Patent Application
20190205938
This application is being filed concurrently with U.S. patent application Ser. No. 14/588,344, filed on Dec. 31, 2014 and entitled “Product Recommendation Based On Perceived Value,” which is incorporated herein by reference in its entirety.
The present disclosure relates to a method and system for determining perceived value. More specifically, it relates to determining perceived value of a good or service and using the determination to make purchase and/or exchange recommendations and to dynamically place a good or service in multimedia.
Consumer attitudes and decision making may be based on a perceived value of a product. Perceived value can be difficult to measure. For example, consumers may have varied definitions for what constitutes value: price, product features, product quality, etc. There exists a need in the art to accurately determine perceived value and leverage the understanding of perceived value in marketing activities. There also exists a need in the art to recommend products for purchase and/or exchange based on perceived values.
Strategic use of product placement in audiovisual media (multimedia) can increase product awareness, enhance product perception, and increase sales. The efficacy of product placement may depend, in part, on the susceptibility of an audience, e.g., a perception of product value. Thus, there exists a need in the art for a method of product placement which takes advantage of a viewer's perceived value of the product.
In an embodiment, a method incorporates an image of a product into template video data. The method may include determining a perceived value, i.e. a user's perception of a product represented by a product image. If the perceived value is above a threshold, the method may generate a frame of video data containing the product image incorporated into the frame of template video data. The method may render the generated frame of video data.
In another embodiment, a method advertises a product by monitoring user reaction to and/or interaction with the product. The method may also assess a user's perception of the product by weighting the user's reaction(s) and/or interaction(s). The method may place the product within multimedia by replacing a generic version of the product with the product, render the multimedia, and assess a fee for rendering the multimedia.
The content publisher 160 may include an application server 140 and storage 150. The content publisher 160 may include a data exchange platform such as a virtual marketplace. The virtual machine may host transactions such as purchasing and selling goods and services including auctions. The data exchange platform may also host processes assisting the transactions such as generating recommendations, synchronizing financial journals, distribution of goods, collection, and payment. The application server 140 may include a perception map machine 148, a product recommendation machine 142, a gift exchange machine 144, a gift return machine 146, and a product placement machine 152. The application server 140 may be communicatively coupled to storage 150.
The network 120 may include any wired connection, wireless connection, or combination thereof, a non-exhaustive list including: LAN (local area network), WAN (wide area network), VPN (virtual private network), cellular network, satellite network, Wi-Fi network, optical network, the Internet, and a Cloud network. The network 120 may use any combination of transmission protocols or techniques.
Storage 150 may include any permanent memory circuit, temporary memory circuit, or combination thereof, a non-exhaustive list including: ROM (read-only memory), RAM (random access memory), EEPROM (electrically erasable programmable read-only memory), Flash memory, CD (compact disk), DVD (digital versatile disk), hard disk drive, or solid state drive.
Each of the perception map machine 148, the product recommendation machine 142, the gift exchange machine 144, the gift return machine 146, and the product placement machine 152 may be operated according to the methods described herein. For example, the perception map machine 148 may perform the methods shown in
The system 100 is an illustrative system having a client-server architecture. The system may be embodied in other types of architectures, including, but not limited to peer-to-peer network environments and distributed network environments.
The processor 212 executes computer program code, for example code stored in memory 214 or storage 250. The execution of the code may include reading and/or writing to/from memory 214, storage 250, and/or I/O device 234. The program code may execute the methods described herein.
Memory 214 may include, or otherwise may communicate with a memory management system 264. The memory management system 264 may include a perception map engine 216, a product placement engine 218, and a gift engine 222. The perception map engine 216 may be configured to make computing device 210 operable to monitor reactions and interactions by a user 260 with the device 200 or sent to the device 200, for example via a network. The perception map engine may implement the methods described herein, e.g., in relation to
The product placement engine 218 may be configured to make computing device 210 operable to place products within multimedia content. The product placement engine may implement the methods described herein, e.g., in relation to
The gift engine 222 may be configured to make computing device 210 operable to make purchasing recommendations and exchange recommendations. The gift engine may implement the methods described herein, e.g., in relation to
One of ordinary skill in the art would understand that a different number of engines than the ones shown may be included in, or otherwise may communicate with memory 214. The functionality described for each engine may also be apportioned to different engines. Additional engines are also possible. For example, a billing engine may be configured to charge a vendor for at least some of the information stored in storage 250 or memory 214. The billing engine may be further configured to charge vendors for product placement or display of products at a particular time and/or location. For example, the billing engine may charge a vendor for incorporating a product into a television show. As another example, the billing engine may charge a vendor for displaying a product within a list of search results.
Memory 214 may include local memory usable during execution of program code, cache memory temporarily storing program code, and bulk storage. The local memory may include any permanent memory circuit, temporary memory circuit, or combination thereof, a non-exhaustive list including: ROM, RAM, EEPROM, and Flash memory.
The I/O device 234 may include any device enabling a user to interact with the computing device 210, including but not limited to a keyboard, pointing device such as a mouse, touchscreen, microphone, speaker system, computer display, and printer.
The computing device 210 may include any special purpose and/or general purpose computing article of manufacture executing computer program code, including, but not limited to, a personal computer, a smart device such as a smartphone, and a server. The computing device may be a combination of general and/or specific purpose hardware and/or program code.
The device 200 may be embodied as a single server or a cluster of servers including at least two servers communicating over any type of communications link. A communications link may include any wired connection, wireless connection, or combination thereof, a non-exhaustive list including: LAN (local area network), WAN (wide area network), VPN (virtual private network), cellular network, satellite network, Wi-Fi network, optical network, the Internet, and a Cloud network. The communications link may use any combination of transmission protocols or techniques.
Consumers may perceive a value or have a taste for a particular good. For example, a consumer may perceive that a particular brand is valuable. Brand perception can be related to or independent of a style or form factor of a product. For some consumers, a perceived value of a good may influence whether the consumer makes a purchase or a return. The perceived value may also be weighed against the price at which a good is offered for sale in making a purchasing decision. Thus, there exists a need in the art to determine the perceived value of a good.
The operations of
User perception may be described and stored in a “map” of perceptions. A map of perceptions (“perception map” for simplicity) refers to a profile of attributes that may be used to predict purchasing behavior. For example, attributes may include a user's tastes, views, values, and habits. The perception map may include a single attribute, or many attributes. The perception map may store a relationship among product purchasing factors, such as product cost and product quality. The perception map or analytics derived from the map may be sold or licensed as described herein.
In another embodiment, the perception map may be used to select products for development. For example, popularity, i.e., high perceived value, of a product may indicate that additional products in a family of products related to the product may also be popular. As another example, an indication that a brand for a product is generally unimportant may suggest that the product is a good candidate for producing a generic version because consumers would likely make a purchasing decision with little or no regard for the brand of the product. The importance of a brand to a purchasing decision may be measured by a perceived value in relation to a threshold value.
The embodiments herein may refer to a good, product, or service. One of ordinary skill in the art would understand that the principles described herein apply analogously to a good, a product, or service.
In box 302, the question may be of various forms. For example, the question may ask a user to guess the price of the product. As another example, the question may ask a user whether the user would buy the product at a pre-definable price. As yet another example, a question may present a product with a price and asking the user whether the price offered is too high or too low. Further examples of questions are shown in
The method 300 may be a part of another process. For example, a user may be logged into or engaging with a virtual environment prior to commencement of method 300. The method 300 may find application in a user-interactive questionnaire or game such as a snacking game. A snacking game may be a game designed with questions that elicit responses after a short period such as 10 to 60 seconds. For example, questions may be generated according to the steps of method 300 in a web application such as a smartphone or tablet application. In an embodiment, the game may be an auctioning game or include features resembling an auctioning process in which a user bids for a product. The bidding may indicate a perceived value by determining a minimum and maximum price the user is willing to pay for the product.
Each response may provide a data point for a perception map for the user, indicating the user's value of a particular product, service, and/or brand or a group thereof.
From the perspective of a user, a particular product may have an associated price and quality, represented as a coordinate on the perceptual map 500 in
In the example of User 1 shown in perceptual map 500, User 1 is not expected to purchase a product below a certain level of quality regardless of price. That is, User 1 will not purchase a product having a quality below the level of the dashed line. For the products shown in perceptual map 500, User 1 is not expected to purchase products A, B, or C. User 1 is expected to purchase product D.
In the example of User 2 shown in perception map 520 in
More complex user perception profiles are possible. For example, in the example of User 3 shown in perceptual map 540 in
Each point on the perceptual map represents a particular user's perception of a particular product. Perceptions may vary from user to user. This is illustrated by the differing perceptions of Users 1, 2, and 3 in the perceptual maps 500, 520, and 540. For example, product A is in the lower right quadrant for Users 1 and 3, and in the lower left quadrant for User 2.
A user may also have product preferences based on brand preferences. A preference may be represented in a perception map in a tiered format. A user is expected to purchase a product in a higher tier over a product in a lower tier notwithstanding attributes associated with each product. In the example shown in perception map 560, the user would purchase a product in the first tier (“Tier I”) over a product in a second tier (“Tier II”). That is, the user would never purchase a product from the second tier before purchasing a product in the first tier. For example, in Scenario 2, although Item G is offered at a price ($1) lower than Item B ($3), the user would nevertheless be expected to prefer Item B. Of course, an order of products may change over time or after a purchase is made.
The examples provided above refer to a user considering purchase of a product for purely illustrative purposes. A perception map may also be applicable to other user decisions including return of a product. For example, a perception map may indicate factors in a user's interest in returning a product. As another example, a perception map may indicate that a return of a product influences a user's interest in purchasing another product.
While the foregoing discussion regarding the perceptual maps refers to a user associated with each map, one of ordinary skill in the art would understand that a map may correspond to a group of users, and that maps may be aggregated. A preference may also be represented in mathematical form. For example, once a threshold number of data points is accumulated, a curve may be fitted to the data points and associated and stored with a user to predict purchasing behavior, e.g., the user is not expected to purchase products below a curve representing attribute(s) of a product. Each of the perceptual maps 500, 520, 540, and 560 may be stored in a storage system according to conventional methods and data structures, for example in a database table accessible via SQL queries.
The perception map may find application in many processes and systems, for example, product placement, providing purchasing recommendations, providing exchange recommendations, and providing gift return value recommendations. Each of these examples is further described herein.
The efficacy of product placement in multimedia may depend, in part, on the perception of the user of the multimedia. For instance, a user who perceives a higher value of a product may be considered more susceptible to the product, i.e., likely to purchase the product. By leveraging user perception, a product may be dynamically placed in multimedia to maximize efficiency of advertising. In other words, product placement may be based on the likelihood of a particular user to purchase the product and may be dynamically adapted with the changing audience of the multimedia. One advantage of this practice is that if a user will never purchase a particular brand, that brand is not futilely advertised to the user. Alternatively, even if a user typically does not prefer a particular brand, the brand may be advertised to the user at a most opportune time, e.g., when the user prefers the brand more than the user historically has favored the brand. The dynamic adaptation of multimedia for product placement may include swapping a stock image of a product in a multimedia sample with a particular product to which a user is more susceptible.
The threshold value in box 608 may be defined automatically or by a designer. For example, the threshold may be set such that a perception rating above the threshold value indicates that the user is more likely than not to purchase the product. As another example, the threshold may be set such that a perception rating corresponds to a quantifiable likelihood of a user to purchase the product.
In an embodiment, a product may be selected for placement from among several candidates based on one or more factors such as: a perception map with a ranking, such as the perception maps shown in
In an embodiment, method 600 may be performed by a server. For example, a product may be incorporated into the multimedia content and distributed to a client for decoding and/or streaming. In another embodiment, method 600 may be performed by a client. In this example, a client device may have a locally stored image of a product and/or a template video frame. The image of the product or the template video frame may alternatively be transmitted to the client device. Based on a user's perceptions, the method 600 may make the client device operative to place the product in the template video frame.
In an embodiment, method 600 may be performed as a pre-process. Pre-processing of an image or video include determining a set-up such as a composition for a shooting of a scene. This is represented in
In another embodiment, method 600 may be performed as a post-process. Post-processing of video may include processing an image or video frame (“template frame” for simplicity) to replace a stock product with a replacement product, the selection of the replacement product being based on user perception. In
Scenes 800, 840, and 880 may each represent a still image or a video frame forming part of a movie, television show, radio broadcast, podcast, documentary, news report, or the like. The scenes 800, 840, and 880 and the figures therein may be live action, an animation, or the like. The principles of product placement in video are also applicable to product placement in other forms of multimedia such as audio.
The threshold value in box 628 may be defined automatically or by a designer. For example, the threshold may be set such that a perception rating above the threshold value indicates that the user is more likely than not to purchase the product. As another example, the threshold may be set such that a perception rating corresponds to a quantifiable likelihood of a user to purchase the product.
In an embodiment, a product may be selected for placement from among several candidates based on one or more factors such as: a perception map with a ranking, such as the perception maps shown in
In an embodiment, method 650 may be performed by a server. For example, a product may be incorporated into the multimedia content and distributed to a client for decoding and/or streaming. In another embodiment, method 650 may be performed by a client. In this example, a client device may have a locally stored audio clip of a product and/or a template audio sample. The audio clip or the template audio sample may alternatively be transmitted to the client device. Based on a user's perceptions, the method 650 may make the client device operative to place the product in the template audio sample.
In an embodiment, method 650 may be performed as a pre-process. Pre-processing of audio may include determining a set-up for narration for an audio sample. This is represented in
In another embodiment, method 650 may be performed as a post-process. Post-processing of audio may include processing an audio sample (“template audio sample” for simplicity) to replace a stock product with a replacement product, the selection of the replacement product being based on user perception. In
In an embodiment, a business method performs the steps for the methods described herein on a fee, advertising, and/or subscription basis. A service provider, for example via the content publisher 160 shown in
In an embodiment, the amount of fee assessed may depend on any combination of the following: the type of multimedia into which the product is incorporated, when the multimedia is distributed to an audience, a temporal location in the multimedia where the product is placed, a spatial location in the multimedia where the product is placed, etc. For example, a product placed in the beginning or end of a multimedia stream may incur a higher fee than a product placed somewhere in the middle of the multimedia stream based on the reasoning that more viewers are likely to pay attention in the beginning or end of a multimedia stream. As another example, a product placed in a less prominent location within a scene such as a shop window of may incur a lower fee than a product placed in a more prominent location within the scene such as a handbag held by a title character of a film. In an alternative embodiment, a flat fee is assessed for placing a product anywhere in the multimedia. The fee assessment may be performed by a device such as the application server 140 shown in
A perception map, developed for example according to method 300, may also be used to provide purchasing recommendations. For example, when making a purchase (“gift”) for another person (“recipient” for simplicity), the purchaser (“giver” for simplicity) may not be well-acquainted with the tastes and values of the recipient. A perception map can be used in the giver's search for a gift to recommend goods that the recipient value and thus would be happy to receive.
The query received in box 1002 may include a product type, a price range, a specific recipient, or a group of recipients, an amount that the gift giver wishes to spend, etc. The results (box 1006) may be adjusted such that the recommended products meet specifiable guidelines. For example, all of the displayed results may be products that are priced below the amount the gift giver wishes to spend.
A perception map, for example developed according to method 300, may be used to provide exchange recommendations. For example, when a recipient returns an item that was gifted, the exchange platform may surface personalized recommendation(s) for the recipient with the same or similar perceived value as the item. The gift giver may thus be credited with giving a higher value gift, the recipient receives a desirable item in exchange, and the exchange platform facilitates clearing of an item with a higher retail value but is on markdown. For example, a giver may purchase a gift at a discount from a full retail price. When the recipient returns the gift, recommendations may be provided that have a comparable perceived value to the perceived value of the gift. A perception map of perceived values can be used to suggest a product for exchange.
The product recommendation provided in box 1108 may be based on at least one of the following factors: a gift giver's designated budget, an inventory of a merchant, whether the user already owns the product, etc. For example, a merchant may prioritize sale of a particular product over another product. When two products are of the same or similar perceived value (i.e., within a threshold range) to a user, the method may select the product that the merchant prefers to sell. Merchant preferences may be specifiable, e.g., in a record of the product, based on profit margin, etc. The method may determine whether a user already owns a product based on browsing or purchase history, for example, data associated with a user profile.
In an alternative embodiment, in box 1112, the user may select more than one item. For example, the user may select a combination of items that total to equal to or less than the price paid for the gift. Method 1100 may be part of another method. For example, subsequent to step 1114, steps may be performed for realizing the exchange. A mailing label for the gift may be generated and an inventory may be updated to reflect the exchange. The selected items may be sent to the user to complete the exchange.
In another embodiment, prior to generating a product recommendation in box 1108, the method 1100 may notify a gift giver that a gift exchange has been requested. The method 1100 may request a spending amount (box 1106). The spending amount may be a threshold price such that the method 1100 generates recommendations of only those products that are below the spending amount in box 1108.
A perception map, for example developed according to method 300, may be used to make up a difference between perceived and retail values of a gift when the gift is returned. A gift giver may be provided an option at the time of purchase or time of return to define a return value. For example, the giver may provide additional funds such that a gift card may be of a value higher than it would be without the additional funds. This way, at the time of return, the recipient perceives that the giver originally spent more on the gift.
In an alternative embodiment, the method 1200 may begin when a recipient returns a gift (box 1206). When a recipient returns the gift, the method may notify the giver in box 1208. For example, the method may provide a SMS message, an email, a telephone call, a message within a web application, or the like to notify the giver that the recipient is returning the gift. In an embodiment, the return value of the gift may be a purchase price of the gift. In another embodiment, the return value of the gift may be a value specified by the giver. The value may be a monetary amount, a number of points, or any other measurable currency. The perceived value of a product may vary depending on the currency. In yet another embodiment, the method 1200 may provide suggested values from which the giver may select a return value of the gift. For example, the suggested values may be based on a perception map of the gift recipient. The perception map may be determined according to method 300. The method may then output the return value of the gift in box 1212. For example, the output return value may be used to generate a gift card of the return value in exchange for return of the gift.
The method 1200 may optionally perform “A” responsive to a determination that a recipient is returning a gift. For example, the method may perform a gift exchange such as method 1100 to provide an opportunity for exchanging the gift.
Although the disclosure has been described with reference to several exemplary embodiments, it is understood that the words that have been used are words of description and illustration, rather than words of limitation. Changes may be made within the purview of the appended claims, as presently stated and as amended, without departing from the scope and spirit of the disclosure in its aspects. Although the disclosure has been described with reference to particular means, materials and embodiments, the disclosure is not intended to be limited to the particulars disclosed; rather the disclosure extends to all functionally equivalent structures, methods, and uses such as are within the scope of the appended claims.
While the computer-readable medium may be described as a single medium, the term “computer-readable medium” includes a single medium or multiple media, such as a centralized or distributed database, and/or associated caches and servers that store one or more sets of instructions. The term “computer-readable medium” shall also include any medium that is capable of storing, encoding or carrying a set of instructions for execution by a processor or that cause a computer system to perform any one or more of the embodiments disclosed herein.
The computer-readable medium may comprise a non-transitory computer-readable medium or media and/or comprise a transitory computer-readable medium or media. In a particular non-limiting, exemplary embodiment, the computer-readable medium may include a solid-state memory such as a memory card or other package that houses one or more non-volatile read-only memories. Further, the computer-readable medium may be a random access memory or other volatile re-writable memory. Additionally, the computer-readable medium may include a magneto-optical or optical medium, such as a disk or tapes or other storage device to capture carrier wave signals such as a signal communicated over a transmission medium. Accordingly, the disclosure is considered to include any computer-readable medium or other equivalents and successor media, in which data or instructions may be stored.
The present specification describes components and functions that may be implemented in particular embodiments with reference to particular standards and protocols, the disclosure is not limited to such standards and protocols. Such standards are periodically superseded by faster or more efficient equivalents having essentially the same functions. Accordingly, replacement standards and protocols having the same or similar functions are considered equivalents thereof
The illustrations of the embodiments described herein are intended to provide a general understanding of the various embodiments. The illustrations are not intended to serve as a complete description of all of the elements and features of apparatus and systems that utilize the structures or methods described herein. Many other embodiments may be apparent to those of skill in the art upon reviewing the disclosure. Other embodiments may be utilized and derived from the disclosure, such that structural and logical substitutions and changes may be made without departing from the scope of the disclosure. Additionally, the illustrations are merely representational and may not be drawn to scale. Certain proportions within the illustrations may be exaggerated, while other proportions may be minimized. Accordingly, the disclosure and the figures are to be regarded as illustrative rather than restrictive.
For example, operation of the embodiments of the present invention has been described in the context of servers and terminals that embody marketplace and/or product placement systems. These systems can be embodied in electronic devices or integrated circuits, such as application specific integrated circuits, field programmable gate arrays and/or digital signal processors. Alternatively, they can be embodied in computer programs that execute on personal computers, notebook computers, tablet computers, smartphones or computer servers. Such computer programs typically are stored in physical storage media such as electronic-, magnetic- and/or optically-based storage devices, where they are read to a processor under control of an operating system and executed. And, of course, these components may be provided as hybrid systems that distribute functionality across dedicated hardware components and programmed general-purpose processors, as desired.
One or more embodiments of the disclosure may be referred to herein, individually and/or collectively, by the term “disclosure” merely for convenience and without intending to voluntarily limit the scope of this application to any particular disclosure or inventive concept. Moreover, although specific embodiments have been illustrated and described herein, it should be appreciated that any subsequent arrangement designed to achieve the same or similar purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all subsequent adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the description.
In addition, in the foregoing Detailed Description, various features may be grouped together or described in a single embodiment for the purpose of streamlining the disclosure. This disclosure is not to be interpreted as reflecting an intention that the claimed embodiments require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter may be directed to less than all of the features of any of the disclosed embodiments. Thus, the following claims are incorporated into the Detailed Description, with each claim standing on its own as defining separately claimed subject matter.
The above disclosed subject matter is to be considered illustrative, and not restrictive, and the appended claims are intended to cover all such modifications, enhancements, and other embodiments which fall within the true spirit and scope of the present disclosure. Thus, to the maximum extent allowed by law, the scope of the present disclosure is to be determined by the broadest permissible interpretation of the following claims and their equivalents, and shall not be restricted or limited by the foregoing detailed description.
