Obviousness

The provided patent text for US Patent 11,042,890, titled "Method and system for customer assistance in a retail store," outlines a "Prior art date" of July 19, 2013, and "Prior art keywords" such as "information," "customer," "person," "product," and "devices." However, it does not explicitly cite or reference specific prior art publications or patents that could be combined for an obviousness analysis under 35 U.S.C. § 103. Therefore, this analysis will rely on the general state of the art as described within the patent's "BACKGROUND" section, which represents knowledge available to a person having ordinary skill in the art (PHOSITA) at the priority date.

General State of the Art (as described in US11042890's Background)

The patent itself details the challenges faced by brick-and-mortar retailers prior to the invention. These challenges highlight the existing technological landscape and the recognized problems in the retail industry at the time:

• Online vs. Brick-and-Mortar: Online retail leveraged "data driven practices to provide optimized messaging to their customers that will influence their purchasing," an ability brick-and-mortar retailers "do not have today."
• Lack of Pre-Sale Data: The retail industry faced "the lack of consumer purchasing data prior to the sale." Existing methods for determining pre-POS consumer behavior included "focus groups, traffic counting devices, surveys, feedback from employees, and shopper shadows," all deemed insufficient.
• Customer Information Gap: Consumers expect relevant in-store information, but store associates often lack sufficient product knowledge, and "trusted third party reviews—which are not available in-store today" often lead customers to competitor websites via mobile devices (showrooming).
• Known Technologies: The patent mentions the existence of "very expensive products that can be installed on shelves to only watch a customer's eyes and determine where they are looking." It also refers to demographic intelligence "algorithms known in the art (such as Intel AIM Suite or SightCorp Crowdsight)" to determine age, gender, and sentiment. Furthermore, it acknowledges that "Smart phones and other mobile devices today have WIFI and Bluetooth built into them" and "are continuously broadcasting a header which contains that particular devices Media Access Control (MAC) address." The patent also describes that using signal strength and algorithms, "the system is able to determine the distance of the mobile device from the receiver/transmitter of the system."

Motivation to Combine Known Technologies

The "BACKGROUND" section of US11042890 provides a strong motivation for a PHOSITA to combine existing technologies. The overarching problem is the inability of brick-and-mortar retailers to offer "a richer experience than they can obtain online" and to "provide the right message to the right customer at the right time" to combat "showrooming" and increase in-store sales.

A PHOSITA in the field of retail technology, recognizing these explicit needs, would be motivated to adapt and integrate known data-gathering and personalization techniques (prevalent in online retail) into physical store environments. The goal would be to bridge the gap in customer behavior data prior to sale and to deliver targeted, real-time engagement to in-store shoppers.

Obviousness Analysis of Independent Claims

Given the general state of the art as described, the independent claims (Claim 1: system, Claim 26: method, Claim 49: computer-readable medium) appear to combine known elements and functionalities in a manner that would have been obvious to a PHOSITA, motivated by the clearly articulated problems in the retail industry.

Combination of Known Elements:

1. Demographic Intelligence: The patent explicitly states that algorithms for determining a person's gender, approximate age, and sentiment were "known in the art (such as Intel AIM Suite or SightCorp Crowdsight)." A PHOSITA would understand how to incorporate such a "demographic intelligence module" into a system for customer analysis.
2. Tracking Modules (e.g., MAC address tracking): The patent describes the known behavior of mobile devices broadcasting MAC addresses and methods to determine location via signal strength and triangulation. Therefore, a "tracking module" utilizing MAC addresses (or other mobile device tracking) would be a known technical capability. "Traffic counting devices" were also known, albeit considered insufficient.
3. Information Monitoring Devices: Cameras, sensors, displays, Wi-Fi devices, and kiosks were common electronic devices capable of gathering information.
4. Server, Databases, Software Modules: These are standard components of any computing system designed for data processing and management.
5. Interactive Displays and Engagement: Digital signage and interactive displays for marketing and information dissemination were known in various commercial settings.
6. Real-time Analysis and Personalized Messaging: Online retail already demonstrated the benefits of "data driven practices" for "optimized messaging" in real-time. The application of real-time data processing to local, in-store data would be an expected extension of these known online capabilities.

Obvious Combination:

A PHOSITA, faced with the challenge of providing brick-and-mortar retailers with "a richer experience than they can obtain online" and the ability to "provide the right message to the right customer at the right time", would be motivated to combine the following known elements:

• Combine known demographic intelligence systems (e.g., using cameras and known algorithms) with known mobile device tracking techniques (e.g., MAC address sniffing and triangulation using Wi-Fi receivers). The motivation is to generate comprehensive customer profiles including demographics and movement patterns, which is a clear enhancement over existing "focus groups, traffic counting devices, surveys, feedback from employees, and shopper shadows." The patent itself states the system "can be able to link the information from the person gathered in the demographic intelligence module and the tracking module", suggesting this linkage was a recognized beneficial step.
• Integrate these data gathering and analysis capabilities into a central server and database system to process the information in real-time. This addresses the "lack of consumer purchasing data prior to the sale" and mimics the "data driven practices" of online retail.
• Connect this system to in-store interactive displays to deliver personalized marketing and advertising messages based on the real-time analyzed demographic and tracking data. This directly addresses the "biggest impediments" of "Delivering the right message to the right time to a customer that influences purchasing" and aims to provide the "richer experience" desired by brick-and-mortar stores.

The independent claims, in essence, describe a system and method for applying data-driven personalization techniques, already proven in online retail, to the physical retail environment using existing and well-understood technologies for data collection (demographics, tracking) and delivery (interactive displays). The motivation to do so is explicitly and strongly articulated in the patent's own background section, making the combination of these known elements and functionalities to achieve the described outcomes an obvious endeavor for a PHOSITA at the time of the invention.