WO2021148590A1

WO2021148590A1 - Social media influencer platform

Info

Publication number: WO2021148590A1
Application number: PCT/EP2021/051429
Authority: WO
Inventors: Kurt Seidensticker; Laura SEIDENSTICKER; Alex POJMAN
Original assignee: Société des Produits Nestlé S.A.
Priority date: 2020-01-22
Filing date: 2021-01-22
Publication date: 2021-07-29
Also published as: JP2023511518A; AU2021209389A1; BR112022012092A2; CA3166022A1; CN114846501A

Abstract

Methods and systems for monitoring nutritional needs and using social networks to influence nutrient intake are presented. In one embodiment, a method is provided that includes receiving, from a user device associated with a user, an image data showing an identifier associated with a recognizable product; analyzing user activity associated followers of the user on a social network to determine, for each follower, an indicia of influence caused by the first user to each follower with respect to the first recognizable product; generating, based on the respective indicia of influence associated with each follower, an influencer score for the first user; and sending, to the mobile device and based on user attributes associated with the health goals of the user, a discount code for one or more first user-specific products to help the user achieve the health goals.

Description

TITLE

SOCIAL MEDIA INFLUENCER PLATFORM

RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No. 62,964,344 filed January 22, 2020, the entire disclosure of which is hereby incorporated herein by reference in its entirety.

TECHNICAL FIELD

[0001] Certain aspects of the present disclosure generally relate to a social media influencer platform as well as methods of managing, verifying, educating, and rewarding social media influencers.

BACKGROUND

[0002] A significant portion of public are in need of specific types of nutrients and dietary supplements in order to lead healthy lives, achieve desired cosmetic improvements, or complement food and beverage options in a diet friendly way. There are many psychological barriers that prevent consumers from purchasing dietary supplements, including inaccurate but prevalent associations of dietary supplements as not being tasty to a lack of knowledge about the possible uses and applications (e.g., recipes) for the dietary supplements. Furthermore, while consumers may desire specific physiological, medical, and/or cosmetic improvements to themselves, they may be unaware of the types of nutritional and dietary supplements available and how to complement them into their daily lives.

[0003] Various embodiments of the present disclosure address one or more of the shortcomings presented above. SUMMARY

[0004] The present disclosure presents new and innovative methods and systems for monitoring nutritional needs and using social networks to influence nutrient intake. In one embodiment, a method is provided that includes a computing device (e.g., an application server) receiving, from a mobile device associated with a first user, a message comprising image data and a first user ID linking the first user to a social network. The computing device may determine that the image data shows an identifier (e.g., logo, product name, company name, etc.) associated with a first recognizable product. The computing device may determine, based on the first user ID, a plurality of follower user IDs corresponding to a plurality of followers associated with the first user ID on the social network. User activity associated with each follower user ID may be analyzed, e.g., to determine, for each follower user ID, an indicia of influence caused by the first user to each follower with respect to the first recognizable product. The computing device may generate a discount level for the first user ID, and may then send, to the mobile device, a discount code for one or more first user-specific products.

[0005] The features and advantages described herein are not all-inclusive and, in particular, many additional features and advantages will be apparent to one of ordinary skill in the art in view of the figures and description. Moreover, it should be noted that the language used in the specification has been principally selected for readability and instructional purposes, and not to limit the scope of the inventive subject matter.

BRIEF DESCRIPTION OF THE FIGURES

[0006] FIG. 1 illustrates a system for monitoring nutritional needs and using social networks to influence nutrient intake, according to an embodiment of the present disclosure.

[0007] FIG. 2 illustrates an example user profile database according to exemplary embodiments of the present disclosure [0008] FIG. 3 illustrates an example dietary supplement product recommendation engine according to an exemplary embodiment of the present disclosure.

[0009] FIG. 4 illustrates a flow diagram of an example method of monitoring nutritional needs and using social networks to influence nutrient intake, according to an exemplary embodiment of the present disclosure.

[0010] FIG. 5 illustrates a screenshot of an example user interface for monitoring nutritional needs and using social networks to influence nutrient intake, according to an embodiment of the present disclosure.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

[0011] A significant portion of public are in need of specific types of nutrients and dietary supplements in order to lead healthy lives, achieve desired cosmetic improvements, or complement food and beverage options in a diet friendly way. However, there are many psychological barriers that prevent consumers from purchasing dietary supplements, and there can be a lack of awareness on what types of dietary supplements are most appropriate for a consumer based on the consumer’s physiological data, medical history, and health goals. Social media may be a powerful took to overcome social barriers towards adoption of dietary supplements, and to spread awareness of health benefits and improvements. Furthermore wearable biosensors can be a useful tool to accurately and precisely monitor a consumer’s health condition to recommend the best dietary supplement product.

[0012] The present disclosure relates generally to a social media influencer platform for monitoring nutritional needs and using social networks to influence nutrient intake. Additionally, the disclosure includes methods of verifying the authenticity of the social media account, including but not limited to a method whereby the social media influencer incorporates special coding into their social media accounts. Additionally, the disclosure provides a social media influencer platform that collects data from the social media influencers, allows for consistency of message, provides data analytics, and is capable of reviewing the performances of influencers. The social media influencer platform further can be used to manage a company's social media influencer program as well as a platform for the efficient exchange of important product information to or from the social media influencers. The disclosure also provides a method for educating social media influencers about the products; a repository of approved images, slogans, and advertising for use by the social media influencers; the ability of the social media influencer to provide feedback to the company; and a system for rewarding and compensating social media influencers for their support of a specific product associated with a nutrient or dietary supplement.

[0013] FIG. 1 illustrates a system 100 according to an embodiment of the present disclosure. The system 100 includes a user device 102 associated with a user (e.g., a “first user”), a plurality of user devices associated with other users (“followers”) that are connected to the first user on a social network (e.g., follower devices 102A-C associated with followers), and an analytics server 120. Each of these devices may be able to communicate with one another over a communication network 150, which may be any wired or wireless network for disseminating information. Examples of the wireless networks may comprise Wi-Fi, a global system for mobile communications (GSM) network, and a general packet radio service (GPRS) network, an enhanced data GSM environment (EDGE) network, 802.5 communication networks, code division multiple access (CDMA) networks, Bluetooth networks or long term evolution (LTE) network, LTE- advanced (LTE-A) network or 5th generation (5G) network. Moreover, each device may include a respective network interface (e.g., network interface 118, 136, 118A, and 146) to facilitate communication through the communication network 150. For example, the respective network interface may comprise a wired interface (e.g., electrical, RF (via coax), optical (via fiber)), a wireless interface, a, modem, etc. Furthermore, each of these devices may include one or more respective processor(s) (e.g., processor 104, 104A, 122, 142) and memory (e.g., memory 110, 110A, 128, 144) The processor may comprise any one or more types of digital circuit configured to perform operations on a data stream, including functions described in the present disclosure. The memory may comprise any type of long term, short term, volatile, nonvolatile, or other memory and is not to be limited to any particular type of memory or number of memories, or type of media upon which memory is stored. The memory may store instructions that, when executed by the processor, can cause the respective device to perform one or more methods discussed herein.

[0014] The user device 102 may be implemented as a computing device, such as a computer, smartphone, tablet, smartwatch, or other wearable through which an associated user can communicate with the analytics server 120 and the follower devices 102A-C. The user device 102 may also be implemented as a camera, voice recorder, or other multimedia content generator to allow the first user to post multimedia content on the social network. For at least these reasons, the user device 102 may include, for example, camera 108 and voice recorder 109. The user device 102 may further include a user interface (Ul) 112, which may comprise a touch-sensitive display, a touchscreen, a keypad with a display device, or a combination thereof, and may work in relation to a display 106. The Ul 112 may allow the first user to view content generated from the camera, access and use one or more applications 114, and enter input signals, e.g., by touching and moving icons on the display 106. The display 106 may comprise any medium of outputting visual information (e.g., image, video, etc.). The applications 114 may comprise any program or software to perform the methods described herein. For example, the applications 16 may include an application hosted by the analytics server 120 for monitoring nutritional needs and using social networks to influence nutrient intake. The first user may have a user profile 116 associated with the application, and the user profile 116 may comprise a plurality of user attributes that may be utilized by the analytics server 120. The user attributes may include biographical details about the first user (e.g., a user identification, gender, weight, height, etc.), information about the health of the first user (e.g., activity level, comorbidities, health goals, etc.), and dietary needs and preferences. In some embodiments, the user attributes may further include physiological data of the first user. The physiological data may be obtained via one or more biosensors and/or a wearable device that includes the one or more biosensors (e.g., “biosensors/wearables” 119). In some aspects, the biosensors/wearables 119 may be a part of, or may be communicatively linked to, the user device 102. The biosensors/wearables may include, but are not limited to, a glucose monitor, a sphygmomanometer, a heart rate measurement device, and/or devices that measure activity levels (e.g., FITBIT®). The applications 14 may further include one or more social media applications hosted by the social media server 140, and the one or more social media applications may allow the first user to network with the one or more followers.

[0015] The one or more follower devices 102A-102C may comprise computing devices associated with the respective followers of the first user on a social network shared with the first user. Thus, the follower devices 102A-102C may comprise substantively similar components and perform substantively similar functions as described for the user device 102. For example, follower device 102A may include processor 104A, display 106A, camera 108A, audio recorder 109A, memory 110A, US 112A, applications 114A, a user profile associated with the follower (e.g., “follower profile” 116A), and network interface 118A.

[0016] The analytics server 120 may comprise a local or a remote computing system for requesting and receiving information received from the user device 102, follower devices 102A-102C, and social media server 140 (e.g., regarding user attributes, user activity, multimedia content posted on the social network, etc.), image processing, object recognition (e.g., for identifiers of recognizable products in the multimedia content), processing information associated with a user or a follower, generating a list of recommended products and uses of the products, and sending recommendations and discount codes to the user device 102.

[0017] The one or more processors 122 of the analytics server 120 may include an image processor 124 and a natural language processor 126. The image processor 124 may digitally process image data produced by the user device 102 or follower devices 102A-C to avoid noise and other artifacts, and prepare such image data for the recognition of texts and physical objects (e.g., identifiers of recognizable products, visible features of the recognizable products, objects within the image data suggesting a type of engagement with the recognizable products, etc.). The natural language processor 126 may be used to recognize texts, and determine meaning from texts captured from the image data. The texts may include the identifiers of recognizable products (e.g., product name, company name, etc.). The image processor and/or natural language processor may rely on stored machine learning models from the machine learning module 124 to recognize appropriate objects from the image data. In one aspect, the machine learning module 124 may utilize reference image data to perform supervised learning to be able to accurately identify relevant objects (e.g., identifiers of recognizable products). Reference training data may be provided to the machine learning module 124 through multimedia content used and generated by the first user and the followers.

[0018] The memory 128 of the analytics server 120 may further include a user database 130, a products database 132, and an application program interface 134. The user database 130 may store the respective user profiles associated with the users of the social network (e.g., user associated with user device 102 and the one or more followers corresponding to follower devices 102A-102C). FIG. 2 shows an example embodiment of the user database 130 in further detail, as will be described further below. The products database 132 may store information about a plurality of recognizable products. The recognizable products can provide nutritional or dietary supplements; and can be the subject of various multimedia content generated by the user and followers. Each recognizable product may be identifiable via an identifier. Furthermore, the products database 132 may list nutritional information for each product, uses of the product within recipes, and special instructions and warnings considering their usage. The products may include food and beverage products associated with nutritional and dietary supplements. An example product may include collagen-infused edible products, such as collagen peptide powders, collagen dietary supplements, collagen-based beverages such as collagen-infused waters or collagen-additives for beverages such as collagen creamers for coffee; and collagen solid food bars such as collagen protein bars. The memory may also include an application program interface (API) 134 that host, manage, or otherwise facilitate one or more applications in the user device 102 (e.g., application 114) or follower device 102A-102C. For example, the API 134 may manage an application that enables the monitoring nutritional needs and using social networks to influence nutrient intake. The diet recommendation engine 124 may comprise one or more programs, applications, or implementations that utilize the user database 130 and products database 132 to generate appropriate recommendations and discounts associated with a set of one or more products for a given user (e.g., first user).

[0019] The analytics server 120 may further include an update interface 138. The update interface 138 may comprise a database management program or application for managing one or more databases (e.g., user database 130, products database 132, etc.), such as via create, read, update, or delete (CRUD) functions. In some aspects, the update interface 138 may allow external devices (e.g., user device 102, follower devices 102A-C, social media server 140) to updated one or more databases, e.g., such as when a new user would like to sign up to an application for monitoring nutritional needs and using social networks to influence nutrient intake.

[0020] The analytics server 120 may further include an authentication module 138. The authentication module may be used to authenticate a new user that would like to register in the application 114 managed by API 134 for monitoring nutritional needs and using social networks to influence nutrient intake. For example, a user may send a request, via the user device 102, to the analytics server 120 to join the application. The request may reveal a user ID associated with the user device and a social network that the user is subscribed to (e.g., INSTAGRAM ®). The authentication module 138 may cause the analytics server 120 to send a personalized authentication code to the user device 102 associated with the user. The user may be prompted to add the code to a user profile associated with the user on a social network (e.g., a user profile on INSTAGRAM ®). The analytics server may then establish communications with a social media server 140 associated with the social network. The analytics server 120 may query the social network for a user bio having the personalized authentication code. After confirming that the user bio associated with the user on the social media network has the personalized authentication code, the analytics server 120 may verify the user and enlist the user into the application for monitoring nutritional needs and using social networks to influence nutrient intake.

[0021] The social media server 140 may comprise a local or a remote computing system associated with a social media network that the user and the user’s followers may be subscribed to. The social media server 140 may be an external device that the analytics server 120 may communicate with to request and receive further information pertaining to a social media user (e.g., user profiles, user activity, user posts, etc.). The social media server 140 may include database of social media profiles of the various users that are a part of the social media network associated with the social media server 140. In some aspects, each social media profile may be linked to the respective devices (e.g., user device 102, follower devices 102A-C) of the respective user of the social media profile, through a respective user device ID. Furthermore, the social media profiles database 148 may include information about the networks formed between the various social media users (e.g., followers of a given social media user, mutual friends or mutual followers between two social media users, etc.).

[0022] FIG. 2 illustrates an example user profile database 200 according to exemplary embodiments of the present disclosure. As discussed previously, the user profile database 200 may be a component of the analytics server 120. The user profile database 200 may allow the analytics server 120 to personalize diet and nutritional intake recommendations for the user with respect to various products, track a user’s ability to influence other users on the social network to engage with the product, and help the user to achieve health goals, among other functions. The user database 200 may comprise a plurality of user profiles 200A-200C corresponding to a plurality of users of the application.

[0023] For example, user profile 200A, which may be representative of the plurality of user profiles, may include a plurality of user attributes 122. For example, the user attributes 122 may be populated by information regarding one or more of age 204, gender 206, weight 208, height 210, activity level 212, food sensitivities 220, preferred diet 222, co-morbidities 220, physiological data 212 (e.g., blood pressure 214, glucose levels 216, etc.) and user health goals 225. Some examples of food sensitivities 212 include lactose, eggs, nuts, shellfish, soy, fish, and gluten sensitivities. Some non-limiting examples of a preferred diet 214 includes vegetarian, vegan, Mediterranean, kosher, halal, paleo, low carb, and low fat diets. Other non-limiting examples of physiological data 212 may include oxygen levels, heart rate, body temperature, body fat percentage, etc. Some non-limiting examples of co-morbidities 220 include diabetes, obesity, high blood pressure, high cholesterol, celiac, and heartburn. In some aspects, the user may be prompted, via application 114, to provide physiological data, e.g., through a wearable biosensor device 119. In some aspects the user may be prompted, e.g., via a message on application 114, to enter their health goals, e.g., via user interface 112. Some non-limiting examples of user health goals may include a target weight, a target physiological data (e.g., a target blood pressure, a target glucose level, a target body fat percentage, etc.).

[0024] The user profile 200A may further include a stored user ID 230 associated with the user and an authentication key 232. The user ID 230 may be used to identify the user, the user device 102 (or follower device 102A-102C) of the user, or a social media profile associated with the user. The authentication key may include a public and/or a private key generated by the authentication module 139 for verifying a user, or a social media profile used by the user, e.g., to enlist a new user into the application for monitoring nutritional needs and using social networks to influence nutrient intake.

[0025] The follower list 234 may comprise a list of other users connected to the user (e.g., followers) on a social network that the user is subscribed to. For example, the follower list 234 may include the respective user IDs of the followers.

[0026] The recent posts 236 may include a listing of recent content generated by the user within the social media network. For example, the recent posts may include photos or videos that the user may have posted. The repository of recent posts may also flag any associations with recognizable products (e.g., product association(s) 238) from the product database 132. For example, a recent image posted by the user that shows the user drinking a beverage containing recognizable dietary supplement may be flagged as having a product association.

[0027] Furthermore, the user profile 200A may track and record the purchase history 240 of the user, e.g., as it relates to products from product database 132. As will be described in more detail below, the purchase history 240 of a given user, recent posts associated with various other users, and product associations indicated in those recent posts may be used to determine an indicia of influence that a recent post of another use may have on the given user to purchase a specific product. The influencer score 242 may indicate the ability of a user to influence other users, e.g., followers in the follower list 234, to engage with a specific product that a recent post of the user may have mentioned, discussed, and/or shown.

[0028] The user database 200 may also include a user profile directory 244 that maps the various user profiles 200A-200C in the user database 200, and a linking engine 246 that links various data structures in the user database 200 (e.g., user profiles 200A-200C) to data structures in other databases (e.g., products database 132). Furthermore a query optimizer 248 may allow external components and devices to more efficiently and accurately retrieve information from the user database 200.

[0029] FIG. 3 illustrates an example dietary supplement product recommendation engine (“diet recommendation engine”) 300 according to exemplary embodiments of the present disclosure. As previously discussed, the diet recommendation engine 300 may comprise one or more programs, applications, or implementations in the analytics server 120 that utilize user attributes from the user database 130 and product information from the products database 132 to generate appropriate recommendations and discounts associated with a set of one or more products for a given user. [0030] In an example embodiment, the diet recommendation engine 300 may comprise a user health plan unit 302, a dietary restrictions filter unit 308, an optimization unit 318, and a product recommendation unit 326. The user health plan module 302 may comprise instructions for computing a health plan for the user based on the user health goals 304 retrieved from a user profile of the user (e.g., from user profile database 200)) and the user current health status 306. The user current health status 306 may comprise a data structure storing various user attributes that indicate the current health of a user. For example, the user current health status 306 may comprise a calculated body mass index (BMI) for a given user based on the height 210, weight 208, gender 206, and age 204 of the given user. The user health goal may be a desired BMI that the user would like to achieve. The user health plan module 302 calculates the difference in weight that may be necessary to achieve that. Furthermore, based on an indicated activity level 218, the use health plan module 302 may calculate, for example, the dietary needs of the given user to achiever the user health goals 304 indicated by the user.

[0031] The dietary filter restrictions unit 144, which may restrict the results provided by the product recommendation unit 326, may comprise filters for one or more of food sensitivities 310, preferred diets 312, comorbidities 316, and physiological restrictions 316. The optimization unit 318 may contain optimization rules based on one or more of caloric intake 320, specific nutrients 322, and/or collagen level 324.

[0032] The diet recommendation engine 300 may further include a product recommendation unit 326 that may store programs and instructions for generating a list of products (e.g., product offerings 328) that pertain to the user (e.g., “user-specific products”) based on the user attributes provided, assessments rendered by the user health plan module 302, dietary filter restrictions 308, and optimization unit 318. The product offerings 326 may include user-specific products comprising food and beverage products associated with specific nutrients (e.g., proteins (e.g., collagen), vitamins, minerals, fat, water, etc.). The product offerings may be identifiable from the products database 132. The product recommendation unit 326 may further generate a list of recommended recipes 330 based on the product offerings. Furthermore, the product recommendation unit 326 may generate a discount code 332 to allow the user to purchase and/or obtain a product from the product offering 328 at a discounted price, or for free. The level of discount applied to the price of the product (“discount level”) may be correlated with an influencer score of the user. For example, a user that is particularly influential in getting followers to engage with products from the product database 132 may be able to achieve a discount level that allows the user to have a greater discount off of the product offerings (including the ability to obtain the products for free), and/or allows the user to have a greater number or variety of product offerings.

[0033] FIG. 4 illustrates a flow diagram of an example method 400 of monitoring nutritional needs and using social networks to influence nutrient intake, according to an exemplary embodiment of the present disclosure. Method 400 may be performed by one or more processors of the analytics server 120. Furthermore, while method 400 may concern the ability for a user of the application 114 to allow the analytics server 120 monitor the user’s nutritional needs and use social networks to influence nutrient intake among the user’s followers, method 400 may be implemented by other users, including the user’s followers in in parallel, via the respective user devices of the other users. For simplicity, the term “first user” may be used to refer to the user of the user device utilizing the below described method 400, to distinguish the user from the other users (e.g., followers).

[0034] Referring to method 400, step 402 may include the analytics server receiving a message from a user device associated with a first user (e.g., as in step 402). The message may comprise a social media post with metadata (e.g., hashtag) that allows the social media post to be sent to the analytics server 120. Also or alternatively, the message may be sent directly to the analytics server 120 by the user device 102. In one aspect, the first user may be interested in improving one’s health or enhancing one’s dietary lifestyle, and may be interested in receiving food and beverage products associated with specific nutrients or dietary supplements. The first user may be made aware (e.g., from another user in a social network that the user is subscribed to) of the application 114 for monitoring nutritional needs and using social networks to influence nutrient intake. Furthermore, the user may be made aware that the user could have the opportunity to receive discounted products based on the user’s ability to influence other users in the first user’s social network to engage with a specific recognizable product. The first user may thus send the message, via application 114, and the request may be received by the analytics server 120 over communications network 150. The message may comprise a user ID (e.g., first user ID) for the social network, an image data, and a time of generation of the image data. The image data may be based on a multimedia content (e.g., image, video, etc.) generated by the user device 102, e.g., to capture a moment in the life of the first user that involves the use of, or depiction of, a recognizable product.

[0035] At step 404, the analytics server 120 may determine whether the image data received in the message shows an identifier associated with a first recognizable product. As used herein, a recognizable product may be a product that the analytics server 120 may be offering to various users of the application 114 based on user attributes, influencer score, and user needs, and at various or no discount levels. The recognizable product that may be show in the image data received with the message in step 402 may be referred to as “first recognizable product” to differentiate it from other recognizable products that will be discussed further herein. Furthermore, a recognizable product may have features that are identifiable from a depiction of the recognizable product in image data (e.g., the identifier of the recognizable product, and the identifiable features may be stored in the products database 132. As used herein, non-limiting examples of an identifier of a product may include, but are not limited to: a name, logo, trademark, or a trade dress associated with the recognizable product; a name, logo, trademark, or a trade dress associated with the recognizable product; a texture, color, and/or shape of the product; and/or an audio recording of the same of the product or manufacturer of the product. In some aspects, the identifier of the product may be within a caption or a handle associated with the multimedia content on which the image data is based. For example, an identifier of a product ABC may include a caption for an image posting that reads as #ABC. If no identifier is shown, the analytics server 120 may continue to monitor for messages received that do include an identifier, or may prompt the user to generate image data that shows the identifier.

[0036] If the image data shows the identifier associated with the first recognizable product, then the analytics server 120, at step 406, may receive a plurality of follower user IDs corresponding to a plurality of followers associated with the first user ID. The plurality of follower IDs may be received using the first user ID. For example, the user may be connected to other users (e.g., followers) in a social network, and each follower may have a respective user ID (e.g., follower ID) that can enable the analytics server 120 to query and receive information pertaining to the follower from a social media server 140 corresponding to the social network.

[0037] At step 408, the analytics server 120 may analyze user activity associated with each follower user ID to determine an indicia of influence that the first user may have to a given follower to cause the given follower to engage with the first recognizable product. In some aspects, engaging with a recognizable product may range from being impressed by a social media post depicting the recognizable product (e.g., via viewing, a “like,” or other indication of appreciation) to the actual purchase of the recognizable product by the given follower. The user activity of each follower user ID may be obtained by establishing communications with the social media server 140 corresponding to the social media server. Furthermore, the user activity that is analyzed may be after the time of the generation of the image data showing the first recognizable object. In one embodiment, the analytics server 120 may access, for each follower user ID, a plurality of image data associated with the follower ID. The analytics server 120 may then identify, for each follower user ID, and from the plurality of image data associated with each follower ID, an identifier associated with another recognizable product (e.g., second recognizable product) that may or may not be the same as the recognizable product shown in the image data provided by the first user. If the second recognizable product is the same as the first recognizable product, then the analytics server 120 may determine that the first user exerted a relatively higher indicia of influence on the follower than if the second recognizable product were different from the first recognizable product.

[0038] In another embodiment, the analytics server 120 may determine, for the respective follower corresponding to each follower user ID, a purchase history associated with the respective follower. For example, for a given follower, the analytics server 120 may track stored account sheets to determine if any recognizable products from the product database 132 had been purchased by the given follower after the time that the image data had been generated by the first user. If the analytics server 120 identifies a purchase of the first recognizable product by the given follower, the analytics server may designate a relatively higher indicia of influence caused by the first server to the given follower, with respect to the recognizable product.

[0039] At step 410, the analytics server 120 may generate, based on the respective indicia of influence caused by the first user to each follower, an influencer score for the first user. For example, the analytics server may summate the respective indicia of influence calculated for each follower of the first user to generate the influencer score for the first user.

[0040] In some aspects, the influencer score may also or alternatively be based on the first image data generated by the first user. For example, an image data showing the recognizable product and/or the identifier of the recognizable product more clearly may result in a relatively higher influencer score. In another example, the influencer score may be based on a type of engagement with the first recognizable product shown in the image data. For instance, an image showing the first user directly holding a beverage that is a recognizable product, with its identifier (e.g., branding) visible on the beverage may be a higher level of engagement than an image showing the first user occupied in an activity not related to the beverage, while the beverage and its identifier is shown in the distant background. The machine learning training module 124 may assist the analytics server 120 to be able to categorize the level of engagement. The machine learning training module 124 may develop this ability by using training data comprising reference images capturing sample recognizable products being used at varying levels of engagement, with training outputs indicating the correct level of engagement. In one aspect, the training data may be used to develop a trained convolutional neural network model to detect a level of engagement based on an inputted image data that is known to show a recognizable product.

[0041] At step 412, the analytics server 120 may generate, based on the influencer score, a discount level for the first user. For example, a greater influencer score (e.g., a greater ability of the first user to cause one or more of the followers to engage with the first recognizable product) may result in a larger discount level. As discussed previously, the discount level may include the discounting of a purchase price entirely (e.g., for free).

[0042] In some embodiments, the analytics server 120 may further assist the first user in achieving their health goals. For example, the user may input and/or upload, via Ul 112, various user attributes into the application 114. The analytics server 120 may use these user attributes to develop a plan for the user to achieve his or her desired health goal, and offer user- specific products that help the user meet the desired health goal.

[0043] Thus, at step 414, the analytics server 120 may receive, based on a user profile associated with the first user, one or more user attributes. The user profile 116, which may or may not necessarily be the same as a social media profile associated with the user, may be a profile used in the application 114 to personalize the application 114 for the first user. As discussed previously in relation to FIG. 2, non-limiting examples of user attributes may include age, gender, weight, height, activity level, food sensitivities, preferred diet, comorbidities, physiological data, and user health goals.

[0044] At step 416, the analytics server 120 may determine, based on the user attributes, a set of user-specific products. As previously discussed in relation to FIG. 3, the user- specific products may be based on an assessment of products that can help the user meet their desired health goals, and may be filtered (e.g., based on dietary restrictions), and optimized accordingly.

[0045] In some aspects, user attributes comprising real-time physiological data (e.g., heart rate, blood pressure, glucose level, etc.) may enable a more accurate monitoring of nutritional needs and a more effective product offering for the first user. For example, the analytics server may prompt the first user to input physiological data by sending, via application 114 on the mobile device 102, a message requesting the first user to input physiological data. For example, a first user desiring to improve one’s athletic performance over time may be prompted to provide a heart rate. A biosensor or wearable associated with or communicatively linked to the user device 102 may be used by the first user to provide such physiological input. The analytics server 120 may then receive, from the mobile device, the physiological data.

[0046] The first user’s health goal is yet another user attribute that can be used to determine a set of user-specific products for the first user. In one aspect the analytics server 120 may send, via the application 114 on the user device 102, a message requesting that the first user to input their health goal. Thereafter, the analytics server 120 may receive the health goal indicated by the first user. Based on the health goal, the analytics server may determine a set of first user-specific products. In further aspects, the user’s stated health goal may compared with the user’s current physiological data to determine the set of first user-specific products.

[0047] At step 418, the analytics server 120 may send, to the user device associated with the first user, and based on the discount level, a discount code for one or more of the set of user-specific products. The discount code may allow the user purchase one or more of the set of user-specific products at a discounted price or for free. In some aspects, the remaining products of the set of user-specific products may nevertheless be products recommended to the first user based on the user attributes of the first user. Also or alternatively, the discount code may be applied to all or none of the set of user-specific products. The first user may then choose to post (e.g., generate multimedia content) on the social network showing the product, and method 400 may thus be repeated.

[0048] FIG. 5 illustrates a screenshot of an example user interface for monitoring nutritional needs and using social networks to influence nutrient intake, according to an embodiment of the present disclosure. The example screenshot may be based on a graphical user interface provided by application 114, and may be viewable by the user on user device 102. The example screenshot may depict a dashboard 502 providing options to the user for ordering products 504, getting more information 506) (e.g., concerning a user attribute, influencer score, etc.), or submitting a post on a social network (e.g., submit post 508). The submitted posts may comprise the generation of multimedia content (e.g., images, video, etc.) to a network of followers of the user. As discussed previously, the generated multimedia content may indicate an association with a recognizable product (e.g., by showing an identifier of the recognizable product in the image or video). Under the analytics 510 section of the user interface, the user may also be able to view and analyze the quantifiable effects of the user’s efforts at influencing followers. For example, under the impressions category 512, the screenshot indicates that the user has impressed 210 followers, e.g., by having the followers view, like, and/or indicate appreciation for a multimedia content showing a recognizable product and posted on the social network. Under the conversions category 514, the screenshot indicates that the user has converted 10 followers, e.g., by having 10 followers purchase a recognizable product that was recently the subject of a multimedia content generated by the user and posted on the social network. Under the total sales category 516, the screenshot indicates that the user has generated $100 worth of sales based on the user’s influencing activity. The total sales may be based on the sales that are directly a result of purchases of the recognizable product that was recently the subject of a multimedia content generated by the user and posted on the social network.

[0049] All of the disclosed methods and procedures described in this disclosure can be implemented using one or more computer programs or components. These components may be provided as a series of computer instructions on any conventional computer readable medium or machine-readable medium, including volatile and non-volatile memory, such as RAM, ROM, flash memory, magnetic or optical disks, optical memory, or other storage media. The instructions may be provided as software or firmware, and may be implemented in whole or in part in hardware components such as ASICs, FPGAs, DSPs, or any other similar devices. The instructions may be configured to be executed by one or more processors, which when executing the series of computer instructions, performs or facilitates the performance of all or part of the disclosed methods and procedures.

[0050] It should be understood that various changes and modifications to the examples described here will be apparent to those skilled in the art. Such changes and modifications can be made without departing from the spirit and scope of the present subject matter and without diminishing its intended advantages. It is therefore intended that such changes and modifications be covered by the appended claims.

Claims

1. A method of monitoring nutritional needs and using social networks to influence nutrient intake, the method comprising: receiving, by a computing device having one or more processors and from a mobile device associated with a first user, a message comprising image data, a time of generation of the image data, and a first user ID linking the first user to a social network; determining, by the computing device, that the image data shows an identifier associated with a first recognizable product; receiving, based on the first user ID, a plurality of follower user IDs corresponding to a plurality of followers connected to the first user on the social network; analyzing user activity associated with each follower user ID to determine, for each follower, an indicia of influence caused by the first user to each follower with respect to the first recognizable product, wherein the user activity associated with each follower user ID occurs after the time of the generation of the image data; generating, based on the respective indicia of influence associated with each follower, an influencer score for the first user; and generating, based on the influencer score, a discount level for the first user; and sending, to the mobile device and based on the discount level, a discount code for one or more first user-specific products.

2. The method of claim 1 , further comprising: identifying, by the computing device and using the image data, a level of engagement with the first recognizable product, wherein the generating the influencer score for the first user ID is further based on the level of engagement with the first recognizable product.

3. The method of claim 1 , further comprising: receiving, based on a user profile associated with the first user ID, one or more first user attributes; and determining, based on the first user attributes, a set of first user-specific products, wherein one or more first user-specific products is from the set of first user-specific products.

4. The method of claim 3, wherein the receiving the one or more first user attributes comprises: sending, via an application on the mobile device, a message requesting the first user to input physiological data; and receiving, from the mobile device, the physiological data.

5. The method of claim 4, further comprising: sending, via an application on the mobile device, a message requesting the first user to input a health goal; receiving, from the mobile device, the health goal; determining, based on a comparison of the physiological data and the health goal, the set of first user-specific products.

6. The method of claim 3, further comprising: sending, via an application on the mobile device, a message requesting the first user to input one or more of an activity level, a food sensitivity, a preferred diet, or a comorbidity; and filtering, from the set of first user-specific products, a first user-specific product based on the one or more of the activity level, the food sensitivity, the preferred diet, or the comorbidity.

7. The method of claim 1 , wherein the analyzing the user activity associated with each follower user ID comprises: accessing, for each follower user ID, a plurality of image data associated with the follower

ID; and identifying, for each follower user ID, and from the plurality of image data associated with each follower ID, an identifier associated with a second recognizable product.

8. The method of claim 7, wherein, for at least one follower user ID, the identifier associated with the first recognizable product comprises the identifier associated with the second recognizable product; and the method further comprising: designating a higher indicia of influence caused by the first user to the at least one follower user ID, with respect to the recognizable product.

9. The method of claim 1 , wherein the analyzing the user activity associated with each follower user ID comprises: determining, fora given follower of the plurality of followers, a purchase history associated with the given follower; identifying, using a respective follower user ID of the given follower, a corresponding purchase of the first recognizable product; and designating, for the given follower, a higher indicia of influence caused by the first user to the given follower with respect to the first recognizable product.

10. A system for monitoring nutritional needs and using social networks to influence nutrient intake, the system comprising: one or more processors; and memory storing instructions that, when executed by the processors, cause the system to: receive, from a mobile device associated with a first user, a message comprising image data, a time of generation of the image data, and a first user ID linking the first user to a social network; determine that the image data shows an identifier associated with a first recognizable product; receive, based on the first user ID, a plurality of follower user IDs corresponding to a plurality of followers connected to the first user on the social network; analyze user activity associated with each follower user ID to determine, for each follower, an indicia of influence caused by the first user to each follower with respect to the first recognizable product, wherein the user activity associated with each follower user ID occurs after the time of the generation of the image data; generate, based on the respective indicia of influence associated with each follower, an influencer score for the first user; generate, based on the influencer score, a discount level for the first user; and send, to the mobile device and based on the discount level, a discount code for one or more first user-specific products.

11 . The system of claim 10, wherein the instructions, when executed, further cause the system to: identify, using the image data, a level of engagement with the first recognizable product, wherein the generating the influencer score for the first user ID is further based on the level of engagement with the first recognizable product.

12. The system of claim 10, wherein the instructions, when executed, further cause the system to: receive, based on a user profile associated with the first user ID, one or more first user attributes; and determine, based on the first user attributes, a set of first user-specific products, wherein one or more first user-specific products is from the set of first user-specific products.

13. The system of claim 12, wherein the instructions, when executed, cause the system to receive the one or more first user attributes by: sending, via an application on the mobile device, a message requesting the first user to input physiological data; and receiving, from the mobile device, the physiological data.

14. The system of claim 13, wherein the instructions, when executed, further cause the system to: send, via an application on the mobile device, a message requesting the first user to input a health goal; receive, from the mobile device, the health goal; determine, based on a comparison of the physiological data and the health goal, the set of first user-specific products.

15. The system of claim 12, wherein the instructions, when executed, further cause the system to: send, via an application on the mobile device, a message requesting the first user to input one or more of an activity level, a food sensitivity, a preferred diet, or a comorbidity; and filter, from the set of first user-specific products, a first user-specific product based on the one or more of the activity level, the food sensitivity, the preferred diet, or the comorbidity.

16. The system of claim 10, wherein the instructions, when executed, cause the system to analyze the user activity associated with each follower user ID by: accessing, for each follower user ID, a plurality of image data associated with the follower

17. The method of claim 16, wherein, for at least one follower user ID, the identifier associated with the first recognizable product comprises the identifier associated with the second recognizable product; and the wherein the instructions, when executed further cause the system to: designate a higher indicia of influence caused by the first user to the at least one follower user ID, with respect to the recognizable product.

18. The system of claim 10, wherein the instructions, when executed, cause the system to analyze the user activity associated with each follower user ID by: determining, fora given follower of the plurality of followers, a purchase history associated with the given follower; identifying, using a respective follower user ID of the given follower, a corresponding purchase of the first recognizable product; and designating, for the given follower, a higher indicia of influence caused by the first user to the given follower with respect to the first recognizable product.

19. A non-transitory computer readable medium for use on a computer system containing computer-executable programming instructions for monitoring nutritional needs and using social networks to influence nutrient intake, the instructions comprising: authenticating, by a computing device having one or more processors, a mobile device associated with a first user, based on a first message posted on the social network; receiving, by the computing device and from the mobile device, a second message comprising image data, a time of generation of the image data, and a first user ID linking the first user to a social network; determining, by the computing device, that the image data shows an identifier associated with a first recognizable product; receiving, based on the first user ID, a plurality of follower user IDs corresponding to a plurality of followers connected to the first user on the social network; analyzing user activity associated with each follower user ID to determine, for each follower, an indicia of influence caused by the first user to each follower with respect to the first recognizable product, wherein the user activity associated with each follower user ID occurs after the time of the generation of the image data; generating, based on the respective indicia of influence associated with each follower, an influencer score for the first user; and generating, based on the influencer score, a discount level for the first user; and sending, to the mobile device and based on the discount level, a discount code for one or more first user-specific products.

20. The computer readable medium of claim 19, wherein the instructions further comprise: identifying, by the computing device and using the image data, a level of engagement with the first recognizable product, wherein the generating the influencer score for the first user ID is further based on the level of engagement with the first recognizable product.