Obviousness

The obviousness of U.S. Patent 11,301,880 under 35 U.S.C. § 103 can be assessed by considering combinations of prior art elements that a person having ordinary skill in the art (PHOSITA) would have been motivated to combine. The patent itself, particularly its Background section and descriptions of various modules, identifies several existing technologies and recognized problems that lay the groundwork for an obviousness argument.

Background in the Art as Described by US11301880

The patent acknowledges several aspects of the prior art and challenges faced by brick-and-mortar retailers at its priority date (July 19, 2013):

• Online retail already possessed the ability to "use data driven practices to provide optimized messaging to their customers that will influence their purchasing," a capability brick-and-mortar retailers lacked.
• A significant challenge for the retail industry was the "lack of consumer purchasing data prior to the sale".
• Existing methods for determining consumer behavior prior to point-of-sale (POS) were limited to "focus groups, traffic counting devices, surveys, feedback from employees, and shopper shadows," none of which provided sufficient information for effective store management or personalized engagement.
• Demographic intelligence algorithms, such as "Intel AIM Suite or SightCorp Crowdsight," were known in the art for determining a person's gender, approximate age, and sentiment from video images.
• The widespread use of Wi-Fi and Bluetooth in smartphones and mobile devices meant these devices were "continuously broadcasting a header which contains that particular devices Media Access Control (MAC) address".
• The patent states that using "multiple receivers/transmitters in a store with a pre-determined or known location, the system can triangulate on each individual device," and "Using the signal strength and an algorithm, the system is able to determine the distance of the mobile device from the receiver/transmitter of the system," to identify the location and path of each device. This indicates that MAC address tracking and triangulation for location determination were known concepts.
• Expensive products existed that could be installed on shelves "to only watch a customer's eyes and determine where they are looking".

Obviousness Analysis under 35 U.S.C. § 103

The independent claims of US Patent 11,301,880 (Claim 1, Claim 15, and Claim 28) largely center on combining demographic intelligence and tracking (e.g., MAC address tracking) to link and analyze customer information in real-time within a retail or public setting.

Hypothetical Combination of Prior Art References:

A PHOSITA in the field of retail technology or data analytics at the priority date would have been motivated to combine several known technologies to address the explicitly stated deficiencies of brick-and-mortar retail, particularly the "lack of consumer purchasing data prior to the sale" and the inability to "provide the right message to the right customer at the right time".

1. Prior Art Reference A (Demographic Intelligence Systems): The patent itself establishes that "demographic intelligence modules utiliz[ing] 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)" were known prior art. These systems provide "who" the customer is in terms of general characteristics.

2. Prior Art Reference B (Mobile Device Tracking Systems): The patent describes the existing capability of "Smart phones and other mobile devices today hav[ing] WIFI and Bluetooth built into them" and "continuously broadcasting a header which contains that particular devices Media Access Control (MAC) address". It further notes that "multiple receivers/transmitters in a store with a pre-determined or known location" can "triangulate on each individual device" to "identify the location of each device at any given time" and determine the customer's path and dwell times. These systems provide "where" the customer is and "how" they move.

3. Prior Art Reference C (Online Retail Personalization and Real-time Data Use): The Background section highlights that "Online retail has the ability to use data driven practices to provide optimized messaging to their customers that will influence their purchasing" and that "Today's shopper expects the information they are provided in-store to be relevant to their needs". This represents the general knowledge in the art that personalized, data-driven engagement, ideally in real-time, is desirable and effective for influencing purchasing decisions.

Motivation for a PHOSITA to Combine:

A PHOSITA, faced with the challenges outlined in the patent's background—such as showrooming, the inability to provide a "richer experience" than online retail, and the lack of pre-POS consumer data—would have a clear motivation to combine Prior Art References A, B, and C.

• Bridging the Online/Offline Gap: The primary motivation would be to bring the data-driven personalization capabilities of online retail (Ref C) to the brick-and-mortar environment. Online retailers already used customer data (demographics, browsing history, etc.) to tailor offers and information in real-time. A PHOSITA would recognize the value in applying similar strategies to physical stores.
• Enhancing Customer Understanding: Combining demographic information (Ref A) with detailed in-store movement and dwell time data (Ref B) would allow for a much more comprehensive understanding of a customer's behavior than either system could provide alone. Knowing who (demographics) is looking at what (product location/dwell time via tracking) would directly address the "lack of consumer purchasing data prior to the sale" and provide insights into "effectiveness of store layout, inventory management, merchandising, at-shelf promotion, sales team positioning, and product feedback".
• Enabling Real-time Engagement: Given the competitive nature of retail and the need to influence immediate purchasing decisions, a PHOSITA would naturally strive for "real-time" analysis to facilitate "engaging digital customer experiences". The real-time analysis of linked demographic and tracking data would be essential for delivering timely and relevant messages or assistance to customers while they are still in the store, thereby replicating the dynamic responsiveness of online retail (Ref C).
• Addressing Specific Problems: For example, if a known demographic system (Ref A) identifies a young male, and a known MAC tracking system (Ref B) shows that individual dwelling near a particular product category (e.g., video games), combining this information to infer an interest and then delivering a personalized message (inspired by online personalized advertising, Ref C) would be an obvious solution to influencing sales.

Application to Independent Claims:

• Claim 1 (System): The claimed system's components (server, information monitoring devices, databases) are generic. The combination of a demographic intelligence module (Ref A) and a tracking module (Ref B) to "link" and "analyze... in real-time" (motivated by Ref C) the collected information about a person's behavior at a location (e.g., a retail store) would be an obvious design choice for a PHOSITA seeking to improve in-store customer engagement and data collection. The elements of the claim, such as tracking a person within a predetermined area and analyzing linked information in real-time, are directly derivable from the motivation to combine the described prior art.

• Claim 15 (Method): The method steps mirror the system claim. Using known information monitoring devices to gather data (demographics via cameras, location via Wi-Fi/Bluetooth signals), employing known modules (Ref A and Ref B) to process this data, and then performing the "linking" and "real-time analyzing" steps would be obvious to a PHOSITA motivated to adapt successful online personalization strategies (Ref C) to a physical retail environment.

• Claim 28 (Computer-Readable Storage Medium): If the method described in Claim 15 is rendered obvious by the combination of prior art, then tangibly encoding computer-executable instructions to perform this obvious method on a computer-readable storage medium would also be obvious to a PHOSITA.

In conclusion, the combination of known demographic intelligence systems, known mobile device tracking technologies, and the recognized need for real-time, data-driven personalization in brick-and-mortar retail (as evidenced by online retail practices) would render the claims of US Patent 11,301,880 obvious to a PHOSITA at the time of the invention.