Customer Analysis): The method claim directly corresponds to the functions of the system. The steps of gathering information, connecting devices to a server/database, implementing demographic intelligence and tracking modules, and analyzing the information gathered by these modules are all explicitly taught or inherently enabled by the combination of '917 and '671, for the motivations described above.
• Independent Claim 3 (A Non-Transitory Computer-Readable Storage Medium): Since the method described in Claim 2 would be obvious based on the combination of prior art, the implementation of that obvious method as computer-executable instructions on a non-transitory computer-readable storage medium would also be obvious to a POSA. This is a conventional means of implementing software-driven systems.