Data processing system for location-based content filtering with optimized transmission protocols

Abstract

A computer-implemented system processes store data from multiple retail locations and content posts from store-based users to provide location-filtered retail content to user devices. The system may employ geolocation to determine user proximity to retail stores and multi¬ criteria filtering algorithms to content posts based on user preferences and real-time location data. Technical innovations include optimized database indexing for rapid location -based content retrieval, adaptive notification algorithms that identify users meeting proximity and preference criteria, and efficient content aggregation protocols that consolidate multiple store¬ based user posts into unified feeds. The system implements near-field communication and / or QR code scanning to trigger content display. Processing optimizations may include compressed transmission protocols and caching mechanisms that pre-load location-relevant content based on user movement patterns, resulting in improved response times and reduced bandwidth consumption for mobile retail content delivery.

Description

Docket No.: RFIX-001-US-PCT1DATA PROCESSING SYSTEM FOR LOCATION-BASED CONTENT FILTERING WITH OPTIMIZED TRANSMISSION PROTOCOLSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Pat. App. No. 63 / 688,106 filed on August 28, 2024, the entire contents of which are hereby incorporated by reference herein.FIELD

[0002] The present disclosure generally relates to computing systems and data processing — more specifically, the present teachings may include geolocation-based data filtering systems combined with end user preferences that optimize content transmission and processing efficiency.BACKGROUND

[0003] In recent years, the retail industry has undergone significant transformations due to the rise of e-commerce and changing consumer behaviors. While online shopping has grown in popularity, brick-and-mortar stores still play a crucial role in the retail ecosystem. However, traditional physical stores face challenges in attracting and engaging customers in an increasingly digital world. Digital engagement in general, and mobile engagement in particular, is now demanded by most consumers today who are in their prime shopping years.

[0004] Local businesses, in particular, often struggle to compete with large e- commerce platforms and chain stores. These smaller retailers may lack the resources to develop sophisticated digital marketing strategies. As a result, they may miss opportunities to connect with potential customers who increasingly rely on digital channels for product discovery and shopping decisions. Additionally, the proliferation of smartphones and mobile applications has changed how consumers interact with businesses and make purchasing decisions. Many shoppers now use their mobile devices to research products, compare prices, and read reviews while in stores. However, existing mobile applications often focus on either e-commerce or general social media, leaving a gap in solutions specifically tailored to enhance the local shopping experience.

[0005] Further, the retail industry has seen a growing interest in personalized shopping experiences and targeted marketing. Consumers are more likely to engage with content and offers that are relevant to their interests and preferences. However, delivering such personalized experiences across multiple stores and brands in a local context presents significant challenges. Another trend in the retail sector is the increasing importance of user-generated content inDocket No.: RFIX-001-US-PCT1 influencing purchasing decisions. Consumers often trust recommendations from peers, influencers, and / or authentic reviews more than traditional advertising. This shift has created a need for platforms that can effectively leverage user-generated content in a retail context such as a brick and mortar, local shopping context.

[0006] There remains a need for, e.g., comprehensive solutions that can effectively combine multiple aspects of modem retail and brand consumer engagement, including local discovery, personalized recommendations, user-generated content, and the seamless integration and synergy of online and offline experiences.SUMMARY

[0007] The present disclosure provides a computer-implemented platform for connecting retail stores and brands they carry (and the like) with consumers. In an aspect, the platform receives store data in the form of feeds from multiple retail stores and content posts within the feeds from multiple store-based users, where a user interface displays these feeds / posts to consumers. Users can set preferences related to stores, products, brands, merchandise product categories, store personnel, and so forth, where the platform filters content posts to provide user-curated content. In aspects, geolocation features are available to allow users to discover nearby stores and receive notifications therefrom, and / or location data may be used by the platform to enable stores to provide content posts to nearby users. The platform may support rich media posts, reposting of content, and / or communication between consumer users and store-based users. Additional features may include unique store identifiers for easy connection, gamification elements to encourage engagement, and integration with third-party platforms for expanded content sharing.

[0008] In an example aspect, a computer program product may include computer executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs the steps of: receiving, at a server, store data from a plurality of retail stores; storing the store data at a database in communication with the server; receiving, at the server, one or more content posts from one or more store-based users, the one or more content posts related to the store data from at least one of the plurality of retail stores; providing, on one or more user devices, a user interface programmatically configured to display the one or more content posts; receiving, at the server, one or more user preferences from a user, the one or more user preferences related to one or more of (i) store data and (ii) product data; filtering the one or more content posts based on the one or more user preferences to provide one or more user-curated content posts related to at least one of the plurality of retail stores; and displaying, on a user interface of a user device associated with the user, the one or more user-Docket No.: RFIX-001-US-PCT1 curated content posts related to the at least one of the plurality of retail stores. Other implementations of this aspect include corresponding computer systems, apparatus, methods, and computer programs recorded on one or more computer storage devices, each configured to perform one or more of the aforementioned steps.

[0009] Implementations of this example aspect, or any other example aspect described in this summary section or otherwise herein, may include one or more of the following features. The one or more user-curated content posts may be received from at least two store-based users associated with a single retail store. The computer program product may include code that, when executing on one or more computing devices, performs the step of displaying, on a single feed on the user interface of the user device, content posts received from the at least two store-based users associated with the single retail store. The computer program product may include code that, when executing on one or more computing devices, performs the steps of: receiving, at the server, geolocation data for the user; and displaying, on the user interface of the user device associated with the user, one or more of the plurality of retail stores within a predetermined proximity to the user based on the geolocation data. The computer program product may include code that, when executing on one or more computing devices, performs the steps of: receiving, at the server, a selection of at least one retail store within the predetermined proximity; and displaying, on the user interface of the user device associated with the user, at least one content post from the at least one retail store. The computer program product may include code that, when executing on one or more computing devices, performs the steps of: receiving, at the server, geolocation data for a plurality of users; determining that at least one of the plurality of users meets certain criteria including being located within a predetermined proximity to one or more stores of the plurality of retail stores; and transmitting a notification related to the one or more stores to the at least one of the plurality of users. The certain criteria may further include the one or more stores corresponding to at least one of the one or more user preferences. The notification may include displaying, on a user interface of a user device associated with the at least one of the plurality of users, a content post related to the one or more stores. The notification may include at least one of: a push notification, a text message, and an email. The one or more user preferences may include selection or identification of at least one of: a retail store, a brand, a product, a product type, a product category, demographic information, geographic information, a store type, a favorite store, price information, and information related to a store-based user. The one or more user preferences may include a selection to follow a store-based user. The store data may include at least one of: store identifying information, a store type, geographic information, product information, and information related to a store-based user. The one or more content posts may include at least one of: product data, a messaging post,Docket No.: RFIX-001-US-PCT1 brand data, and brand availability. The product data may include at least one of product availability, product information, pricing information, and a link to purchase a product. The one or more content posts may include reposted content. The reposted content may include content from a third-party platform. The third-party platform may be a social media platform. The reposted content may include influencer content. The reposted content may include at least one of a previous content post and a revised version of the previous content post. The one or more user-curated content posts may be displayed in a feed format. The one or more user-curated content posts may include rich media. The computer program product may include code that, when executing on one or more computing devices, performs the steps of: providing a unique store identifier; receiving a scan of the unique store identifier by the user device; and in response to receiving the scan, displaying, on the user interface of the user device, at least one content post from a store associated with the unique store identifier. The computer program product may include code that, when executing on one or more computing devices, performs the steps of: providing a unique store signal; receiving the unique store signal by the user device; and in response to receiving the unique store signal, displaying, on the user interface of the user device, at least one content post from a store associated with the unique store signal. The unique store signal may be provided via near-field communication. The computer program product may include code that, when executing on one or more computing devices, performs the step of providing a chat interface for communication between the user and one or more store-based users. The one or more store-based users may earn points for one or more engagement activities. The one or more engagement activities may include creation of a content post. Implementations of the described techniques may include hardware, a method or process, and / or computer software on a computer-accessible medium.

[0010] In an example aspect, a method may include: receiving, at a server, store data from a plurality of retail stores; storing the store data at a database in communication with the server; receiving, at the server, one or more content posts from one or more store-based users, the one or more content posts related to the store data from at least one of the plurality of retail stores; providing, on one or more user devices, a user interface programmatically configured to display the one or more content posts; receiving, at the server, one or more user preferences from a user, the one or more user preferences related to one or more of (i) store data and (ii) product data; filtering the one or more content posts based on the one or more user preferences to provide one or more user-curated content posts related to at least one of the plurality of retail stores; and displaying, on a user interface of a user device associated with the user, the one or more user-curated content posts related to the at least one of the plurality of retail stores.Docket No.: RFIX-001-US-PCT1

[0011] In an example aspect, a system may include a data network, a plurality of processors coupled to the data network, and a remote computing resource coupled to the data network, the remote computing resource including a processor and a memory, the memory storing code executable by the processor to perform the steps of: receiving store data from a plurality of retail stores; storing the store data at a database in communication with the remote computing resource; receiving one or more content posts from one or more store-based users, the one or more content posts related to the store data from at least one of the plurality of retail stores; providing, on one or more user devices, a user interface programmatically configured to display the one or more content posts; receiving one or more user preferences from a user, the one or more user preferences related to one or more of (i) store data and (ii) product data; filtering the one or more content posts based on the one or more user preferences to provide one or more user-curated content posts related to at least one of the plurality of retail stores; and displaying, on a user interface of a user device associated with the user, the one or more user- curated content posts related to the at least one of the plurality of retail stores.

[0012] These and other features, aspects, and advantages of the present teachings will become better understood with reference to the following description, examples, and appended claims.BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The foregoing and other objects, features and advantages of the devices, systems, and methods described herein will be apparent from the following description of some of the particular embodiments thereof, as illustrated in the accompanying drawings. The drawings are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the devices, systems, and methods described herein. In the drawings, like reference numerals generally identify corresponding elements.

[0014] Fig. 1 illustrates a system for providing a computer-implemented platform for local retail experiences and the like, in accordance with a representative embodiment.

[0015] Fig. 2 is a flow chart of a method for providing a computer-implemented platform for local retail experiences and the like, in accordance with a representative embodiment.

[0016] Fig. 3 is a flow chart of a method for providing a computer-implemented platform for local retail experiences and the like, in accordance with a representative embodiment.

[0017] Fig. 4 shows a consumer-facing interface of a platform according to the present teachings, by way of example.Docket No.: RFIX-001-US-PCT1

[0018] Fig. 5 shows additional components of a consumer-facing interface of a platform according to the present teachings, by way of example.

[0019] Fig. 6A shows two of three example additional components of a consumerfacing interface of a platform according to the present teachings, by way of example.

[0020] Fig. 6B shows the third of the three example additional components of a consumer-facing interface of a platform according to the present teachings, by way of example.

[0021] Fig. 7 shows additional components of a consumer-facing interface of a platform according to the present teachings, by way of example.

[0022] Fig. 8 shows an additional component of a consumer-facing interface of a platform according to the present teachings, by way of example.

[0023] Fig. 9A shows store-user features of a platform according to the present teachings, by way of example.

[0024] Fig. 9B shows a consumer-facing interface of a platform according to the present teachings, by way of example.

[0025] Fig. 10A shows additional store-user features of a platform according to the present teachings, by way of example.

[0026] Fig. 10B shows additional store-user features of a platform according to the present teachings, by way of example.

[0027] Fig. 11 A shows a version of a content creation studio with store-user team management features of a platform according to the present teachings, by way of example.

[0028] Fig. 1 IB shows a version of a content creation studio with store-user team management features of a platform according to the present teachings, by way of example.

[0029] Fig. 12A shows further details and additional features about store-user content creation using a platform according to the present teachings, by way of example.

[0030] Fig. 12B shows further details about the output / results presented to the consumer-user of store-user content creation using a platform according to the present teachings, by way of example.

[0031] Fig. 13 A shows an example of a consumer-user experience enabled by storeuser content creation features of a platform according to the present teachings, by way of example.

[0032] Fig. 13B shows an example of a consumer-user experience enabled by storeuser content creation features of a platform according to the present teachings, by way of example.

[0033] Fig. 14A shows use of geolocation in a consumer-facing interface on a platform according to the present teachings, by way of example.Docket No.: RFIX-001-US-PCT1

[0034] Fig. 14B shows use of geolocation in a consumer-facing interface on a platform according to the present teachings, by way of example.

[0035] Fig. 14C shows use of geolocation in a consumer-facing interface on a platform according to the present teachings, by way of example.

[0036] Fig. 14D shows use of geolocation in a consumer-facing interface on a platform according to the present teachings, by way of example.DETAILED DESCRIPTION

[0037] The embodiments will now be described more fully hereinafter with reference to the accompanying figures, in which preferred embodiments are shown. The foregoing may, however, be embodied in many different forms and should not be construed as limited to the illustrated embodiments set forth herein. Rather, these illustrated embodiments are provided so that this disclosure will convey the scope to those skilled in the art.

[0038] All documents mentioned herein are hereby incorporated by reference in their entirety. References to items in the singular should be understood to include items in the plural, and vice versa, unless explicitly stated otherwise or clear from the text. Grammatical conjunctions are intended to express any and all disjunctive and conjunctive combinations of conjoined clauses, sentences, words, and the like, unless otherwise stated or clear from the context. Thus, the term “or” should generally be understood to mean “and / or” and so forth.

[0039] Recitation of ranges of values herein are not intended to be limiting, referring instead individually to any and all values falling within the range, unless otherwise indicated herein, and each separate value within such a range is incorporated into the specification as if it were individually recited herein. The words “about,” “approximately” or the like, when accompanying a numerical value, are to be construed as indicating a deviation as would be appreciated by one of ordinary skill in the art to operate satisfactorily for an intended purpose. Similarly, words of approximation such as “about,” “approximately,” or “substantially” when used in reference to physical characteristics, should be understood to contemplate a range of deviations that would be appreciated by one of ordinary skill in the art to operate satisfactorily for a corresponding use, function, purpose, or the like. Ranges of values and / or numeric values are provided herein as examples only, and do not constitute a limitation on the scope of the described embodiments. Where ranges of values are provided, they are also intended to include each value within the range as if set forth individually, unless expressly stated to the contrary. The use of any and all examples, or exemplary language (“e.g.,” “such as,” or the like) provided herein, is intended merely to better illuminate the embodiments and does not pose a limitationDocket No.: RFIX-001-US-PCT1 on the scope of the embodiments. No language in the specification should be construed as indicating any unclaimed element as essential to the practice of the embodiments.

[0040] In the following description, it is understood that terms such as “first,” “second,” “top,” “bottom,” “up,” “down,” and the like, are words of convenience and are not to be construed as limiting terms unless specifically stated to the contrary.

[0041] As stated above, a need exists for solutions that can effectively combine multiple aspects of modern retail and brand consumer engagement, including local discovery, personalized recommendations, user-generated content, and the seamless integration and synergy of online and offline experiences. This is particularly true for engaging consumers across multiple retailers and multiple brands. This type of digital offering is highly desired by consumers, but is mostly absent in the marketplace except in the unstructured worlds of overly large social media platforms, where consumers see retailer and brand ads in the same feed they see friends’ birthdays, family vacation photos, national news updates, requests for political activism and donations, high school reunion alerts, local realtor ads, etc. Besides large social media platforms (a high-tech solution, but where existing platforms are poorly organized to meet the needs for specific shopping intent, and are not designed well for localized shopping) and local direct mail mailers (a low-tech solution that is poorly targeted to each consumer’s needs and interests), there are few multi -retail er and multi-brand consumer engagement solutions that meet the needs of today’s consumer.

[0042] In general, the devices, systems, computer-program products, and methods disclosed herein relate to computer-implemented platforms designed to enhance local retail experiences (and the like) through mobile devices and similar. This platform may provide a digital user interface that allows users to interact with a multitude of retail stores and brands in their local area or while traveling. In some aspects, the platform may receive and store data from a plurality of retail stores, and allow store-based users to create and post content related to their store’s products or services, in a managed and coordinated fashion if needed, with management oversight features. This content may then be displayed on the user interface of the platform, which can be accessed via a user’s mobile device, computer, or the like. The platform may also provide the capability to receive and process user preferences related to store data and product data, enabling a personalized and curated experience for each user. The platform may further leverage geolocation data to display retail stores within a predetermined proximity (and / or content posts and / or notifications therefrom) to the user, enhancing the relevance and convenience of the shopping experience.

[0043] Therefore, the present teachings may include one or more of the following features (e.g., all of the following features in certain aspects): 1) a highly-networked platformDocket No.: RFIX-001-US-PCT1 that has successful social media traits but is more specifically designed for retailers and brands to promote to consumers to shop for products and services, and for consumers to engage in multi-retailer and multi-brand product discovery and shopping; 2) geo-location based on user location (at home or traveling), to provide brick-and-mortar new store discovery, product discovery, service discovery (e.g., restaurants, movie theaters, hotel concierge services, and even shoe repair), and brand discovery; 3) geo-location based on the app interface, in-store QR code, and / or NFC / other for each store, to gain consumer engagement in an easy manner to immediately see that store’s feed and also the stores nearby which also may be of interest to maximize a shopping trip; and 4) per-store multiple user implementation and management to drive a single store feed in a manner that works for store teams, which may also or instead include an “enterprise” account or similar where a retailer with multiple stores can choose to manage things centrally. Another feature may include a clear delineation between a general store feed and offers; for which the general store feed allows a consumer to focus on a general understanding of what stores and brands are all about, and facilitate stronger engagement and relationship building, and brand affinity; versus offers allowing a consumer to look more specifically at promotional, sale, and clearance items for a deal, which is often far more transactional in nature.

[0044] It will be understood that, while the present disclosure may emphasize usecases of the present teachings involving retail stores, the present teachings may also or instead be adapted for use in non-retail venues selling products or services, such as hotel concierge desks, designer showrooms, trade shows, conferences, and the like. Thus, where this disclosure refers to “retail stores” or “stores” or similar — unless expressly stated to the contrary or otherwise clear from the context — these terms shall be interpreted to potentially include one or more of the following: traditional brick-and-mortar stores, pop-up shops and temporary retail spaces, department stores, boutiques and specialty shops, grocery stores and supermarkets, electronics retailers, clothing and apparel stores, home goods and furniture stores, bookstores, beauty and cosmetics retailers, restaurants and cafes, service-based businesses (e.g., salons, spas, repair shops, and the like), entertainment venues (e.g., movie theaters, concert halls, sports and other arenas, and the like), museums and art galleries (e.g., with gift shops), fitness centers and gyms (e.g., with retail components), hotels offering their own services and the products and services offered by other businesses nearby, and the like.

[0045] Fig. 1 illustrates a system 100 for providing a computer-implemented platform for local retail experiences and the like, in accordance with a representative embodiment. In general, the system 100 may include a networked environment where a data network 102 interconnects a plurality of participating devices and / or users in a communicating relationship.Docket No.: RFIX-001-US-PCT1The participating devices may, for example, include any number of user devices 110, remote computing resources 120, databases 130, and other resources 140.

[0046] The data network 102 may be any network(s) or internetwork(s) suitable for communicating data and information among participants in the system 100. This may include public networks such as the Internet, private networks, telecommunications networks such as the Public Switched Telephone Network or cellular networks using third generation (e.g., 3G or IMT-2000), fourth generation (e.g., LTE (E-UTRA) or WiMAX- Advanced (IEEE 802.16m)), fifth generation (e.g., 5G), and / or other technologies, as well as any of a variety of corporate area or local area networks and other switches, routers, hubs, gateways, and the like that might be used to carry data among participants in the system 100.

[0047] Each of the participants of the data network 102 may include a suitable network interface comprising, e.g., a network interface card, which term is used broadly herein to include any hardware (along with software, firmware, or the like to control operation of same) suitable for establishing and maintaining wired and / or wireless communications — e.g., a communications interface as described herein or otherwise known in the art. The network interface card may include without limitation a wired Ethernet network interface card (NIC), a wireless 802.11 networking card, a wireless 802.11 USB device, and / or other hardware for wired or wireless local area networking. The network interface may also or instead include cellular network hardware, wide-area wireless network hardware or any other hardware for centralized, ad hoc, peer-to-peer, or other radio communications that might be used to connect to a network and carry data. In another aspect, the network interface may include a serial or USB port to directly connect to a local computing device such as a desktop or laptop computer that, in turn, provides more general network connectivity to the data network 102.

[0048] A user 101 in the system 100 may include shoppers, consumers, customers, and / or individuals interested in browsing, purchasing, and / or learning about products and services offered by retail stores and the like. By way of example, users 101 may be local residents exploring nearby shops, tourists seeking unique local product and / or service offerings, online shoppers looking for evening shopping hours, sales, in-store pickup availability, flexible payment plan options, and so forth. In some cases, users 101 may be individuals looking to be inspired by new products or researching products before making a purchase, comparing prices across different stores, and / or seeking product affirmation (likes), recommendations and reviews from other shoppers.

[0049] A user 101 in the system 100 may also or instead include a store-based user. Store-based users may include employees, managers, owners, product or product category specialists, service specialists, and / or representatives of retail stores and similar establishments.Docket No.: RFIX-001-US-PCT1These may, for example, be sales associates creating product showcase posts, store managers announcing promotions or events, visual merchandisers sharing new window displays, and / or social media coordinators managing the store’s online presence. In some instances, store-based users may also or instead include brand representatives, influencers, or the like, e.g., partnering with specific stores to create content and / or promote the brand’s products.

[0050] The user devices 110 may include any devices within the system 100 operated by one or more users 101 for practicing the techniques as contemplated herein. Specifically, the user devices 110 may include any device for connecting to, and using, a platform according to the present teachings, and / or any device configured to provide, supplement, and / or support functionality of a platform according to the present teachings. The user devices 110 may also or instead include any device for managing, monitoring, or otherwise interacting with tools, platforms, and devices included in the systems and techniques contemplated herein. The user devices 110 may be coupled to the data network 102, e.g., for interaction with one or more other participants in the system 100.

[0051] By way of example, the user devices 110 may include one or more desktop computers, laptop computers, network computers, tablets, mobile devices, portable digital assistants, messaging devices, cellular phones, smart phones, portable media and / or entertainment devices, Internet-connected televisions and the supporting streaming devices / services, or any other computing devices that can participate in the system 100 as contemplated herein. As discussed above, the user devices 110 may include any form of mobile device, such as any wireless, battery-powered device, that might be used to interact with the networked system 100. It will also be appreciated that one of the user devices 110 may coordinate related functions (e.g., providing inputs, retrieving and / or processing data, and the like) as they are performed by another entity such as one of the remote computing resources 120 or other resources 140.

[0052] Each user device 110 may generally provide a user interface on a display 112 thereof, such as any of the user interfaces described herein. The user interface may be maintained by a locally executing application on one of the user devices 110 that receives data from, e.g., the remote computing resources 120 and / or other resources 140. In other embodiments, the user interface may be remotely served and presented on one of the user devices 110, such as where a remote computing resource 120 or other resource 140 includes a web server that provides information through one or more web pages or the like that can be displayed within a web browser or similar client executing on one of the user devices 110. The user interface may in general create a suitable visual presentation for user interaction on a display 112 of one of the user devices 110, and provide for receiving any suitable form of userDocket No.: RFIX-001-US-PCT1 input including, e.g., input from a keyboard, mouse, touchpad, touch screen, voice- or other AI- activated interfaces, hand gesture, or other use input device(s).

[0053] The remote computing resources 120 may include, or otherwise be in communication with, a processor 122 and a memory 124, where the memory 124 stores code executable by the processor 122 to perform various techniques of the present teachings. More specifically, a remote computing resource 120 may be coupled to the data network 102 and accessible to the user device 110 through the data network 102, where the remote computing resource 120 includes a processor 122 and a memory 124, where the memory 124 stores code executable by the processor 122 to perform the steps of a method according to the present teachings.

[0054] The remote computing resources 120 may also or instead include data storage, a network interface, and / or other processing circuitry. In the following description, where the functions or configuration of a remote computing resource 120 are described, this is intended to include corresponding functions or configuration (e.g., by programming) of a processor 122 of the remote computing resource 120, and / or a processor 122 in communication with the remote computing resource 120. In general, the remote computing resources 120 (or processors 122 thereof or in communication therewith) may perform a variety of processing tasks related to providing a platform and / or its various features as discussed herein. For example, the remote computing resources 120 may manage information received from one or more of the user devices 110, and provide related supporting functions such as analyzing and processing data (e.g., normalizing data, prioritizing data, filtering data, and so forth), storing data, communicating with third-party resources, communicating with local resources, communicating with other resources 140, implementing one or more machine learning models 126 (and similar models and / or algorithms), transmitting and / or retrieving data from one or more databases 130, and the like. The remote computing resources 120 may also or instead include machine learning models 126 and / or backend algorithms, e.g., that react to actions performed by a user 101 at one or more of the user devices 110 or otherwise perform / enable functionality of a platform as described herein. The machine learning models 126 and / or backend algorithms may also or instead be located elsewhere in the system 100.

[0055] Thus, the remote computing resources 120 may incorporate machine learning models 126 and / or artificial intelligence (Al) algorithms to enhance various aspects of the platform. Two examples of potential Al-driven components are provided for illustrative purposes, but the present teaching’s use of Al-driven components are not limited to these examples. First, to use Al features like Large Language Models (LLMs) to ingest a store or brand’s web site, marketing materials, and product information, and then use LLM techniques toDocket No.: RFIX-001-US-PCT1 assist store users in writing content and choosing images and video to inform end users of a store or brand’s product or services via new store user content, with increased store user efficiency and accuracy and always in ‘the voice of the store or brand.’ Second, with increasing scale of users, store teams, stores and brands to analyze user behavior, preferences, and interactions within the system 100 to provide personalized experiences and improve overall functionality. In some aspects, machine learning models 126 may be employed to develop recommendation systems that suggest relevant products and / or services, stores, brands, promotions and / or content to users 101 based on their browsing history, purchase patterns, store, brand and product category affinity, stated preferences, demographics, and so on. These models may analyze large datasets of user interactions to identify patterns and make predictions about user interests and future behaviors. More generally, Al algorithms may also or instead be used in other ways to optimize content curation and delivery. For example, the system 100 may use natural language processing techniques to analyze user-generated content, such as reviews and comments, to extract information. This analysis may help in presenting the most relevant and impactful content to users 101. In some cases, computer vision algorithms may be integrated into the platform to enhance visual search capabilities. For example, users 101 may be able to upload images of products of interest, where the system 100 uses Al to identify similar items available from local retailers. The platform may also or instead leverage Al for dynamic pricing strategies, allowing retailers to optimize their pricing based on various factors such as demand, inventory levels, and competitor pricing. Machine learning models 126 may analyze market trends and consumer behavior to suggest optimal pricing strategies for store-based users. Further, chatbots and virtual assistants powered by Al may be implemented to provide instant customer support and other forms of personalized shopping assistance. These Al-driven assistants may be capable of answering product-related questions, providing store information, assisting with purchase decisions, and the like. In some implementations, predictive analytics powered by machine learning may be used to forecast trends, helping retailers make informed decisions about inventory management and marketing strategies. These predictive models may analyze historical data, seasonal patterns, and external factors to provide valuable insights. The present teachings may thus provide a solid foundation for a novel store and customer interaction that will be able to take advantage of Al innovation as it unfolds in the marketplace.

[0056] The remote computing resources 120 may also or instead include a web server or similar front end that facilitates web-based access by the user devices 110 to the capabilities of the remote computing resource 120 and / or other components of the system 100. A remote computing resource 120 may also or instead communicate with other resources 140 in order to obtain information for providing to a user 101 through a user interface on a display 112 of theDocket No.: RFIX-001-US-PCT1 user device 110. Where the user 101 specifies certain criteria for data processing, this information may be used by a remote computing resource 120 (and any associated machine leaning models and / or algorithms) to access other resources 140. Additional processing may be usefully performed in this context such as recommending certain data processing operations and techniques.

[0057] A remote computing resource 120 may also or instead be configured to manage access to certain content (e.g., for an enterprise associated with a user 101 of the user device 110). In one aspect, a remote computing resource 120 may manage access to a component of the system 100 by a user device 110 according to input from a user 101.

[0058] A remote computing resource 120 may also or instead maintain, or otherwise be in communication with, a database 130 of content, along with an interface for users 101 at the user devices 110 to utilize the content of such a database 130. This may include one or more local, remote, in-house, and / or third-party databases 130. The database 130 may store raw data, processed data, user inputted data, filtered data, rules for data processing and / or analysis, and so on.

[0059] Content included in such a database 130 may include store data 132 and / or user preferences 134. In some aspects, the store data 132 may include at least one of store identifying information (e.g., name, address, and the like), store type including brands carried and featured product categories, geographic information, product information, information related to store-based users, and so forth. In some aspects, product information may include at least one of product availability, product descriptions, pricing information, links to purchase products, and so forth.

[0060] User preferences 134 stored in the database 130 may include selections and / or identifications of at least one of retail stores, brands, services, products, product types, product categories, demographic information, geographic information, store types, favorite stores, favorite product categories, price ranges, information related to store-based users, preferred shopping times, preferred promotional types, and so forth. In some cases, user preferences 134 may also include selections to follow specific stores, store-based users, brands, products, services, and so forth. It will be understood that the store data 132 and the user preferences 134 may include the same or similar data, and in such aspects, filtering for providing a user-curated content feed may include comparing the user preferences 134 to the store data 132.

[0061] The database 130 may also or instead store content posts 136 created by storebased users. These posts may include, for example, one or more of product data, services information, messaging posts, promotional messages, brand data, brand availability information, sales information, event information and announcements, and the like. In some instances, theDocket No.: RFIX-001-US-PCT1 database 130 may contain reposted content such as: content from third-party platforms, such as social media posts and / or influencer content; revised (e.g., updated) prior posts such as updates on product availability; and the like.

[0062] The database 130 may also or instead store geolocation data for users 101, allowing the system 100 to provide location-based services and recommendations. It may also include data related to user interactions with the platform, such as viewing history, purchase history, and engagement with content posts. In some aspects, the database 130 may store information related to a gamification system, including points earned by store-based users for various engagement activities. It may also or instead contain data necessary for implementing features such as chat interfaces between consumers and store-based users.

[0063] The other resources 140 may include any resources that may be usefully employed in the devices, systems, computer program products, and methods as described herein. For example, the other resources 140 may include without limitation other data networks, human actors (e.g., programmers, researchers, annotators, editors, analysts, and so forth), sensors (e.g., audio or visual sensors), data mining tools, computational tools, data monitoring tools, and so forth. The other resources 140 may also or instead include any other software or hardware resources that may be usefully employed in the networked applications as contemplated herein. For example, the other resources 140 may include payment processing servers or platforms used to authorize payment for access, content or feature purchases, or otherwise. In another aspect, the other resources 140 may include certificate servers or other security resources for third-party verification of identity, encryption or decryption of data, and so forth. In another aspect, the other resources 140 may include a desktop computer or the like co-located (e.g., on the same local area network with, or directly coupled to through a serial or USB cable) with one of the user devices 110 or remote computing resources 120. In this case, the other resource 140 may provide supplemental functions for the user device 110 and / or remote computing resource 120. Other resources 140 may also or instead include supplemental resources such as scanners, cameras, printers, input devices, and so forth.

[0064] The other resources 140 may also or instead include one or more web servers that provide web-based access to and from any of the other participants in the system 100. While depicted as a separate network entity, it will be readily appreciated that the other resources 140 (e.g., a web server) may also or instead be logically and / or physically associated with one of the other devices described herein, and may, for example, include or provide a user interface for web access to a remote computing resource 120 or a database 130 in a manner that permits user interaction through the data network 102, e.g., from a user device 110.Docket No.: RFIX-001-US-PCT1

[0065] It will be understood that the participants in the system 100 may include any hardware or software to perform various functions as described herein. For example, one or more of the user device 110 and the other resources 140 may include a memory 124 and a processor 122.

[0066] The various components of the networked system 100 described above may be arranged and configured to support the techniques described herein in a variety of ways. For example, in one aspect, a user device 110 connects through the data network 102 to a server (e.g., that is part of one or more of the remote computing resource 120 or other resources 140) that performs a variety of processing tasks related to providing a platform as described herein and / or providing functionality of such a platform. For example, the remote computing resource 120 may include a server that hosts a website and / or mobile application or the like that runs a platform as described herein. Such permissions related to the system 100 may include one or more of the following: content creation permissions (e.g., store-based users may be granted permissions to create and publish different types of content posts, such as product showcases, promotional announcements, store updates, etc. — in some cases, junior staff may have limited posting capabilities, while managers or owners for each store may have full posting, editing, and deletion rights for all store content created by all store users); media upload permissions (e.g., the system 100 may allow certain store-based users to upload and attach various media types to their posts, including images, videos, audio files, etc.); editing and deletion permissions; interaction permissions; analytics access; user management permissions; brand collaboration permissions; promotional tool access; inventory management permissions; geolocation feature access; and the like. These permission levels may be customizable and adjustable based on the specific needs of each retail store, their organizational structure, and the nature of the business relationship they have with each brand company partner. The system 100 may provide tools for store administrators to manage and oversee these permissions, ensuring appropriate access control and security within the platform.

[0067] Fig. 2 is a flow chart of a method 200 for providing a computer-implemented platform for local retail experiences and the like, in accordance with a representative embodiment. The method 200 illustrated in Fig. 2 may be performed by one or more of the components of the system 100 described above. For example, a remote computing resource 120 may execute instructions stored in memory 124 to perform various steps of the method 200. In some aspects, the method 200 may be implemented as a computer program product comprising computer executable code embodied in a non-transitory computer readable medium that, when executing on one or more computing devices, performs one or more steps of the method 200.Docket No.: RFIX-001-US-PCT1

[0068] As shown in step 202, the method 200 may include receiving — e.g., at a server, remote computing resource, or the like — store data from a plurality of retail stores. In some aspects, the store data may include at least one of: store identifying information (e.g., store name, store address, store number, and the like); store type (e.g., grocery store, convenience store, apparel store, sporting goods store, movie theater, event venue, and the like); geographic information (e.g., location data, description of location, parking information, and the like); product information (e.g., product availability, product descriptions, pricing information, links to purchase products, brand information, release dates / times, and the like); more general product category and brand information to inform and educate users as to the more general nature of the store’s products and services, information related to store-based users (e.g., name or other identifying information, demographics, likes / dislikes, interests, style, credentials, expertise, and the like); and the like.

[0069] A server and / or remote computing resource may be configured to receive this store data — and / or other data described herein — through various means, such as direct input from store-based users, automated data feeds from retail store management systems or third- party content management systems (e.g., CMS vendors like HootSuite or similar), and / or through integration with existing e-commerce and related platforms. In some cases, the server may periodically update the store data to ensure that information remains current and accurate.

[0070] As shown in step 204, the method 200 may include storing the store data at a database in communication with the server, remote computing resource, or the like. In some aspects, the database may be part of a remote computing resource or it may be a separate database within a system 100. In some implementations, the database may organize and index the stored data to facilitate efficient retrieval and processing for various platform functions. The system may employ data structures and algorithms optimized for quick searches and updates, allowing for real-time access to store information when needed. The stored data may be used to support various features of the platform. For example, the product information may be used to populate content posts created by store-based users and / or to provide detailed product information to users browsing the platform.

[0071] The database may also store historical data, allowing the system to track changes in store information over time. This historical data may be used for analytics purposes, helping stores understand trends in their product offerings and / or customer engagement. In some aspects, the database may employ access control mechanisms to ensure that only authorized users can access or modify specific portions of the store data. This may align with the permission levels implemented in the system, where different types of store-based users have varying levels of access to create, edit, and / or delete store information.Docket No.: RFIX-001-US-PCT1

[0072] In some implementations, the database may support real-time synchronization with other components of the system. For example, when a store-based user updates product information through their user interface, these changes may be immediately reflected in the stored data and propagated to relevant parts of the system.

[0073] In some implementations, the method 200 may involve processing the received store data to extract relevant information or to standardize the data format across different retail stores. This processing may involve using machine learning models and / or other algorithms to categorize products, identify trends, and / or generate additional metadata that can enhance the user experience on the platform. The server may also be configured to associate the received store data with specific user accounts for store-based users, allowing for personalized access and management of the store information within the platform. This association may be based on user authentication and the permission levels granted to different types of store-based users.

[0074] As shown in step 206, the method 200 may include receiving — e.g., at a server, remote computing resource, or the like — one or more content posts from one or more storebased users. The content posts may be related to the store data from at least one of the plurality of retail stores. In some aspects, the content posts may include product data, messaging posts, brand data, brand availability information, and the like. The server or remote computing resource may be configured to receive content posts through various means, such as a mobile application and / or web interface executed on user devices. Store-based users with appropriate permissions may create and submit these posts, which may then be processed and stored by the platform. Product data included in a content posts may be any as described herein. In some cases, this information may be automatically populated by scraping e-commerce product pages or the like.

[0075] In some implementations, the content posts may include rich media such as images, videos, and / or audio files. The platform may support various file formats and implement compression algorithms to optimize storage and transmission of these media files.

[0076] A platform according to the present teachings may support the creation of reposted content. This may include content from third-party platforms such as social media, influencer content, and the like. This may also or instead include revised versions of previous content posts, such as updates to product availability, pricing, and the like. The ability to repost content may allow store-based users to leverage existing marketing efforts, provide interesting and timely updates to drive store traffic and sales, and reach a wider audience.

[0077] In some aspects, the platform may implement an artificial intelligence component to enhance product descriptions and generate sales pitches tailored to specificDocket No.: RFIX-001-US-PCT1 products and store branding. This Al-enhanced content creation may make the product posts more effective in promoting products and attracting customers

[0078] The method 200 may also include validating and processing the received content posts. This may involve checking for compliance with platform guidelines, filtering inappropriate content, optimizing the posts for display on various user devices, and the like.

[0079] As shown in step 208, the method 200 may include providing, on one or more user devices, a user interface programmatically configured to display one or more content posts. In some aspects, this user interface may be designed to present the content posts in a visually appealing and user-friendly manner, optimized for various device types and screen sizes.

[0080] The user interface may thus display one or more user-curated content posts related to at least one of the plurality of retail stores. These posts may be filtered based on one or more user preferences received from the user, which may be related to store data and / or product data. The filtering process may utilize machine learning models to provide a personalized content feed for each user.

[0081] In some implementations, the user interface may present the content posts in a feed format, allowing users to scroll through a continuous stream of updates from their preferred stores and / or brands. The feed may include rich media elements such as images, videos, augmented reality, virtual reality, Al-enhanced content, and / or interactive elements to enhance user engagement.

[0082] The user interface may also or instead incorporate features that allow users to interact with displayed content posts. For example, users may be able to like, comment on, share, and perform similar actions related to posts directly from their feed. In some cases, the interface may include options for users to save specific posts for later viewing, and / or to add products featured in posts to a saved post to plan a shopping trip. The interface may also or instead include options for users to create a wish list, shopping cart, or the like, and / or perform similar actions. In some aspects, a user may be able to make a reservation, appointment, or similar using the platform. Also or instead, a user may be able to reserve the right to purchase a product via the platform partnering with the store’s ecommerce site, set up reminders related to product releases, and similar.

[0083] In some aspects, the user interface may integrate geolocation features, displaying content posts from retail stores within a predetermined proximity to the user based on their current location. This may help users discover local shopping opportunities and special offers.

[0084] As shown in step 210, the method 200 may include receiving — e.g., at a server, remote computing resource, or the like — one or more user preferences from a user. TheDocket No.: RFIX-001-US-PCT1 preferences may be related to one or more of: (i) store data, (ii) brand data, and (iii) product or product category data, and the like. In some aspects, one or more user preferences may include selection or identification of various elements that enhance the user’s shopping experience and personalize the content that they shall receive using a platform according to the present teachings.

[0085] By way of example, the user preferences may include selection or identification of at least one of: a retail store, a brand, a product, a product type, a product category, demographic information (e.g., demographic information for the user or related users), geographic information, a store type, a favorite store (and / or other favorites), price information, information related to a store-based user (e.g., favorite users and / or user types, interests, and so forth), and the like. In some cases, the user preferences may include a selection to follow a storebased user, allowing the user to receive updates and content from specific store representatives and / or influencers.

[0086] The system may provide various methods for users to input their preferences. This may include interactive questionnaires, browsing history analysis, allowing users to manually select their interests through the user interface, and the like. In some implementations, the system may use machine learning algorithms to infer user preferences based on their interactions with the platform, such as the types of content they engage with most frequently.

[0087] The user preferences may be stored in the database and associated with the user’s account. This allows the system to maintain a persistent profile of the user’s interests and preferences, which can be updated over time as the user’s shopping habits and interests evolve. In some aspects, the system may allow users to set different preference profiles for different contexts. For example, a user may have one set of preferences for everyday shopping and another for special occasions or gift shopping. This flexibility can provide a more nuanced and personalized experience for users.

[0088] The platform may implement privacy controls that allow users to manage how their preference data is used and shared within the platform. Users may have the option to keep certain preferences private or to share them with specific stores or brands to receive more targeted offers and recommendations. In some implementations, the user preferences may include settings for notification frequency and / or type. Users may be able to specify how often they want to receive updates from stores or brands, and through which channels (e.g., push notifications, emails, SMS marketing messaging, in-app alerts, and the like).

[0089] The user preferences received in this step 210 may be used in subsequent steps of the method 200, such as filtering content posts to provide user-curated content that alignsDocket No.: RFIX-001-US-PCT1 with the user’s interests and preferences. This personalization can significantly enhance the user’s experience on the platform, making it more relevant and engaging.

[0090] As shown in step 212, the method 200 may include receiving — e.g., at a server, remote computing resource, or the like — geolocation data for a user, e.g., a plurality of users and / or a particular user. The geolocation data may be obtained from user devices, which may include smartphones, tablets, computers, and / or other devices equipped with GPS capabilities or other location-determining technologies. The platform may receive this data through various means, such as a mobile application installed on a user device or through a web interface accessed by the user.

[0091] In some implementations, the geolocation data may include latitude and longitude coordinates, speed and direction of movement, and / or accuracy metrics. The system may process this raw data to determine the user’s precise location or general area and mode of transport (e.g., sitting, walking, driving / mass transit — by way of example, a person driving by a shopping district may not be targeted while the person walking or sitting in the district would be). The frequency of geolocation data updates may vary depending on user settings and system requirements. In some cases, the system may receive real-time location updates, while in others, it may receive periodic updates or location data only when the user actively engages with the application. In some aspects, users may be able to set different privacy levels for different contexts or temporarily disable location sharing.

[0092] Receiving geolocation data may enable various location-based features within a platform according to the present teachings. For example, it may allow the system to display retail stores within a predetermined proximity to the user. This feature may enhance the user’s shopping experience by providing relevant, location-specific content and offers. In some implementations, the system may use the geolocation data in conjunction with other user data, such as preferences and browsing history, to provide highly personalized recommendations and notifications. For instance, the system may alert a user about a nearby store that carries a product in which they have previously shown interest.

[0093] The geolocation data may also or instead be used to support features such as instore navigation, augmented or virtual reality experiences, previously Internet-only flash sales with short expirations, and other location-based games that encourage users to visit physical retail locations, and the like. These features may help bridge the gap between online and offline shopping experiences, creating a more engaging and interactive platform for users. These gamification elements may be tied to consumer loyalty programs for each store.

[0094] As shown in step 214, the method 200 may include determining that at least one user meets certain criteria including being located within a predetermined proximity to oneDocket No.: RFIX-001-US-PCT1 or more stores of the plurality of retail stores. In some aspects, this determination may be made by analyzing the geolocation data received in step 212. The system may compare the user’s location to the geographic information stored in the database for each of the plurality of retail stores. In some implementations, the predetermined proximity may be a fixed distance, such as a radius around the user’s current location. In other cases, the proximity may be dynamically adjusted based on factors such as the density of retail stores in the area, the user’s mode of transportation, the user’s historical shopping patterns, user settings, and the like. In some aspects, the system may use machine learning algorithms to optimize the definition of “predetermined proximity” for each user. For example, the system may learn that a user is willing to travel further for certain types of stores or products, and may adjust the proximity threshold accordingly.

[0095] The criteria for determining whether a user meets the proximity requirement may also or instead include additional factors beyond physical distance. In some implementations, the system may consider the user’s direction of travel, speed, and predicted route to determine if they are likely to pass near a retail store in the near future. In some cases, the system may also factor in the user preferences received in step 210 when determining if a user meets the criteria. For example, if a user has expressed a strong preference for a particular brand or product category, the system may extend the predetermined proximity for stores carrying those items.

[0096] The system may perform this determination continuously or at regular intervals for each user, allowing it to provide timely and relevant notifications or content updates. In some implementations, the frequency of this determination may be adjusted based on the user’s activity level and / or battery life of their device to optimize performance and power consumption.

[0097] When the system determines that a user meets the criteria, it may trigger subsequent actions such as transmitting notifications and / or updating the user interface to display relevant content posts from nearby stores. This process may help create a more dynamic and location-aware shopping experience for users of a platform according to the present teachings.

[0098] As shown in step 216, the method 200 may include transmitting a notification related to one or more stores to the user located within a predetermined proximity. In some aspects, this notification may be sent to at least one of the plurality of users who meets certain criteria, including being located within the predetermined proximity to one or more stores of the plurality of retail stores.Docket No.: RFIX-001-US-PCT1

[0099] The notification may include various types of content related to one or more stores. In some implementations, it may include displaying, on a user interface of a user device associated with the user, a content post related to one or more stores. This content post may include product and product category data, messaging posts, brand data, and / or brand availability information.

[0100] In some cases, the notification may be delivered through different channels, such as in-app notifications, outside app mobile push notification, a text message, an email, and the like. The system may select the most appropriate channel based on one or more user preferences, engagement patterns, and the like. The content of the notification may also or instead be personalized based on the user’s preferences. For example, if the user has expressed interest in a particular product category or brand, the notification may prioritize content related to those interests. In some implementations, the system may use machine learning algorithms to predict which types of notifications are most likely to engage the user.

[0101] The notification may also or instead include rich media elements, such as images or videos of products available at the nearby stores. In some cases, it may include special offers or promotions that are exclusive to users of the platform, encouraging engagement with both the platform and the physical retail locations. In some aspects, the notification may provide interactive elements. For instance, it may include a link that, when clicked, opens the app to display more detailed information about the store or product, or initiates a chat interface for communication between the user and store-based users.

[0102] The system may also implement a frequency cap on notifications to avoid overwhelming users. In some implementations, users may have control over the frequency and types of notifications they receive, allowing for a more personalized experience.

[0103] By leveraging geolocation data, user preferences, and real-time store information, these notifications may create a bridge between digital engagement and physical retail experiences, potentially driving foot traffic to stores and enhancing the overall shopping experience for users.

[0104] As shown in step 218, the method 200 may include displaying, on the user interface of the user device associated with the user, one or more of the plurality of retail stores within a predetermined proximity to the user based on the geolocation data. For example, the user interface may be programmatically configured to display a map, a list view of nearby retail stores, and / or similar. In some implementations, the system may use the geolocation data received in step 212 to determine which stores are within the predetermined proximity. The proximity may be a fixed distance or may be dynamically adjusted based on factors such as user preferences — by way of example, this could be a static value such as ‘show me stores within oneDocket No.: RFIX-001-US-PCT1 mile of my location’ as an app setting, or the user can simply zoom in and out on a geolocation map within the app to see closer or further away stores, to decide what’s available and how far to go on a shopping trip, store density in the area, or the user’s mode of transportation.

[0105] The display may include various details about each retail store, such as the store name, address, operating hours, distance from the user’s current location, a brief description or highlight of current promotions, and the like. In some cases, the system may also or instead display indicators of stores that match the user’s preferences. The user interface may allow for interactive elements, such as the ability to tap on a store to view more details, to get directions, or similar. In some implementations, the interface may display a preview of content posts from each store, allowing users to quickly gauge the relevance of each store’s offerings.

[0106] The system may update this display in real-time as the user moves, ensuring that the information remains accurate and relevant. In some aspects, the user may be able to adjust the display settings, such as expanding or contracting the range of stores shown or filtering the types of stores displayed based on their preferences.

[0107] This feature may enhance the user’s shopping experience by providing a visual representation of nearby shopping opportunities, potentially encouraging exploration of local retail options that the user might not have been aware of otherwise. It may also serve as a bridge between online browsing and physical store visits, helping to drive foot traffic to retail locations.

[0108] As shown in step 220, the method 200 may include receiving — e.g., at a server, remote computing resource, or the like — a selection of at least one retail store within the predetermined proximity. In response to the selection, the method 200 may include displaying, on the user interface of the user device associated with the user, at least one content post from the retail store within the predetermined proximity. In some aspects, the selection of the retail store may be made by the user through one or more various interactions with the user interface. For example, the user may tap on a store icon on a map view, select a store from a list, or use a search function to find a specific store within a predetermined proximity. Upon receiving the selection, the system may retrieve relevant content posts associated with the selected retail store from the database.

[0109] As shown in step 222, the method 200 may include filtering one or more content posts based on one or more user preferences to provide one or more user-curated content posts related to at least one of the plurality of retail stores. In some aspects, this filtering process may be performed by the server and / or remote computing resource using the user preferences received in step 210. The filtering process may thus take into account various user preferences, which may include selection or identification of at least one of: a retail store, a brand, a product, a product type, a product category, demographic information, geographic information, a storeDocket No.: RFIX-001-US-PCT1 type, a favorite store, price information, and information related to a store-based user. In some cases, the user preferences may also include a selection to follow a specific store-based user.

[0110] The system may analyze the content posts received from store-based users and compare them against the user’s preferences. In some implementations, this analysis may involve examining the store data associated with each content post, which may include any as described herein. The content posts themselves may include various types of information, such as product data, messaging posts, brand data, and brand availability. The system may use this information to determine which posts are most relevant to the user’s interests and preferences.[OHl] In some aspects, the filtering process may also or instead consider the type of content in each post. One example might be to act on a user’s preference for product posts versus messaging posts. As a second example, if a user has shown a preference for visual content, the system may prioritize posts that include rich media such as images or videos. As a third example, if a user frequently engages with reposted content from third-party platforms or influencers, the system may give higher priority to such posts. The system may employ machine learning algorithms to continuously refine and improve the filtering process. These algorithms may analyze user behavior, such as which posts a user interacts with, how long they spend viewing certain types of content, and which products they ultimately purchase, to better understand and predict the user’s preferences over time.

[0112] In some implementations, the filtering process may take into account the user’s current context, such as their location, the time of day, and the like. For instance, if a user is near a particular store, the system may prioritize content posts from that store or related to products available at that location.

[0113] The result of this filtering process may include a set of user-curated content posts that are tailored to an individual user’s interests and preferences. These curated posts may be displayed in a feed format on the user interface of the user device, providing a personalized and engaging shopping experience that bridges the gap between online browsing and in-store shopping.

[0114] As shown in step 224, the method 200 may include displaying, on a user interface of a user device associated with the user, one or more user-curated content posts related to the at least one of the plurality of retail stores. In some aspects, this step 224 may involve presenting the filtered content posts in a visually appealing and user-friendly manner, optimized for various device types and screen sizes. The user interface may display one or more user-curated content posts in a feed format, allowing users to scroll through a continuous stream of updates from their preferred stores and / or brands. This feed may include rich media elements such as images, videos, and / or interactive elements to enhance user engagement.Docket No.: RFIX-001-US-PCT1

[0115] The system may continuously optimize the display of user-curated content posts based on user interactions and preferences, e.g., leveraging machine learning algorithms to improve content relevance and user engagement over time. This personalization may enhance the overall shopping experience for users of the platform, creating a more dynamic and tailored interface.

[0116] As shown in step 226, the method 200 may include providing an interactive interface on the user interface of a user device associated with the user. This may include, for example, providing a chat interface for communication between the user and one or more storebased users. The chat interface may allow direct communication between users and store-based users, enabling real-time interactions and personalized customer service. Users may be able to ask questions about products, request additional information, seek assistance with their shopping needs, and so forth. Store-based users may respond providing detailed product information, offering recommendations, addressing any concerns, and so forth. In some implementations, the chat interface may support rich media exchanges, allowing users and store-based users to share images, videos, and / or links related to products and / or services. This feature may enhance the communication experience and provide visual context for discussions about specific items.

[0117] In some cases, the interactive interface may include features for users to provide feedback on their interactions with store-based users and / or rate their shopping experiences. This feedback may be used to improve the quality of service and may factor into a gamification system for store-based users. The interactive interface may also or instead support the display of personalized recommendations based on the user’s usage history. These recommendations may be generated using machine learning algorithms that analyze the user’s preferences and shopping behavior. In some implementations, the interactive interface may include a feature for scheduling in-store appointments, reserving products for in-store pickup, and the like.

[0118] This may also or instead include providing a gamification system for one or more store-based users. By way of example, in such a system, the store-based users may earn points for one or more engagement activities. In some aspects, the gamification system may extend beyond store-based users to include consumers as well, creating a comprehensive engagement strategy that encourages active participation from all users of the platform. The system may incorporate various game-like elements and mechanics to make the shopping experience more enjoyable and rewarding for both consumers and store-based users whose goal is the consumer’s engagement and overall customer satisfaction.

[0119] For consumers, a gamification system may include features such as:Docket No.: RFIX-001-US-PCT1

[0120] 1. Points and Rewards: Users may earn points for various activities on the platform, including viewing content posts, interacting with posts (likes, comments, shares), making purchases, writing reviews, and visiting physical store locations. These points may be redeemable for discounts, exclusive offers, early access to new products, and the like.

[0121] 2 Levels and Badges: As users accumulate points and complete certain actions, they may progress through different levels or earn badges. These achievements may unlock special perks or status symbols within the platform.

[0122] 3. Challenges and Quests: The system may present users with time-limited challenges or quests, such as visiting a certain number of stores in a week or trying products from different categories. Completing these challenges may earn users bonus points or special rewards.

[0123] 4. Leaderboards: Users may be able to compare their progress and achievements with friends or other users in their area through leaderboards, fostering a sense of friendly competition.

[0124] 5. Virtual Collections: The platform may allow users to create and share virtual collections of products they’ve purchased or wish to purchase, encouraging exploration of different stores and brands.

[0125] For store-based users, a gamification system may include:

[0126] 1. Performance Metrics: Store-based users may earn points based on various performance metrics, such as the number of content posts created, engagement rates on their posts, customer satisfaction scores, and / or sales conversions.

[0127] 2. Skill Trees: The system may incorporate skill trees that allow store-based users to unlock new features or capabilities as they gain experience and complete certain tasks on the platform.

[0128] 3. Competitive Challenges: Stores or individual store-based users may participate in competitive challenges, such as creating the most engaging content or achieving the highest customer satisfaction ratings over a given period.

[0129] 4. Recognition and Rewards: Top-performing store-based users may receive recognition through featured profiles, special badges, or real-world rewards such as bonuses or professional development opportunities.

[0130] 5. Collaborative Goals: The system may set collaborative goals for all storebased users within a retail location or brand, encouraging teamwork and collective effort to achieve shared objectives.

[0131] In some implementations, the gamification system may also facilitate interactions between consumers and store-based users. For example:Docket No.: RFIX-001-US-PCT1

[0132] 1. User-Generated Challenges: Consumers may be able to create challenges for store-based users, such as requesting specific types of content or product information.

[0133] 2. Mentorship Programs: Experienced users (both consumers and store-based users) may earn points for mentoring new users and helping them navigate the platform.

[0134] 3 Cross-Promotion: The system may reward both consumers and store-based users for successful referrals or cross-promotions that bring new users to the platform.

[0135] The gamification system may be designed to be flexible and adaptable, allowing for the introduction of new elements and mechanics over time to keep users engaged. In some cases, the system may use machine learning algorithms to personalize the gamification experience for each user, tailoring challenges and rewards to their individual preferences and behaviors.

[0136] By incorporating these gamification elements, the platform may create a more engaging and interactive shopping experience that encourages ongoing participation from both consumers and store-based users. This may lead to increased user retention, higher levels of engagement with content posts, and potentially drive more foot traffic to physical retail locations.

[0137] Fig. 3 is a flow chart of a method for providing a computer-implemented platform for local retail experiences and the like, in accordance with a representative embodiment. The method 300 depicted in Fig. 3 may be implemented in conjunction with method 200 and / or the system 100 of Fig. 1 to enhance the functionality of a computer- implemented platform for local retail experiences. In some aspects, method 300 may provide additional features for store discovery and engagement, complementing the content curation and display capabilities of the method 200 of Fig. 2. As a computer-implemented method, the steps of the method 300 may be performed by one or more processors executing instructions stored in a non-transitory computer-readable medium. This implementation may allow for seamless integration with mobile applications and web interfaces, providing users with a consistent experience across different platforms and devices.

[0138] As shown in step 302, the method 300 may include providing one or more of a unique store identifier and a unique store signal. In some aspects, the unique store identifier may be a quick response (QR) code associated with a specific retail store from the plurality of retail stores. The QR code may encode information such as store identifying information, store type, geographic information, and other relevant store data. In some implementations, the unique store signal may be provided via near-field communication (NFC). The NFC signal may contain similar information to a QR code discussed above, allowing for seamless interaction between the user device and the physical retail location.Docket No.: RFIX-001-US-PCT1

[0139] The system may generate these unique identifiers and signals for each retail store in the database. This process may involve associating store data and / or content posts with a unique identifier or signal. The store data may include any as described herein. In some cases, the unique store identifier or signal may be dynamically updated to reflect current promotions, events, changes in store inventory, and the like. The provision of these unique identifiers and signals may facilitate various features of the platform. For example, it may enable users to quickly access store-specific content, add stores to their preferences, and / or participate in storespecific promotions or events.

[0140] In some implementations, the system may also or instead use these unique identifiers and signals as part of a gamification system. For example, users may earn points or unlock achievements for discovering and interacting with new stores through these identifiers and signals, encouraging exploration of local retail options. After store discovery, the frequency of store visits or ‘check-ins’ documented by scanning the in-store QR code display or using NFC (or the like) can also or instead be rewarded with points or other rewards.

[0141] The unique store identifiers and signals may be integrated with geolocation features of a platform. For example, when a user is within a predetermined proximity to a store, as determined by geolocation data or the like, the system may prompt the user to scan the QR code or interact with the NFC signal to access store-specific content.

[0142] As shown in step 304, the method 300 may include receiving an interaction. By way of example, this may include receiving a scan of a unique store identifier by the user device and / or receiving a unique store signal by the user device.

[0143] For example, the unique store identifier may be a QR code associated with a specific retail store from the plurality of retail stores, and the user device may utilize its camera or other optical scanning capabilities to capture and decode the QR code. The unique store signal may also or instead be provided via NFC, where the user device may be equipped with NFC technology capable of detecting and interpreting NFC signals emitted by transmitters located at or near retail stores. The system may also or instead support other forms of unique store identifiers or signals, such as Bluetooth beacons, radio-frequency identification (RFID) for longer distances vs. NFC, Wi-Fi hotspots with specific SSIDs, and / or audio signals that can be detected by a user device’s microphone. These various technologies may provide flexibility in how stores can interact with users’ devices, accommodating different store environments and user preferences.

[0144] In some implementations, the interaction may be initiated automatically when the user device comes within a predetermined proximity of a retail store (e.g., geofencing for marketing). This may leverage the geolocation features of the platform, where the system hasDocket No.: RFIX-001-US-PCT1 received geolocation data for the user and determined that the user is within the predetermined proximity to one or more stores of the plurality of retail stores. The interaction may also or instead be user-initiated, where the user actively chooses to scan a QR code or tap their device to an NFC tag. This may allow for a more intentional engagement with specific stores of interest to the user. Upon receiving the interaction, the system may process the information encoded in the unique store identifier or signal. This processing may involve decoding the information, verifying its authenticity, and retrieving associated store data from the database in communication with the server.

[0145] In some aspects, the system may log this interaction as part of the user’s activity history. This data may be used to refine the user’s preferences, contribute to the gamification system (e.g., awarding points for store discoveries), and improve the overall personalization of the user’s experience on the platform. The interaction may also trigger subsequent actions within the system, such as displaying store-specific content, updating the user’s proximity to stores, and / or initiating special offers or promotions associated with the interacted store.

[0146] As shown in step 306, the method 300 may include, in response to the interaction, displaying, on the user interface of the user device, at least one content post from a store associated with the unique store identifier or unique store signal. In some aspects, this step 306 may also involve filtering one or more content posts based on the user preferences to provide one or more user-curated content posts related to the store associated with the unique identifier or signal. The content post displayed may include any as described herein.

[0147] In some aspects, in response to the interaction, the method 300 may also or instead include displaying, on the user interface of the user device, something else related to the store associated with the unique store identifier or unique store signal. This may include, for example, a link to download an application for a platform according to the present teachings, a link or similar to follow the store and / or a product related thereto, and the like.

[0148] The system may also use this interaction to update the user’s preferences and store affiliations. For instance, the store associated with the scanned QR code or detected NFC signal may be automatically added to the user’s list of followed stores, allowing for easy access to the store’s content in future use sessions.

[0149] Thus, the present disclosure may provide for a social retail platform designed to enhance local shopping experiences through mobile devices and the like. This platform, which may be embodied as a mobile application and / or a website, may be programmatically configured to facilitate communication between retail stores and consumers, leveraging the power of social media-style content feeds to deliver targeted, location-based advertising and promotion. TheDocket No.: RFIX-001-US-PCT1 platform may receive and store information about a multitude of retail stores, user preferences, and content posts from retail store personnel, thereby creating a personalized, dynamic shopping experience for each user.

[0150] In some aspects, the platform may be designed to avoid the need for feed algorithms by sequestering content by individual stores. This design may allow users to easily focus their intent on stores or brands of interest without being overwhelmed by content. Unlike traditional social media platforms that use complex algorithms to determine what content to show users, the platform may allow users to see all content from their chosen stores and brands, putting the consumer in control of their feed.

[0151] In some aspects, the platform may function as a new type of ad network, offering expanded ad inventory and local targeting capabilities. Unlike traditional advertising methods, which may have limited inventory or poor targeting, the platform may provide a cost- effective solution using the highly effective social media, rich-media content posting method. The platform may offer less constraints on ad inventory, as consumers opt-in to particular stores and brands, allowing for a more focused and effective advertising experience with better targeting and higher consumer receptivity to advertisements and their intrinsic messaging.

[0152] In some aspects, the platform may provide a geolocation-based interface, displaying nearby retail stores based on the user’s current location, and allowing users to save content posts for later viewing. The platform may also or instead provide a store-specific interface activated by scanning a unique store identifier, further enhancing the user’s shopping experience. A platform according to the present teachings may also or instead integrate with other location-based services, and may also provide a software development kit for retailers, enabling the integration of the platform’s functionality into their own mobile applications.

[0153] In some aspects, a server of the social retail platform may be configured to receive and store information about a plurality of retail stores. This information may include, but is not limited to, the store’s name, location, operating hours, and the types of products or services it offers. The server may receive this information from various sources, such as directly from the retail stores themselves, from third-party databases, or from platform administrator user or store user inputs. For example, a retail store may provide its information to the platform through a store registration process, or a user may input information about a retail store they wish to follow on the platform, where such information may be subsequently used to create or enhance a store profile on the platform. Once received, the server may store the retail store information in a database coupled to the server. The database may be structured to efficiently store and retrieve this information, enabling the platform to provide a seamless and responsive user experience. The database may organize the retail store information in various ways, such asDocket No.: RFIX-001-US-PCT1 by geographical location, store type, or brand affiliation, to facilitate efficient retrieval and display of the information to users.

[0154] The server may be configured to receive and store additional information related to the retail stores and the like, such as promotional content, product listings, or user reviews. This information may be used to enrich the content posts displayed to users, providing a more immersive and informative shopping experience.

[0155] In some aspects, the server of a social retail platform may be configured to receive and store user preferences, which may include, but are not limited to, favorite stores and brands. The server may receive these user preferences through the mobile application, where users can select their favorite stores and brands through the user interface. For example, a user may select a particular retail store as a favorite store, indicating a preference for receiving content posts from that store. Similarly, a user may select a particular brand as a favorite brand, indicating a preference for receiving content posts related to that brand. Similarly, a user may select a particular product category as a favorite product category, indicating a preference for receiving content posts related to that product category. The platform may be structured to efficiently store and retrieve these user preferences, enabling the platform to provide a personalized user experience. For instance, the platform may use the stored user preferences to filter the content posts displayed to a user, showing only posts from the user’s favorite stores and brands. This ensures that the content presented to users through the platform is tailored to their individual preferences, enhancing the relevance and personalization of the platform.

[0156] In some aspects, the server of the social retail platform may be configured to receive and store content posts from retail store personnel. These content posts may include, but are not limited to, product information, promotional messages, event announcements, and other types of content that the retail store personnel wish to share with users of the platform. The content posts may be created and submitted by the retail store personnel through a store-specific interface provided by a mobile application and / or a webpage or similar. For example, a store team member may create a content post about a new product arrival, including a product description, pricing information, and product images, and submit the post to the platform through the store-specific interface (e.g., each store may have a personalized interface that is a content creation dashboard that is only for that store). In other aspects, the platform may be configured to receive and store additional types of content posts from retail store personnel, such as user reviews, customer testimonials (e.g., a store user posting these “Our customer Stacy G. loved using these fake botanicals in her dining room when throwing a party for 40 people, etc.”; also or instead, this may be automated with consumer content creation by adding review-site- specific functionality or integrating with a review site or the like), new seasonal assortments,Docket No.: RFIX-001-US-PCT1 extended shopping hours, brand launch events, or other store news updates. This information may be used to enrich the content posts displayed to users, providing a more immersive and informative shopping experience.

[0157] In some aspects, the server of a social retail platform may be configured to provide a user interface for displaying content posts from the user’s favorite stores, brands and product categories. The user interface may be designed to present the content posts in a feed format, similar to the feeds found in popular social media platforms. This feed format may allow users to easily browse through the content posts, providing a dynamic and engaging shopping experience. In some cases, the server may be configured to update the user interface in real-time or near real-time, ensuring that the content posts displayed in the feed are up-to-date. This may involve receiving new content posts from retail store personnel, updating existing content posts, or removing outdated content posts from the feed.

[0158] The platform may also provide various customization options for the feed, allowing users to adjust the appearance and layout of the feed according to their preferences. For example, users may be able to choose the order in which the content posts are displayed in the feed, the size of the content posts, the number of content posts displayed per page, and other display settings.

[0159] In some aspects, the server of a social retail platform may be configured to provide a geolocation-based interface for displaying nearby retail stores. This interface may utilize the geolocation capabilities of a user’s device to determine the user’s current location and display retail stores that are in close proximity to that location. The server may retrieve information about nearby retail stores from a database, based on the user’s current location, and provide this information for display. For example, the platform may display a map showing the user’s current location and the locations of nearby retail stores, and / or it may display a list of nearby retail stores sorted by distance from the user’s current location. In some cases, the server may be configured to update the geolocation-based interface in real-time or near real-time, ensuring that the information about nearby retail stores displayed to the user is up-to-date. This may involve receiving updated location information from the user’s device, retrieving updated information about nearby retail stores from the database, and / or removing information about retail stores that are no longer in close proximity to the user’s current location.

[0160] The interface may be designed to be intuitive and easy to use, allowing users to quickly and easily find nearby retail stores, view information about these stores, and navigate to these stores. The interface may also provide various customization options, allowing users to adjust the display of nearby retail stores according to their preferences. For example, users mayDocket No.: RFIX-001-US-PCT1 be able to choose the location radius within which to display nearby retail stores that the user considers ‘nearby’, the types of retail stores to display, and other display settings.

[0161] In some aspects, the platform may be configured to allow users to save content posts for later viewing. This feature may be particularly useful for users who wish to review certain content posts at a later time, such as when planning a shopping trip or when considering a purchase. In some cases, the platform may provide a separate user interface for viewing saved content posts. This user interface may display the saved content posts in a similar feed format as the main feed, or it may display them in a different format, such as a grid or a list. The user interface for viewing saved content posts may provide additional functionality, such as the ability to remove content posts from the saved list, to organize the saved content posts into categories or folders, or to share the saved content posts with other users. The saved content posts may serve as a personalized shopping guide, helping users to plan their shopping trips, discover new products or promotions, and make informed purchasing decisions.

[0162] In some aspects, the mobile application of the social retail platform may be configured to provide a store-specific interface activated by scanning a unique store identifier. This unique store identifier may be a Quick Response (QR) code, a Near Field Communication (NFC) tag, or any other type of machine-readable identifier associated with a specific retail store. The unique store identifier may be displayed in a physical location within the retail store, such as at the entrance, at the checkout counter, and / or on product labels or displays. When a user scans the unique store identifier using their mobile device or the like, a mobile application may recognize the identifier and activate a store-specific interface. This interface may display content posts from the specific retail store associated with the scanned identifier, providing a personalized shopping experience tailored to that store. The store-specific interface may also or instead provide (e.g., launch) additional features, such as the ability to follow the store, save content posts from the store, and / or interact with store personnel through a chat function.

[0163] In some aspects, a platform according to the present teachings may be configured to receive and store different types of content posts from retail store personnel. These content posts may include product posts and non-product messaging posts. Product posts may contain detailed information about a specific product, such as its features, benefits, pricing, and availability. This information may be provided by the retail store personnel and may be based on the product’s specifications, the store’s inventory data, and / or other relevant sources. The product posts may also or instead include images and / or other multimedia content related to a product, including but not limited to video, augmented reality, and virtual reality experiences, enhancing the visual appeal and informational value of the posts. In some cases, the product posts may include a link to an e-commerce website or a product page where the product can beDocket No.: RFIX-001-US-PCT1 purchased online. This feature may provide a convenient way for users to make a purchase directly from the content post, enhancing the shopping experience and potentially increasing sales for a retail store.

[0164] Non-product messaging posts, on the other hand, may not be specific to a particular product. Instead, these posts may contain general information and / or announcements related to the retail store or its offerings. For example, a non-product messaging post may announce a store-wide sale, a special event, the arrival of a new product line, and the like. These posts may serve to inform and engage users, promoting store visits and customer loyalty.

[0165] In some aspects, the platform may be configured to receive and store brand information associated with products sold by retail stores. This brand information may include, but is not limited to, the brand’s name, logo, product lines, and other relevant details. The platform may receive this brand information from various sources, such as directly from the brands themselves, from the retail stores that carry the brand’s products, and / or from third-party databases. For example, a brand may provide its information to the platform through a brand registration process, and / or a retail store may input information about the brands of the products they carry. In yet other aspects, the platform may be configured to receive and store additional information related to the brands, such as promotional content, product listings, or user reviews. This information may be used to enrich the content posts displayed to users, providing a more immersive and informative shopping experience

[0166] In other aspects, the server may be configured to periodically update stored brand information. This may involve receiving updated information from the brands, verifying the accuracy of the stored information, or removing information about brands that are no longer associated with the retail stores. This ensures that the brand information presented to users through the platform is accurate and up-to-date, enhancing the reliability and usefulness of the platform.

[0167] In some aspects, a platform according to the present teachings may be configured to display brand availability across multiple retail stores, e.g., based on a user’s location. This feature may leverage the geolocation capabilities of the user’s device to determine the user’s current location and display information about the availability of a particular brand in retail stores that are in close proximity to that location. For example, the platform may display a list of nearby retail stores that carry the user’s favorite brand, sorted by distance from the user’s current location. This feature may enhance the user’s shopping experience by allowing them to easily discover and explore retail stores that carry their favorite brands in their local area. This feature may also or instead enhance the user’s shopping experience by allowing them to easilyDocket No.: RFIX-001-US-PCT1 discover and explore product categories of interest in a close proximity — e.g., “where can I find women’s shoes nearby?”

[0168] In some aspects, a platform according to the present teachings may be configured to allow users to follow specific retail store personnel. This feature may enhance a user’s shopping experience by fostering a more personalized and engaging interaction with a retail store. The platform may provide a user interface element, such as a button or a menu option, that allows users to follow a specific retail store personnel when viewing their content posts in a content feed. Upon selecting this user interface element, the platform may store a reference to the followed retail store personnel in a user-specific data structure, such as a list or a database, which is associated with the user’s account on the platform. This can be particularly useful for users who have a preference for the style, expertise, or personality of a specific retail store personnel and wish to regularly view their content posts.

[0169] In some cases, the platform may provide a separate user interface for viewing content posts from the followed retail store personnel. This user interface may display the content posts in a similar feed format as the main feed, or it may display them in a different format, such as a grid or a list. The user interface for viewing content posts from followed retail store personnel may also or instead provide additional functionality, such as the ability to unfollow the retail store personnel, to organize the content posts into categories or folders, or to share the content posts with other users. The platform may also or instead synchronize a list of followed retail store personnel — or other information — across multiple devices associated with the same user account, ensuring that the user can access their information from any of their devices.

[0170] In some aspects, the platform may be configured to provide a chat interface for communication between users and retail store personnel. This chat interface may facilitate realtime or near real-time text-based communication, allowing users to ask questions, request assistance, or provide feedback directly to the retail store personnel. The chat interface may be designed to be intuitive and easy to use, with features such as message threading, read receipts, and typing indicators to enhance the communication experience. In some cases, the chat interface may support the exchange of multimedia content, such as images, videos, or audio clips. For example, a user may send a photo of a product they are interested in to the retail store personnel, or the retail store personnel may send a video demonstrating how to use a product to the user. This feature may enhance the shopping experience by allowing users and retail store personnel to share and discuss rich, contextual information. In yet other aspects, the chat interface may be integrated with other features of the social retail platform. For example, users may be able to initiate a chat conversation directly from a content post, allowing them to discussDocket No.: RFIX-001-US-PCT1 the content post with the retail store personnel in a dedicated chat thread. Similarly, retail store personnel may be able to send content posts to users through the chat interface, providing a personalized shopping recommendation or promotion.

[0171] In some cases, the chat interface may also be configured to support group chat functionality, allowing multiple users and / or retail store personnel to participate in a single chat conversation. This feature may be particularly useful for facilitating discussions about a specific product, promotion, or event among a group of interested users and retail store personnel, or it could be deployed for VIP -level communication to all VIPs for each store.

[0172] In some aspects, the social retail platform may incorporate gamification elements to incentivize and reward store personnel or other users. This gamification system may be implemented in the form of a points-based system, where store personnel can earn points for performing certain actions or achieving certain goals on the platform. For example, store personnel may earn points for creating content posts, attracting followers, receiving likes or comments on their posts, and / or achieving high sales numbers. The points earned by store personnel may be tracked and stored in a database, allowing the platform to provide a real-time view of each store personnel’s points balance.

[0173] In some cases, the points earned by store personnel may be redeemed for various rewards. These rewards may include, but are not limited to, monetary bonuses, store discounts, promotional items, or recognition awards. The specific rewards available may be determined by the retail store or the platform, and may be customized based on the preferences and needs of the store personnel. The rewards system may be designed to motivate store personnel to actively participate in the platform, thereby enhancing the quality and quantity of content posts and improving the overall user experience on the platform.

[0174] In other aspects, the gamification system may include a leaderboard or ranking system, where store personnel are ranked based on their points balance or other performance metrics. This leaderboard may be displayed on the platform, allowing store personnel to compare their performance with their peers and strive for higher rankings. The leaderboard may also be used to recognize and celebrate the achievements of top-performing store personnel, further incentivizing participation in the platform. In yet other aspects, the gamification system may be configured to provide feedback and progress updates to store personnel. For example, the platform may send notifications to store personnel when they earn points, achieve goals, or move up in the leaderboard. The platform may also provide a dashboard or progress report, where store personnel can view their points balance, rewards earned, and performance metrics. This feedback system may help store personnel understand their performance on the platform, identify areas for improvement, and set goals for future performance.Docket No.: RFIX-001-US-PCT1

[0175] By way of example, in some aspects, the gamification system for store personnel may include specific point values for different actions. For example, store personnel may earn 1000 points for each new follower, 500 points for creating new product posts, 100 points each time a consumer clicks through to an ecommerce product page from a post, 200 points for new message-only posts, 25 points for each post like, 200 points for product re-posts with updates, 750 points when a consumer saves their post, and 300 points when a consumer checks in to prove a store visit. Other values are also or instead possible. This detailed point system may be designed to motivate specific behaviors that drive engagement and sales.

[0176] In some aspects, the platform may be configured to facilitate the reposting of content with updates or changes. This feature may be particularly beneficial for retail stores in providing timely and relevant information to consumers. For instance, a store team member may create a product post about a new product arrival, including a product description, pricing information, and product images. Later, the same store team member or a store manager may repost the same content with updates, such as a change in price, availability, and / or additional product details. This reposting feature may be implemented through a user interface provided by the platform, which allows store personnel to select a previously posted content, edit the content as needed, and repost it to the platform.

[0177] In aspects, a platform according to the present teachings may incorporate a feature for scraping e-commerce product pages to automatically populate product posts. This feature may leverage web scraping technologies to extract product information from e- commerce websites, such as product descriptions, prices, images, and other relevant details. The extracted product information may be used to automatically populate the content of product posts, reducing the effort required by store personnel to create product posts and ensuring that the product information presented in the posts is accurate and consistent with the information available on the e-commerce websites.

[0178] In some aspects, the platform may incorporate a manager role, which provides additional capabilities within the platform. The manager role may be assigned to specific retail store personnel, such as store managers or supervisors, who are responsible for overseeing the store’s operations and content posts on the platform. The manager role may be associated with a user account on the platform, which may be created and managed through a mobile application, website or similar. In some cases, the manager role may include the ability to monitor, correct, edit, repost, and / or repurpose any content post from users associated with the same retail store. For instance, a store manager may review the content posts created by store team members, make necessary edits or corrections to the posts, or repost the posts with updates or changes. The store manager may also have the authority to remove any content post that does not meet theDocket No.: RFIX-001-US-PCT1 store’s standards or guidelines. This feature may enhance the quality and consistency of the content posts displayed on the platform, ensuring that the posts accurately represent the store and its offerings.

[0179] In other aspects, the manager role may be associated with a manager account on the platform. The manager account may provide the store manager with access to a dashboard or control panel, where they can manage the store’s operations and content posts on the platform. The manager account may also provide the store manager with access to various tools and features of the platform, such as analytics, reporting, and / or user management tools. These tools may assist the store manager in monitoring the store’s performance on the platform, making informed decisions, and / or managing the store’s team members and their activities on the platform. This dashboard may also function as a control center, e.g., for an enterprise-level version of the platform such that multiple stores in a chain can be managed simultaneously.

[0180] In some aspects, a platform according to the present teachings may avoid the need for feed algorithms by implementing artificial intelligence (Al) to enhance product descriptions and / or sales pitches in content posts. This Al enhancement may be designed to improve the quality and effectiveness of the content posts, making them more engaging and persuasive to users. For instance, the Al may take the original product description provided by retail store personnel and refine it to make it more concise, compelling, and / or sales-oriented. The Al may also or instead reframe a description to make it more of a personal sales pitch from the store personnel, further helping to bring the concept of micro-influencing to life with lesser experienced store personnel.

[0181] In some cases, Al enhancement may also or instead be applied to non-product messaging posts, such as announcements of store-wide sales or events. The Al may ingest an ecommerce site to gain a key brand “voice” and messaging techniques, and help the store team members craft on-brand messaging that is also compelling from a selling perspective. This feature may be particularly beneficial for retail personnel who may not be sophisticated in communicating marketing messages, helping them to create more effective and engaging content posts.

[0182] In other aspects, Al enhancement may be used to assist store personnel in reposting content from major influencers on platforms like Tik Tok or Instagram. The Al may help the store personnel write a secondary endorsement when using smart-links to bring snippets of these posts into the platform. For example, the Al may suggest how to phrase a post like “here's a Tik Tok post of Kylie describing her new eyeliner and here’s why I love it too” in the best possible sales-oriented manner with branded voice and messaging.Docket No.: RFIX-001-US-PCT1

[0183] In yet other aspects, the Al enhancement may be configured to learn and adapt over time, improving its ability to enhance product descriptions and sales pitches based on the performance of previous content posts. The Al may analyze the engagement and sales data associated with each content post, identify patterns and trends, and use this information to refine its enhancement techniques. This feature may ensure that the Al enhancement remains effective and relevant as the retail store’s offerings, branding, and customer preferences evolve over time.

[0184] In some aspects, the platform may be configured to integrate with other location-based services. For instance, the platform may utilize location beacons to facilitate instore check-ins and gamification. Location beacons are small, wireless transmitters that use low- energy Bluetooth technology to send signals to other smart devices nearby. When a user enters a retail store, their mobile device may detect the signal from the location beacon and automatically check-in the user to the store on the platform. The platform may also or instead display the user’s check-in history, points balance, available rewards, and so on, providing a user-friendly interface for users to interact with the gamification features of the platform. This automatic check-in feature may enhance the user’s shopping experience by providing a seamless and convenient way to interact with the platform while shopping in-store.

[0185] In some cases, the platform may leverage the location beacons to implement gamification features. For example, the platform may award points to users for checking-in to a store, with the points being accumulated over time and potentially redeemed for rewards. This gamification feature may incentivize users to visit retail stores more frequently and engage more actively with the platform, thereby enhancing the overall user experience and potentially driving increased foot traffic and sales for the retail stores.

[0186] In some aspects, the platform may be extended to incorporate additional features and capabilities. For instance, the platform may be configured to allow brand advertisers to push branded content through to trusted retail partners. This feature may enable a new mode of brand advertising that channels messaging and promotions from a brand through a retailer to a store, essentially creating a new modality of a more recent business model — digital retail media. This feature may be particularly beneficial for brands that wish to leverage the platform’s reach and engagement to promote their products and services to a wider audience.

[0187] In some cases, the platform may be configured to integrate with blockchain and crypto technologies to create a highly trusted brand advertising platform. This integration may allow for accurate tracking and billing of brand ad impressions and click-throughs on the platform. The nature of trustworthy and accurate distributed blockchain processing may provide a validation of the platform’s brand advertising offering, enhancing the reliability and transparency of the advertising process.Docket No.: RFIX-001-US-PCT1

[0188] In other aspects, the platform may be configured to integrate with Content Management Systems (CMS) for scheduling posts across multiple platforms. This integration may allow for a more efficient and streamlined content creation and distribution process, enabling store personnel to simultaneously post content on the platform and other social media platforms, such as Facebook or Instagram. This feature may enhance content distribution efficiency and augment the reach and visibility of the content posts, potentially driving increased engagement and sales for the retail stores.

[0189] In yet other aspects, the platform may provide a Software Development Kit (SDK) for larger retailers to integrate the platform’s functionality into their own apps. This SDK may provide a packaged solution that allows larger retailers to leverage the platform’s features and capabilities within their own mobile applications. This feature may enhance the user experience for customers of these larger retailers by providing them with the platform’s rich and engaging shopping experiences within the familiar environment of the retailer’s own app.

[0190] In some cases, the platform may implement an Al-powered recommendations engine based on consumer app history across stores and brands. This engine may analyze the aggregated consumer data collected by the platform to provide personalized product recommendations to users. For example, the engine may suggest products that are similar to those that the user has previously viewed or purchased, or products that are popular among other users with similar preferences. This feature may enhance the user’s shopping experience by providing them with personalized and relevant product suggestions, potentially driving increased engagement and sales for the retail stores.

[0191] In other aspects, and as described above, the platform may be applied to nonretail venues such as hotel concierge desks and trade shows. For instance, the platform may be used to promote local attractions at hotel concierge desks, or to showcase products and services at trade shows. This feature may enhance the platform’s versatility and reach, potentially driving increased usage and engagement across a wider range of venues and contexts.

[0192] By way of further example, the platform may be applied to visually oriented home furnishings designer showrooms. For example, the platform may be used in settings such as the Pacific Design Center in Los Angeles, where designers typically only visit a limited number of showrooms. The platform may allow designers to discover and explore other showrooms they’ve never visited before, based on content posted by those showrooms. This application of the platform may help increase foot traffic and engagement in these traditionally struggling showroom environments.

[0193] In other aspects, the platform may be utilized in trade shows and conferences. For instance, exhibitors at a trade show could use the platform to showcase their products andDocket No.: RFIX-001-US-PCT1 services, post updates about demonstrations or presentations, and / or engage with attendees. This could enhance the overall trade show experience by providing a digital layer of interaction and discovery.

[0194] The platform may be adapted for use in hotel concierge services. In this application, the platform could replace traditional paper pamphlets with a digital interface for promoting local attractions, restaurants, and events. Hotel guests could use the platform to discover and plan their local experiences, while businesses could reach potential customers more effectively through targeted, up-to-date digital content.

[0195] Figs. 4-14D show examples of graphical user interfaces of a platform, according to some of the representative embodiments.

[0196] In particular, Fig. 4 shows a consumer-facing interface of a platform, according to a representative embodiment. That is, this figure may represent an organizing presentation layer 400 of the platform, as presented to today’s consumer demanding digital -first solutions for more productive and enjoyable shipping experiences — i.e., a “consumer-facing app presentation layer.” This may be presented as a scrollable feed, which aligns with demand by consumers wanting more digital-first solutions to consume content similar to the extremely popular feed formats seen on the most popular large social media platforms. By way of example, specifically what is shown is a single store feed supported and managed by multiple role-based store users — i.e., the “store-users.” In this example presentation layer 400, two store-users are shown (i.e., User 1 and User 2) for a store (i.e., Local Grocery) but it will be understood that the platform may have no limitation to the number of store-users and each of their roles in posting (e.g., an in-store team member, marketing manager, owner, brand owner or marketing consultant, beauty expert at a department store, restaurant owner or its hired local advertising expert, and the like). Each store may set up its store users based on its particular needs to provide the right team to communicate with their target consumers, to both more deeply engage existing customers and attract new customers. Even the marketing professionals of the store’s brand partners could be given a store-user role to pass branding marketing content posts into the platform, to be presented in the store feed (likely in an “enterprise” version of the present teachings, which can be configured to serve much larger retail chains).

[0197] This consumer-facing presentation layer 400 may be used in many different ways as described herein. For example, any of the following features may be included. A “My Stores” feed may be included, which may be a pulldown type of menu or feed that is scrollable as indicated by the arrows 401, where this type of feed may always be made available to consumers users — i.e., the “consumer-users” — to quickly view multiple favorite stores in rapid succession to see what’s new and interesting, which can both inspire and motivate a shoppingDocket No.: RFIX-001-US-PCT1 trip and / or serve for more detailed planning of such a trip. This example presentation layer 400 shows that the consumer-user is currently looking at the store feed created by the store-user team at “Local Grocery,” where the icon 402 at the top right is present to allow the consumer-user to go to the interface provided to add more stores of interest to them (this interface is shown and described below, with reference to Figs. 14A-14D). The first store-user post by User 1 is presented, with the following sub-components shown by way of example: display of a store user photo and name; store name and address, which may be geo-located in the app to enable powerful local shopping features benefitting the consumer-users; a Follow button 404 available to be selected if the consumer-user would like to look at an aggregated feed of posts from this particular store-user; descriptive text for this post written by the store-user which may be drafted by Al tools and approved for publication by the store-user for far greater store-user post-creation capacity and productivity; and a set number of post photos for displaying, which may be augmented by additional or different photos, video, and content from third-party sites that can be drafted by metadata powered snippets displayed with the consumer option to view them in full in a mobile browser, or a more integrated approach using legally approved APIs to present the third-party content in full.

[0198] Further, as shown by way of example, a second store-user post by User 2 is presented, illustrating the multi-user store feed feature of the platform, and for product-specific posts like the one shown in the second post, where ecommerce data from the store’s website may be used to display certain information. This may include, for example, one or more of: product shopping information such as product name, price, sale price if on sale, product description; and an informational button for these ecommerce-populated product posts which if selected can take the consumer user to the store’s ecommerce product detail page for this particular product. In some aspects, for certain types (e.g., all types) of posts in all display applications, one or more icons 406 (e.g., a heart-shaped or thumbs-up-shaped icon) may be displayed, allowing the consumer-user to see how popular (liked) the item is with previous consumer-user viewers, and / or like it themselves if desired. Similarly, a save-for-later bookmark shaped icon may be displayed, allowing the consumer-user to store this particular post to review later and / or plan for an upcoming shopping trip. The scrollable feed may organize multiple store-user posts, for example, arranging them in reverse-chronological order for the targeted consumer-users, which results in the most recent store-user posts to appear at the top of the feed, alerting consumer-users to what’s new and what’s current. Persistent (e.g., always shown in the app interface) lower navigation features 410 may also be included. The platform may also include icons or buttons that direct users to features such as: My Stores, My Brands, Following, Saved, Account, and Offers.Docket No.: RFIX-001-US-PCT1

[0199] Fig. 5 shows consumer-facing interface components of a platform according to the present teachings, by way of example. Specifically, this figure shows a first interface 501 and a second interface 502. The first interface 501 shows by way of example the “My Stores” pulldown, which is another powerful core consumer-facing app presentation layer feature, allowing for quick review of a consumer-user’s favorite stores, after these stores are selected as favorites in a different interface (e.g., the “My Stores” interfaces). This example figure shows: a snapshot of the consumer-user selecting one of the favorite stores (Store 2) to review that store’s feed; all of the consumer-user’s favorite stores (Store 1, Store 2, and Store 3), conveniently show in this innovative My Stores pulldown interface all the consumer-user’s favorite stores in one place to allow quick selection of any of them for rapid and sequential review of each store’s most recently updated scrollable store feed; the All My Stores selection option 504, which shows a mixed-store feed of all the favorite stores aggregated together in reverse chronological order, allowing consumer-users to quickly scan for new posts across all their favorite stores; and the All Local Stores selection option 506 in the My Stores pulldown showing a mixed-store feed of all the stores participating on the platform, aggregated together in reverse chronological order, and allowing the consumer-user to leverage the platform’s geolocation features to specify a radius distance from their location or an entire ZIP Code to do discovery for all stores (e.g., selected favorites and others too participating on the platform), brands, product discovery, local sales, and so forth, in close geographic proximity. As noted, the consumer-user action being taken in this drawing is the selection of a favorite store (Store 2) in the first interface 501 for viewing, and the results are shown in the second interface 502. The second interface 502 shows the consumer-user the single store’s scrollable feed created by that store’s multiple store-users (using the platform’s innovative consumer-facing app presentation layer format, and showing the features described above in Fig. 4).

[0200] Fig. 6A shows two of three example components of a consumer-facing interface of a platform according to the present teachings, by way of example, and Fig. 6B shows the third of the three example components of a consumer-facing interface of a platform according to the present teachings, by way of example. This shows examples of content designed to be viewed across multiple stores. The first interface 601 shows how the consumerfacing app presentation layer may be used for favorite brands, as set up in using the My Brands feature 604, which may be done in the same or similar manner that has been described in other drawings for the user to set up favorite stores using My Stores features. Shown by way of example is a scrollable favorite brand feed for “Shoe,” which when implemented will allow a user to see the “Shoe” brand’s feeds across the multiple stores carrying this brand, e.g., within a specified distance from the consumer-user when the radius and / or geolocation features (or ZIPDocket No.: RFIX-001-US-PCT1Code) are specified. The second interface 602 shows by way of example a circled / highlighted My Brands pulldown 606, which may operate in the same or similar manner as the My Stores pulldown does, to provide quick review of several favorite brands already selected in a different My Brands interface, switching from one favorite brand to another in rapid succession to see what’s new and interesting. The third interface 603 shows by way of example how the other multi-store feature Follow / F oilowing may be deployed with a circled / highlighted Following pulldown feature 608 which may allow a consumer to follow a favorite person’s posted content and interact further through other features like chat, customer-user support, gamification, etc. Summarizing, the My Stores pulldown and related features shown in Fig. 5 may provide features for rapid review of favorite stores, usually one at a time, while the My Brands and Follow / F oilowing features shown in this drawing may include multi-store features, allowing powerful consumer discovery for exciting brand content across stores within a certain geographic proximity, and allowing more personal relationships and communications to develop between consumers and their favorite store personnel that they have met and enjoyed. These My Brands and Follow / F oilowing features and results may be accessible by the consumer-user anytime by the My Brands and Following options, which may be shown on the lower navigation, for example.

[0201] Fig. 7 shows components of a consumer-facing interface of a platform according to the present teachings, by way of example. Specifically, these components may be related to Offers 700a (e.g., discounted, SALE, clearance items, coupons, etc.) to be implemented in the platform. In the first interface 701 shown by way of example, a consumer planning a shopping trip can view: 1) the consumer-facing app presentation layer deployed to show the Offers 700a interface with 2) an Offers pulldown 700b to allow multiple favorite stores to be reviewed quickly and easily for promotional offers, helping a value-conscious consumer determine which stores have the highest priority to visit. The second interface 702, provided by way of example, using a selected favorite store (Store 1), shows 3) an innovative toggle feature 703 that allows the user to quickly review the regular store feed (e.g., announcement of new arrivals, a weekend sale, introducing a new store team member to the community, new store set up of Spring merchandise, the carrying of a new brand, the launching of a private label credit card, etc.) and then toggle to 4) the circled / highlighted promotional Offers feed 704 (e.g., discounted, SALE, clearance items, etc.). In both feeds accessed by this innovative toggle feature 703, the consumer-facing app presentation layer format described above in Fig. 4 may be used to display the results. This feature may even allow for the simultaneous servicing of two very different customer-users with one platform — the person who always wants to learn about and shop for the newest products, usually at full price versus the discount shopper who onlyDocket No.: RFIX-001-US-PCT1 likes to buy things on sale. Any combination of these two shopping habits is well-served by the platform. Offers may be added to the persistent lower navigation 705 to give consumer access from anywhere in the app.

[0202] Fig. 8 shows a component of a consumer-facing interface of a platform according to the present teachings, by way of example. The example interface 800 may demonstrate how a bookmark-style Saved function icon 801, which may be available on any post to activate that post’s Saved status, can show all Saved posts 802 that can be viewed anytime later by the consumer-user, using the consumer-facing app presentation layer as shown. These Saved features may be allowed for any type of posts (e.g., product posts, store messaging posts, future Offer posts). These Saved posts 802 displayed in this interface may be viewed across all stores (e.g., this may be a multi-store feature presented to the consumer-user in a mixed store feed) for later viewing and can be referenced while planning a shopping trip or during the trip itself. The Saved features displayed can be accessed anytime by the consumeruser by selecting the Saved feature icon 801 on the persistent lower navigation, in some aspects.

[0203] Fig. 9A introduces store-user features of a platform according to the present teachings, by way of example, and Fig. 9B shows a consumer-facing interface store feed of a platform according to the present teachings, by way of example. Specifically, Fig. 9A shows an example of a web-based store-user solution 900 (which may be called a Store Content Studio or similar, with an example shown with Store l’s store user, User 1), by way of example. The platform may allow each store to have its own Content Creation Studio, and user credentials may be established for both store team members (store-users) and store managers (elevated store-users with additional capabilities in this role) to access this store-user solution for their store only. This innovative store-user platform may address the specific needs and requirements to allow teams of store-based users at each store to deliver fun, efficient, immersive, interesting, and useful shopping-focused store feeds to interested consumers, with unique and innovative features shown in this drawing and drawings that follow. The number of Content Creation Studio store-users and those with manager credentials can be as few or as many as any particular store wishes. Shown by way of example is user, User 1, assigned in an elevated store manager role, as she can see and act on second user, User 2’s post, which can be seen in the store-user manager’s list of content 903, and also can be partially seen in the consumer-facing app presentation layer 902 shown by way of example in Fig. 9B. Store managers may create their own posts, but can also act on store-user posts from all store team members as if they are their own by deleting, editing by re-post, or re-post with no changes just to bring an old post to the top of the feed, etc. Additional store manager features may also or instead be included in the Content Creation Studio for store-users. A few more specific features of an example store-userDocket No.: RFIX-001-US-PCT1 solution are shown here: previously published posts (i.e., in the store-user list of content 903) are presented for potential action by this store-user in reverse chronological format; the DELETE button allows any post to be deleted, by the original store team poster or another user with a manager role for this particular store, as User 1 has; and the RE-POST button allows any post to be re-posted, either to bring it to the top of the store feed in the consumer-facing app presentation layer 902, or to make edits with new information that customers would benefit from knowing, like editing the description to update consumer-users on inventory availability or new Fall colors of the product now available. Any results of these changes made in the store-user interface of Fig. 9A may be shown in the consumer-facing interface updated feed of Fig. 9B. Fig. 9A shows that Published Posts 904 is selected in the top navigation, and this top navigation is described more fully in the next drawing. Another approach to delivering store-user and store manager functions may be to add store-user features to the app interface when activated by store user credentials. Yet another approach may be to create a separate app (e.g. a Store App or Store-Version App of the present teachings), similar to the Lyft Driver App, that can only be used by users with store-user credentials.

[0204] Figs. 10A and 10B show additional store-user features of a platform according to the present teachings, by way of example. That is, these figures show additional features that may be available to all store-users in the Content Creation Studio, including store managers in the manner described for the previous drawing. For example, these figures show a top navigation 1001 that allows each store-user to: select NEW POST to create a new post from scratch; or select PENDING POSTS to look at their posts already created, which are in a saved draft form to be further edited or could also be saved in completed form to be published at an opportune moment for supporting the store’s communication efforts targeting consumer-users; or select PUBLISHED POSTS to see all their posts already displayed in the consumer-facing app presentation layer, and possibly delete them, or possibly select the RE-POST function described in the previous drawing to add or change post titles, post text descriptions, or post images as ongoing store operations affect the post content and the need to update the store’s consumer-users (e.g., announce an item on sale, end extended store holiday hours, allow a store manager to fix or improve a post generated by one of the store team members, etc.). Fig. 10A shows the opened NEW POST screen 1000, where new post content can be created from scratch, and where the user has selected by way of example the simple message post option, which displays entry fields 1002 that allow the user to enter a message about anything related to the store (e.g., extended hours, new employee hired, new Spring merchandising and store windows set up, a private store-branded credit card or other types of financing now being offered, etc.), and also the selection of up to a set number of images for this new post (this mayDocket No.: RFIX-001-US-PCT1 also or instead include videos, third-party content, and the like). Fig. 10B shows an interface 1004 where the user has selected a more complex product post option (e.g., a “Product Post” as opposed to the “Message Post” shown by way of example in Fig. 10A), which displays entry fields 1002 that allow the user to enter the store’s ecommerce link to the product’s: ecommerce product detail page, used for several platform features and described in later drawings; the product’s title; the brand of the product (with the store’s brand name as an option for private label merchandise); the price of the product, and if on sale, the sale price of the product (thus, this field is optional); a store-user description of or messaging about the product in an editorial or promotional manner; and the selection of up to a set number of images for this new post (and / or other content as described in Fig. 10A, for example). In both drawings, one or more action buttons 1010 are shown: by way of example, CLEAR allows the user to remove all data from the post and start over, PENDING allows the user to save a partially created post for more editing later or save a fully created post to be published to the consumer-facing app presentation layer later, and PUBLISH allows the user to immediately release the post for publication to the consumer-facing app presentation layer. Any type of post can be created by any store-based user, and these action buttons 1010 may for example provide more elaborate review and queuing to allow store team members more powerful flexibility and to allow management to have more planning, review, and scheduling. As described in previous figures, these store-user features may be delivered with different web and mobile app approaches.

[0205] Figs. 11 A and 1 IB show an example of an in-app design version of the Content Creation Studio with added store-user features illustrating how to help store users generate content much quicker and far more easily, and with greater accuracy. For example, using the product link 1110 from a store’s ecommerce site as a source of data, ecommerce website content scraping is shown here that uses API-style linkage software to pull data from the ecommerce page and pre-populate text fields and images. In the first interface 1101, the user may insert the ecommerce product link 1110 to call the API software to pre-populate the post, and may use more generalized Al tools where possible that may not require the precise integration needed by API software, and that work for most store websites without specific coding interfaces needed for each. In the second interface 1102, the results may be shown of this pre-population process, and the user then has the option to edit these fields before publishing. Also shown in each of these figures are store team posting features 1120, for example: if manager review is required for each post by a store team member, the REVIEW button may be selected to send a post to a manager for a review / approval process before publishing, and what the manager sees may be what is shown in the third interface 1103 of Fig. 1 IB. The QUEUE button may allow the storeuser to set an ideal publication time, which will publish the post automatically at that futureDocket No.: RFIX-001-US-PCT1 desired moment, and the POST button allows the store-user to publish the post immediately if no manager review is required and no queuing is needed. Based on specific store set-up requirements, some of these future posting features will be active or greyed out as inactive based upon each store’s configuration of posting rules and management supervision techniques. As described above, these store-user features may be delivered with different web and mobile app approaches (a design for an in-app store-user solution for these features is shown).

[0206] Figs. 12A and 12B show further details about store-user content creation using a platform according to the present teachings, by way of example. That is, these figures show more detail about a Content Creation Studio store-user feature for re-posting content, by way of example. Specifically, these figures may demonstrate how the RE-POST button (RE-POST button interface and method of activation is shown in Fig. 9A, where this figure shows an example of the next store-user step which displays the interface where content fields can be updated) can allow store-users to take an existing post and re-post with edits showing typical retail updates. In this example, the store-user is making changes to the post content fields to announce that a popular item went on sale, including updated SALE pricing information 1202, possibly an updated description 1204, and possibly updating additional content 1206 such as images or multimedia. Fig. 12B then shows how the updated post is added to the reverse- chronological consumer-facing single-store feed, alerting consumers to new information such as the description 1204 and the SALE pricing information 1202. Stated otherwise, the circled SALE price entry added during this use of the RE-POST feature in Fig. 12A may be present in Fig. 12B showing the consumer-facing app presentation layer 1201 with the updated SALE price. Similarly, the description 1204 entered in the post description box by the store-user in Fig. 12A shows up after this post is published in Fig, 12B in the consumer-facing app interface, by way of example. As described above in Figs. 9A and 9B, these store-user features may be delivered with different web and mobile app approaches (a web-based store user solution is shown).

[0207] Figs. 13 A and 13B show one example of the many powerful consumer-user experiences enabled by the store-user features of the Content Creation Studio described herein. Specifically, a component of the consumer-facing interface of a platform according to the present teachings, by way of example, includes: 1) by selecting the circled information icon 1302 on a product post in the consumer-facing app presentation layer, the consumer-user activates the opening of the device’s mobile browser to automatically view 2) the store’s ecommerce page 1304 for the product. Once there, the user can look at more specific product details like colors and sizes available, consumer ratings of the product, inventory availability, a much more detailed product description, more photos and video if available, etc. This can helpDocket No.: RFIX-001-US-PCT1 the customer-users to decide whether or not they would like to save this product post in the platform using the Save functions described herein, so that it can be referred to for an upcoming shopping trip. Or, the consumer-user could make an immediate ecommerce online purchase, as an alternative to purchasing the item at the store during a future shopping trip. Either way, the store’s goals of increased consumer satisfaction and increased sales are met.

[0208] Figs. 14A-14D show use of geolocation in a consumer-facing interface on a platform according to the present teachings, by way of example. That is, these figures illustrate how the use of geolocation and related technologies may be used in an integrated manner in the platform to increase visibility of stores using the platform to attract new customers and deepen relationships with existing customers, thereby increasing store sales and store foot traffic. For example, in Figs. 14A and 14B, Store 1 and Store 2, respectively, which represent two participating stores, are tagged with active selectable pins 1401a, 1401b within the geo-location interface of the app, and the figures show how easy it is for a consumer-user to add one or both stores as a favorite store.

[0209] Fig. 14C shows an example of a scannable code 1402 (e.g., QR code) that may be displayed at Store 1, such as at the checkout counter or at other prominent locations in the store, which shows how easy it is for each store to encourage consumers to engage with the platform, especially given that store personnel are right there to explain the service. The platform may show that store’s feed to the new consumer-user immediately upon app download, without the need to even create a consumer-user account. In Fig. 14D, with Store 1 (“Grocery”) again used as an example, the circled NFC store display placard 1404 is shown as an alternative to a displayed QR Code. This and other connectivity tools may be used extensively to help create this shopping experience serving local stores and consumers who want digital-first engagement tools that make shopping trips more aspirational, easy, efficient, rewarding, and fun.

[0210] The above systems, devices, methods, processes, and the like may be realized in hardware, software, or any combination of these suitable for a particular application. The hardware may include a general -purpose computer and / or dedicated computing device. This includes realization in one or more microprocessors, microcontrollers, embedded microcontrollers, programmable digital signal processors or other programmable devices or processing circuitry, along with internal and / or external memory. This may also, or instead, include one or more application specific integrated circuits, programmable gate arrays, programmable array logic components, or any other device or devices that may be configured to process electronic signals. It will further be appreciated that a realization of the processes or devices described above may include computer-executable code created using a structured programming language such as C, an object oriented programming language such as C++, orDocket No.: RFIX-001-US-PCT1 any other high-level or low-level programming language (including assembly languages, hardware description languages, and database programming languages and technologies) that may be stored, compiled or interpreted to run on one of the above devices, as well as heterogeneous combinations of processors, processor architectures, or combinations of different hardware and software. In another aspect, the methods may be embodied in systems that perform the steps thereof, and may be distributed across devices in a number of ways. At the same time, processing may be distributed across devices such as the various systems described above, or all of the functionalities may be integrated into a dedicated, standalone device or other hardware. In another aspect, means for performing the steps associated with the processes described above may include any of the hardware and / or software described above. All such permutations and combinations are intended to fall within the scope of the present disclosure.

[0211] Embodiments disclosed herein may include computer program products comprising computer-executable code or computer-usable code that, when executing on one or more computing devices, performs any and / or all of the steps thereof. The code may be stored in a non-transitory fashion in a computer memory, which may be a memory from which the program executes (such as random-access memory associated with a processor), or a storage device such as a disk drive, flash memory or any other optical, electromagnetic, magnetic, infrared, or other device or combination of devices. In another aspect, any of the systems and methods described above may be embodied in any suitable transmission or propagation medium carrying computer-executable code and / or any inputs or outputs from same.

[0212] The foregoing description, for purpose of explanation, has been described with reference to specific embodiments. However, the illustrative discussions above are not intended to be exhaustive or to limit the disclosure to the precise forms disclosed. Many modifications and variations are possible in view of the above teachings.

[0213] Unless the context clearly requires otherwise, throughout the description, the words “comprise,” “comprising,” “include,” “including,” and the like are to be construed in an inclusive sense as opposed to an exclusive or exhaustive sense; that is to say, in a sense of “including, but not limited to.” Additionally, the words “herein,” “hereunder,” “above,” “below,” and words of similar import refer to this application as a whole and not to any particular portions of this application.

[0214] It will be appreciated that the devices, systems, and methods described above are set forth by way of example and not of limitation. For example, regarding the methods provided above, absent an explicit indication to the contrary, the disclosed steps may be modified, supplemented, omitted, and / or re-ordered without departing from the scope of this disclosure. Numerous variations, additions, omissions, and other modifications will be apparentDocket No.: RFIX-001-US-PCT1 to one of ordinary skill in the art. In addition, the order or presentation of method steps in the description and drawings above is not intended to require this order of performing the recited steps unless a particular order is expressly required or otherwise clear from the context.

[0215] The method steps of the implementations described herein are intended to include any suitable method of causing such method steps to be performed, consistent with the patentability of the following claims, unless a different meaning is expressly provided or otherwise clear from the context. So, for example performing the step of X includes any suitable method for causing another party such as a remote user, a remote processing resource (e.g., a server or cloud computer) or a machine to perform the step of X. Similarly, performing steps X, Y, and Z may include any method of directing or controlling any combination of such other individuals or resources to perform steps X, Y, and Z to obtain the benefit of such steps. Thus, method steps of the implementations described herein are intended to include any suitable method of causing one or more other parties or entities to perform the steps, consistent with the patentability of the following claims, unless a different meaning is expressly provided or otherwise clear from the context. Such parties or entities need not be under the direction or control of any other party or entity, and need not be located within a particular jurisdiction.

[0216] While particular embodiments have been shown and described, it will be apparent to those skilled in the art that various changes and modifications in form and details may be made therein without departing from the spirit and scope of this disclosure and are intended to form a part of the invention as defined by the following claims, which are to be interpreted in the broadest sense allowable by law.

Claims

Docket No.: RFIX-001-US-PCT1CLAIMSWhat is claimed is:

1. A computer program product comprising computer executable code embodied in a non- transitory computer readable medium that, when executing on one or more computing devices, performs the steps of: receiving, at a server, store data from a plurality of retail stores; storing the store data at a database in communication with the server; receiving, at the server, one or more content posts from one or more store-based users, the one or more content posts related to the store data from at least one of the plurality of retail stores; providing, on one or more user devices, a user interface programmatically configured to display the one or more content posts; receiving, at the server, one or more user preferences from a user, the one or more user preferences related to one or more of: (i) store data and (ii) product data; filtering the one or more content posts based on the one or more user preferences to provide one or more user-curated content posts related to at least one of the plurality of retail stores; and displaying, on a user interface of a user device associated with the user, the one or more user-curated content posts related to the at least one of the plurality of retail stores.

2. The computer program product of claim 1, wherein the one or more user-curated content posts are received from at least two store-based users associated with a single retail store.

3. The computer program product of claim 2, further comprising code that, when executing on one or more computing devices, performs the step of displaying, on a single feed on the user interface of the user device, content posts received from the at least two store-based users associated with the single retail store.

4. The computer program product of claim 1, further comprising code that, when executing on one or more computing devices, performs the steps of: receiving, at the server, geolocation data for the user; and displaying, on the user interface of the user device associated with the user, one or more of the plurality of retail stores within a predetermined proximity to the user based on the geolocation data.Docket No.: RFIX-001-US-PCT15. The computer program product of claim 4, further comprising code that, when executing on one or more computing devices, performs the steps of: receiving, at the server, a selection of at least one retail store within the predetermined proximity; and displaying, on the user interface of the user device associated with the user, at least one content post from the at least one retail store.

6. The computer program product of claim 1, further comprising code that, when executing on one or more computing devices, performs the steps of: receiving, at the server, geolocation data for a plurality of users; determining that at least one of the plurality of users meets certain criteria including being located within a predetermined proximity to one or more stores of the plurality of retail stores; and transmitting a notification related to the one or more stores to the at least one of the plurality of users.

7. The computer program product of claim 6, wherein the certain criteria further includes the one or more stores corresponding to at least one of the one or more user preferences.

8. The computer program product of claim 6, wherein the notification includes displaying, on a user interface of a user device associated with the at least one of the plurality of users, a content post related to the one or more stores.

9. The computer program product of claim 6, wherein the notification includes at least one of: a push notification, a text message, and an email.

10. The computer program product of claim 1, wherein the one or more user preferences include selection or identification of at least one of: a retail store, a brand, a product, a product type, a product category, demographic information, geographic information, a store type, a favorite store, price information, and information related to a store-based user.

11. The computer program product of claim 1 , wherein the one or more user preferences include a selection to follow a store-based user.Docket No.: RFIX-001-US-PCT112. The computer program product of claim 1, wherein the store data includes at least one of: store identifying information, a store type, geographic information, product information, and information related to a store-based user.

13. The computer program product of claim 1, wherein the one or more content posts include at least one of: product data, a messaging post, brand data, and brand availability.

14. The computer program product of claim 13, wherein the product data includes at least one of product availability, product information, pricing information, and a link to purchase a product.

15. The computer program product of claim 1, wherein the one or more content posts include reposted content.

16. The computer program product of claim 15, wherein the reposted content includes content from a third-party platform.

17. The computer program product of claim 16, wherein the third-party platform is a social media platform.

18. The computer program product of claim 15, wherein the reposted content includes influencer content.

19. The computer program product of claim 15, wherein the reposted content includes at least one of a previous content post and a revised version of the previous content post.

20. The computer program product of claim 1, wherein the one or more user-curated content posts are displayed in a feed format.

21. The computer program product of claim 1, wherein the one or more user-curated content posts include rich media.

22. The computer program product of claim 1, further comprising code that, when executing on one or more computing devices, performs the steps of: providing a unique store identifier;Docket No.: RFIX-001-US-PCT1 receiving a scan of the unique store identifier by the user device; and in response to receiving the scan, displaying, on the user interface of the user device, at least one content post from a store associated with the unique store identifier.

23. The computer program product of claim 1, further comprising code that, when executing on one or more computing devices, performs the steps of: providing a unique store signal; receiving the unique store signal by the user device; and in response to receiving the unique store signal, displaying, on the user interface of the user device, at least one content post from a store associated with the unique store signal.

24. The computer program product of claim 23, wherein the unique store signal is provided via near-field communication.

25. The computer program product of claim 1, further comprising code that, when executing on one or more computing devices, performs the step of providing a chat interface for communication between the user and one or more store-based users.

26. The computer program product of claim 1, further comprising code that, when executing on one or more computing devices, performs the step of providing a gamification system for one or more store-based users, wherein the one or more store-based users earn points for one or more engagement activities.

27. The computer program product of claim 26, wherein the one or more engagement activities includes creation of a content post.

28. A method, comprising: receiving, at a server, store data from a plurality of retail stores; storing the store data at a database in communication with the server; receiving, at the server, one or more content posts from one or more store-based users, the one or more content posts related to the store data from at least one of the plurality of retail stores; providing, on one or more user devices, a user interface programmatically configured to display the one or more content posts;Docket No.: RFIX-001-US-PCT1 receiving, at the server, one or more user preferences from a user, the one or more user preferences related to one or more of: (i) store data and (ii) product data; filtering the one or more content posts based on the one or more user preferences to provide one or more user-curated content posts related to at least one of the plurality of retail stores; and displaying, on a user interface of a user device associated with the user, the one or more user-curated content posts related to the at least one of the plurality of retail stores.

29. A system, comprising: a data network; a plurality of processors coupled to the data network; and a remote computing resource coupled to the data network, the remote computing resource including a processor and a memory, the memory storing code executable by the processor to perform the steps of: receiving store data from a plurality of retail stores; storing the store data at a database in communication with the remote computing resource; receiving one or more content posts from one or more store-based users, the one or more content posts related to the store data from at least one of the plurality of retail stores; providing, on one or more user devices, a user interface programmatically configured to display the one or more content posts; receiving one or more user preferences from a user, the one or more user preferences related to one or more of: (i) store data and (ii) product data; filtering the one or more content posts based on the one or more user preferences to provide one or more user-curated content posts related to at least one of the plurality of retail stores; and displaying, on a user interface of a user device associated with the user, the one or more user-curated content posts related to the at least one of the plurality of retail stores.

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