Patent Publication Number: US-11640632-B2

Title: User segmentation for listings in online publications

Description:
CROSS REFERENCE TO RELATED APPLICATION 
     This application is a Continuation of U.S. patent application Ser. No. 16/123,636, filed Sep. 6, 2018, which is a Continuation of U.S. patent application Ser. No. 14/135,523 (now U.S. Pat. No. 10,089,671), filed Dec. 19, 2013, which is a Continuation of U.S. patent application Ser. No. 13/722,926 (now U.S. Pat. No. 8,635,121), filed Dec. 20, 2012, which is a Continuation of U.S. patent application Ser. No. 12/752,022 (now U.S. Pat. No. 8,364,560), filed Mar. 31, 2010, the benefit of priority of each of which is claimed hereby, and the disclosure of each of which is hereby incorporated by reference herein in its entirety. 
    
    
     TECHNICAL FIELD 
     The present application relates generally to the technical field of information management and, in one specific example, to user segmentation for listings in online publications. 
     BACKGROUND 
     Online publication systems may receive listings from users and publish those listings on a website so that they are viewable by other users. In some instances, the online publication system may comprise an online marketplace where sellers may post listings that describe items or services for sale that are viewable by users. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Some embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings in which: 
         FIG.  1    is a network diagram depicting a client-server system, within which one example embodiment may be deployed. 
         FIG.  2    is a block diagram of a segmentation engine according to an example embodiment. 
         FIG.  3    is a flow chart of an example method to prepare a listing for user segmentation according to an example embodiment. 
         FIG.  4    is a flowchart of an example method to provide a listing to a segmented user according to an example embodiment. 
         FIG.  5    is a high-level entity-relationship diagram, illustrating various tables that may be maintained, and that are utilized by and support the applications of the publication system. 
         FIGS.  6 A and  6 B  are examples of rendered listings based on a user profile. 
         FIGS.  7 A and  7 B  are further examples of rendered listings based on a user profile. 
         FIGS.  8 A and  8 B  are additional examples of rendered listings based on a user profile. 
         FIG.  9    shows a diagrammatic representation of a machine in the example form of a computer system within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. 
     
    
    
     DETAILED DESCRIPTION 
     Example methods and systems to render listings based on user segmentation in a publication system are described. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of example embodiments. It will be evident, however, to one skilled in the art that the present invention may be practiced without these specific details. 
     In an online publication system, one or more listings may be posted that are viewable by users. In some instances, the listings may describe items for sale by a seller. In various embodiments, a segmentation engine may be used to modify how a listing is rendered based on a user segmentation associated with the particular user viewing the listing. 
     The segmentation engine may associate a user with one or more profiles. The profiles may include data about the user such as demographic information such as age and sex, buying patterns, and buyer “stickiness.” Buyer stickiness, as used herein, is defined as a metric to measure a buyer&#39;s loyalty to one or more sellers. The stickiness of a buyer may be measured based on a buyer&#39;s history with a seller associated with a particular listing and/or based on the buyer&#39;s history with other merchants. 
     When a seller provides a listing to be published within the online publication system, the seller may also provide one or more rules for rendering the listing based on the profiles. Based on the rules, and the profile associated with the user, a listing is rendered for the user. In some instances, the listing may include different terms or conditions and/or highlight various features of an item for sale. For example, a sticky buyer may be offered free shipping while an infrequent buyer may have to pay for shipping. In a further example, a female buyer may be shown a listing showing the item for sale in pink while a male buyer may be shown the same item in black. 
       FIG.  1    is a network diagram depicting a client-server system  100 , within which one example embodiment may be deployed. A networked system  102 , in the example forms of a network-based marketplace or publication system, and provides server-side functionality, via a network  104  (e.g., the Internet or Wide Area Network (WAN)) to one or more clients.  FIG.  1    illustrates, for example, a web client  106  (e.g., a browser, such as the Internet Explorer browser developed by Microsoft Corporation of Redmond, Wash. State), and a programmatic client  108  executing on respective client machines  110  and  112 . 
     An Application Program Interface (API) server  114  and a web server  116  are coupled to, and provide programmatic and web interfaces respectively to, one or more application servers  118 . The application servers  118  host one or more marketplace engine(s)  120  and segmentation engine(s)  122 . The application servers  118  are, in turn, shown to be coupled to one or more databases servers  124  that facilitate access to one or more databases  126 . 
     The marketplace engine(s)  120  may provide a number of marketplace functions and services to users that access the networked system  102 . The segmentation engine(s)  122  may likewise provide a number of segmentation services and functions to users such as buyers and sellers. The segmentation engine(s)  122  may allow sellers to specify how a listing should be rendered to potential buyers based on a profile associated with the buyers for items for sale that are made available via the marketplace engine(s)  120 . While the marketplace and segmentation engines  120  and  122  are shown in  FIG.  1    to both form part of the networked system  102 , it will be appreciated that, in alternative embodiments, the segmentation engine(s)  122  may form part of a segmentation service that is separate and distinct from the networked system  102 . 
     Further, while the system  100  shown in  FIG.  1    employs a client-server architecture, the present invention is of course not limited to such an architecture, and could equally well find application in a distributed, or peer-to-peer, architecture system, for example. The various marketplace and segmentation engines  120  and  122  could also be implemented as standalone software programs, which do not necessarily have networking capabilities. 
     The web client  106  accesses the various marketplace and segmentation engines  120  and  122  via the web interface supported by the web server  116 . Similarly, the programmatic client  108  accesses the various services and functions provided by the marketplace and segmentation engines  120  and  122  via the programmatic interface provided by the API server  114 . The programmatic client  108  may, for example, be a seller application (e.g., the TurboLister application developed by eBay Inc., of San Jose, Calif.) to enable sellers to author and manage listings on the networked system  102  in an off-line manner, and to perform batch-mode communications between the programmatic client  108  and the networked system  102 . 
       FIG.  1    also illustrates a third party application  128 , executing on a third party server machine  130 , as having programmatic access to the networked system  102  via the programmatic interface provided by the API server  114 . For example, the third party application  128  may, utilizing information retrieved from the networked system  102 , support one or more features or functions on a website hosted by the third party. The third party website may, for example, provide one or more promotional, marketplace or segmentation functions that are supported by the relevant applications of the networked system  102 . 
       FIG.  2    is a block diagram of a segmentation engine  200  according to an example embodiment. The segmentation engine  200  may be the same as or similar to the segmentation engine  122  of  FIG.  1   . The segmentation engine  200  operates in conjunction with one or more marketplace engine(s)  120  in the online publication system (or the networked system  102 ) to render one or more listings for display to a user based on a profile associated with the user. 
     The parameters module  202  is to identify one or more parameters of a listing provided by a seller that may be modified by the segmentation engine  200 . Some of the parameters that may be modified include, but are not limited to, price, color, item title, item description, item picture, shipping options, warranties offered, return policy, and sale type (e.g., auction or buy it now). 
     The parameters module  202  accesses one or more options associated with each of the identified parameters. The options each correspond to a particular parameter. In some instances, two or more parameters may be associated with each other so that, based on the option associated with a particular parameter for a particular listing, another parameter associated with the particular listing may be automatically assigned to a specific option. For example, if the parameter “item color” is associated with the option “pink,” the parameter “item picture” is automatically assigned to a picture of the item in the color pink. Each parameter may correspond to an option preselected as a default option. 
     The rules module  204  provides a rules interface for a seller to provide one or more rules for rendering the listing to potential buyers. The interface may include the parameters of the parameters module  202  or some portion thereof. The portion of the parameters may be selected based on, for example, a department corresponding to the item for sale, the seller&#39;s history, a season (e.g., holidays) during which the listing is submitted, features specific to the item listed, and other listings for items for sale submitted by the same seller. 
     At least a portion of the parameters selected and the rules interface is provided to the seller to provide one or more rules for rendering the listing to a potential buyer. In some instances, the rules may be provided by the seller according to a profile of a group of users. The profiles correspond to a group of users that share one or more characteristics. The users may be grouped according to demographic information such as age and gender, and buying habits such as monthly expenditures and departments associated with the items purchased. A description of the profiles may be displayed as part of the rules interface. In some instances, only a portion of the profiles may be provided to the seller. For example, if the item for sale is in the electronics department, only profiles associated with users who regularly buy electronics may be provided. In some instances, a seller may be able to restrict certain users from accessing the listing based on a profile. For example, a wine merchant may choose to restrict users associated with a profile of people below a legal drinking age from viewing a listing describing a bottle of wine. 
     In some instances, the rules interface is configured to receive rules as “if, then, else” statements. A single statement may include additional “if, then” clauses to identify additional profiles. The statement, when completed by the seller may read, in one example, “if the buyer is associated with profile A (males age 20-25), then render the listing with image 1, if the buyer is associated with profile C (males age over 40, spends at least $100 per month), then offer a 10% discount, else render the listing with image 0 and offer no discount.” 
     In some instances, the rules module  204  may access a record of past sales and rules used to render the listings. The rules module  204  may suggest one or more rules to a seller. For example, in the department “books,” the rules engine  204  may suggest that the seller offer free shipping to profiles associated with females age 20-25 based on previous successful transactions where other sellers offered free shipping. In another instance, the rules engine  204  suggests providing a warranty to buyers who associated with a profile that corresponds to “sticky” users who frequently make repeat purchases from the same seller. 
     A user behavior module  206  collects data about one or more potential buyers such as demographic data, purchasing data, and stickiness data. The user behavior module  206  may store the data in a profile database  208 . In the profile database  208 , the user behavior data may be stored according to one or more profiles. For example, a first profile may be associated with males age 20-25, a second profile may be associated with females age 20-25, and a third profile may include males above age 40 and that spend at least $100 per month. A user may belong to one or more profiles. For example a user may belong to the first profile (males age 20-25) and to another profile (people who spend more than $100 per month on video games and accessories). 
     A seasonal module  210  is to access seasonal data that may further be used to render the listing. The seasonal data may identify a particular period as being associated with a particular holiday. For example, November 1 to December 24 may be identified as a “Holiday Shopping Season” including holidays such as Christmas, Chanukah, Kwanzaa, and the winter solstice. For listings to be rendered during this period of time, a seller may provide rules for rendering the listing in accordance with a particular tradition. For example, a seller may wish to provide a “Christmas discount” to users associated with particular profiles for listings of nativity scenes and to provide a “Chanukah discount” to users associated with other profiles for listings of menorahs. 
     Alternatively or additionally, a profile associated with a buyer may indicate a seasonal tradition observed by the buyer. For example, a “Profile C” may indicate that the buyer celebrates Christmas while a “Profile K” indicates that the buyer celebrates Kwanzaa. Using the rules module  204  in conjunction with the seasonal module  210 , the seller may, for example, specify that buyers associated with “Profile C” be offered guaranteed shipping before Christmas Day (December 25th) and the buyers associated with “Profile K” be offered guaranteed shipping before the first day of Kwanzaa (December 26th). 
     A rendering module  212  is to render a listing to a user based on a profile associated with the user and the seller&#39;s rules. In response to a query or other browsing activity, the rendering module  212  may render one or more listings to be displayed to the user. When rendering more than one listing (e.g., in a results list in response to a query) the rendering module  212  may access rules associated with more than one seller. 
       FIG.  3    is a flow chart of an example method  300  to prepare a listing for user segmentation according to an example embodiment. The method  300  may be performed when a listing is received from a seller, in a step  302 . Alternatively or additionally, the method may be performed some period of time after a listing has been submitted. 
     When the listing is received from the seller, the seller may associate the listing and/or an item for sale described in the listing with a product description in a catalog. The product description may describe a mass-produced or fungible product having standard features and characteristics. 
     In a step  304 , one or more parameters in the listing are identified. The parameters may include, but are not limited to: price, shipping options, warranty, product description, product image, and a background graphic or color. The parameters may each be associated with one or more options including a default option that may be provided by (or selected by) the seller. For example, the price parameter may be associated with a default option such as “no discount” and with additional options such as “10% discount,” “$10 discount,” or a new price. 
     In a step  306 , a determination is made that the seller has previously submitted other listings that describe similar items. The similar items are substantially similar items that differ from the present listing by a feature such as size, color, seasonal edition, or the like. 
     In a step  308 , where the seller has previously listed a plurality of similar listings, one or more product features (such as color, model number, size, etc.) may be identified as parameters. To illustrate, if a seller submits a first listing describing a sweater in blue and submits a second listing describing the same sweater in pink, the parameter “product color” may be identified and associated with the options “blue” and “pink.” 
     In a step  310 , rules associated with the identified parameters are received from the seller based on user profiles. The rules indicate that when the listing is provided to a potential buyer, if the potential buyer is associated with a certain user profile, that the listing be modified in a certain way. For example, a seller may specify that users belonging to a “Profile A” be shown a listing that offers free shipping and that users belonging to a “Profile B” be shown a listing having a different background. In some instances, the seller may specify that certain profiles be shown an alternative listing. For example, a seller may specify potential buyers associated with a “Profile TW” (including teenage women) be shown a separate listing for a similar item (identified in step  308 ) in another color, e.g., pink. 
     In some embodiments, a seller may maintain one of more sets of rules that were previously provided. The seller may then select the desired set of rules when submitting a listing or provide a new set of rules. A seller may be able to specify a default set of rules that is applied to each new listing if no other set of rules is specified. In some instances, the seller may submit rules to be applied to more than one listing. 
       FIG.  4    is a flowchart of an example method  400  to provide a listing to a segmented user or potential buyer according to an example embodiment. In the method  400 , the user has previously been associated with one or more profiles based on demographic information, buying history and other information known about the user. 
     In a step  402 , user activity is received via a user interface. The user activity may be submission of a query, navigation within a product hierarchy or catalog provided by the online publication system, or the like. Based on the user activity, one or more listings to be provided to the user are identified in a step  404 . 
     In a step  406 , at least one profile of the user is accessed. The profile may be previously associated with the user and stored as part of a user account or may be determined once the user activity has been received. The profiles may be associated with a user according to department. For example, when a listing is identified in the step  404 , the listing may be associated with a particular department such as shoes. A user may be associated with a first profile for the department “shoes” and other profiles for other departments. The first profile is selected from the other profiles based on the identified listing being also associated with the department “shoes.” 
     In a step  408 , the rules from the seller associated with the identified listing are accessed. In some embodiments, only the portion of the rules that are associated with the particular profile of the user are accessed. 
     In a step  410 , the parameters of the listing are modified based on the rules of step  408  and the profile of step  406 . Alternatively, the parameters may be generated, instead of modified, based on the rules and profile. In a step  412 , the listing is rendered or otherwise provided to the user based on the rules and the profile. 
       FIG.  5    is a high-level entity-relationship diagram, illustrating various tables  500  that may be maintained within the databases  126 , and that are utilized by and support the engines  120  and  122 . A user table  502  contains a record for each registered user of the networked system  102 , and may include identifier, address, profiles, and financial instrument information pertaining to each such registered user. A user may operate as a seller, a buyer, or both, within the networked system  102 . In one example embodiment, a buyer may be a user that has accumulated value (e.g., commercial or proprietary currency), and is accordingly able to exchange the accumulated value for items that are offered for sale by the networked system  102 . 
     A profile table  504  contains a record of each profile that may be associated with one or more users. The profile table  504  may include records indicating the users associated with each profile. 
     The tables  500  also include an items table  506  in which are maintained item records for goods and services that are available to be, or have been, transacted via the networked system  102 . Each item record within the items table  506  may furthermore be linked to one or more user records within the user table  502 , so as to associate a seller and one or more actual or potential buyers with each item record. 
     A parameters table  508  includes data relating to each listing that is changeable based on the profiles within the profile table  504 . 
     A seller table  510  contains a record for each seller within the networked system  102 . The seller table  510  may relate each item within the items table  506  to a specific seller of the sellers in the networked system  102 . 
     A rules table  512  includes rules received from the seller for each listing (each listing may be recorded in the items table  506  or in another table (not shown)). The rules table  512  may be accessed along with the parameters table  508  to render a listing based on the profile of the user. 
     A department table  514  may be included and may contain information relating to department-specific profiles and/or parameters. The department table  514  may further link to listings describing similar listings in the same department to provide additional parameters. For example, the department table  514  may include an indication that the seller has provided a first listing of a sweater in the color blue and a second listing of the same sweater in pink within the department “clothing.” In these instances, the parameter “color” may be included in the parameters table  508  for both the sweaters. 
       FIGS.  6 A and  6 B  are examples of rendered listings based on a user profile.  FIG.  6 A  depicts a default or unmodified listing for an “Apple iPod Touch 8 GB WiFi Video MP3 MB528LL 2nd Gen.” The listing includes a price of $183.89 with no indication of a discount or free shipping. The listing of  FIG.  6 B , while describing the same item being offered by the same seller, indicates that the user is eligible for free shipping and a special price of $173.89. The listing of  FIG.  6 B  is generated based on the rules submitted by the seller and the profile of the user. 
       FIGS.  7 A and  7 B  are further examples of rendered listings based on a user profile for the listing shown in  FIG.  6 A . The rendered listing in  FIG.  7 A  includes the additional description of “Play your favorite games!” and may be rendered based on demographic information of a profile associated with the user. For example, the profile associated with the user viewing the listing of  FIG.  7 A  may be “males, age 18-27.” 
       FIG.  7 B  depicts another rendering of the same listing that is rendered based on another profile. In this instance, the same seller has another listing for the same item in another color (pink). For profiles associated with a demographic “women age 18-21,” the listing of  FIG.  7 B  shows the item “Apple iPod Touch 8 GB WiFi Video MP3 MB528LL 2nd Gen” in the color pink and includes the additional description “In Pink! Shop from your phone!” It is noted that the listing of  FIG.  6 A  may be modified or the listing associated with the item in pink may replace the listing of  FIG.  6 A . 
       FIGS.  8 A and  8 B  are additional examples of rendered listings based on a user profile. The listing of  FIG.  8 A  may be an unmodified or default listing and/or may be associated with one or more profiles of user. The listing of  FIG.  8 A  indicates that shipping is $24.99 and that no returns are accepted. In contrast, based on a user profile and rules provided by the seller, the listing of  FIG.  8 B  includes the additional parameters “free shipping” and “Returns: Within 30 days.” Additionally, the listing of  FIG.  8 B  includes a modified (discounted) price of $173.89. Based on the rules provided by the seller, the listing of  FIG.  8 B  may be rendered to “sticky” buyers who are more likely to purchase additional items from the seller in the future. 
       FIG.  9    shows a diagrammatic representation of machine in the example form of a computer system  900  within which a set of instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a server computer, a client computer, a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein. 
     The example computer system  900  includes a processor  902  (e.g., a central processing unit (CPU) a graphics processing unit (GPU) or both), a main memory  904  and a static memory  906 , which communicate with each other via a bus  908 . The computer system  900  may further include a video display unit  910  (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). In some instances, the video display unit  910  may be a touch screen for receiving input from a user. The computer system  900  also includes an alphanumeric input device  912  (e.g., a keyboard), a cursor control device  914  (e.g., a mouse), a disk drive unit  916 , a signal generation device  918  (e.g., a speaker) and a network interface device  920 . 
     The disk drive unit  916  includes a machine-readable medium  922  on which is stored one or more sets of instructions (e.g., software  924 ) embodying any one or more of the methodologies or functions described herein. The software  924  may also reside, completely or at least partially, within the main memory  904  and/or within the processor  902  during execution thereof by the computer system  900 , the main memory  904  and the processor  902  also constituting machine-readable media. 
     The software  924  may further be transmitted or received over a network  926  via the network interface device  920 . 
     While the machine-readable medium  922  is shown in an example embodiment to be a single medium, the term “machine-readable medium” should be taken to include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more sets of instructions. The term “machine-readable medium” shall also be taken to include any medium that is capable of storing, encoding or carrying a set of instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present invention. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, optical and magnetic media, and carrier wave signals. 
     Thus, a method and system to segment users for listings in online publications have been described. Some technical problems that the present invention may be used to solve include more efficient data base management, reducing a number of operations performed on a database, and more efficient delivery of information to one or more users based on user characteristics. Although the present invention has been described with reference to specific example embodiments, it will be evident that various modifications and changes may be made to these embodiments without departing from the broader spirit and scope of the invention. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense. 
     The Abstract of the Disclosure is provided to comply with 37 C.F.R. § 1.72(b), requiring an abstract that will allow the reader to quickly ascertain the nature of the technical disclosure. It is submitted with the understanding that it will not be used to interpret or limit the scope or meaning of the claims. In addition, in the foregoing Detailed Description, it can be seen that various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of 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 lies in less than all features of a single disclosed embodiment. Thus the following claims are hereby incorporated into the Detailed Description, with each claim standing on its own as a separate embodiment.