Patent Application
20080097772
Embodiments illustrated by way of example and not limitation in the figures of the accompanying drawings, in which:
A computer-implemented system and method for automatic disposition of referrals in an online marketplace are disclosed. In the following description, numerous specific details are set forth. However, it is understood that embodiments may be practiced without these specific details. In other instances, well-known processes, structures and techniques have not been shown in detail in order not to obscure the clarity of this description.
As described further below, according to various example embodiments of the disclosed subject matter described and claimed herein, there is provided a system and method for automatic disposition of referrals in an online marketplace. The system includes a referral receiver operable to receive a referral, the referral including referral information identifying a referred party, the referral receiver being further operable to obtain referred party information related to the referred party. The system further includes a referral disposition engine being operable to use the referral information and the referred party information to automatically produce a disposition for the referral. Various embodiments are described below in connection with the figures provided herein.
Referring to
Using one of a variety of network connection means, server computer 100 can communicate with client computers 150 using conventional means. In a particular implementation of this network configuration, a server computer 100 may operate as a web server if the Internet's World-Wide Web (WWW) is used for wide area network 110. Using the HTTP protocol and the HTML coding language across wide-area network 110, web server 100 may communicate across the World-Wide Web with clients 150. In this configuration, clients 150 use a client application program known as a web browser such as the Internet Explorer™ published by Microsoft Corporation of Redmond, Wash., the user interface of America On-Line™, or the web browser or HTML renderer of any other supplier. Using such conventional browsers and the World-Wide Web, clients 150 may access image, graphical, and textual data provided by web server 100 or they may run Web application software. Conventional means exist by which clients 150 may supply information to web server 100 through the World Wide Web 110 and the web server 100 may return processed data to clients 150.
Having briefly described one embodiment of the network environment in which an example embodiment may operate,
An optional data storage device 228 such as a magnetic disk or optical disk and its corresponding drive may also be coupled to computer system 200 for storing information and instructions. Computer system 200 can also be coupled via bus 216 to a display device 204, such as a cathode ray tube (CRT) or a liquid crystal display (LCD), for displaying information to a computer user. For example, image, textual, video, or graphical depictions of information may be presented to the user on display device 204. Typically, an alphanumeric input device 208, including alphanumeric and other keys is coupled to bus 216 for communicating information and/or command selections to processor 220. Another type of user input device is cursor control device 206, such as a conventional mouse, trackball, or other type of cursor direction keys for communicating direction information and command selection to processor 220 and for controlling cursor movement on display 204.
Alternatively, the client 150 can be implemented as a network computer or thin client device. Client 150 may also be a laptop or palm-top computing device, such as the Palm Pilot™. Client 150 could also be implemented in a robust cellular telephone, where such devices are currently being used with Internet micro-browsers. Such a network computer or thin client device does not necessarily include all of the devices and features of the above-described exemplary computer system; however, the functionality of an example embodiment or a subset thereof may nevertheless be implemented with such devices.
A communication device 226 is also coupled to bus 216 for accessing remote computers or servers, such as web server 100, or other servers via the Internet, for example. The communication device 226 may include a modem, a network interface card, or other well-known interface devices, such as those used for interfacing with Ethernet, Token-ring, or other types of networks. In any event, in this manner, the computer system 200 may be coupled to a number of servers 100 via a conventional network infrastructure such as the infrastructure illustrated in
The system of an example embodiment includes software, information processing hardware, and various processing steps, which will be described below. The features and process steps of example embodiments may be embodied in articles of manufacture as machine or computer executable instructions. The instructions can be used to cause a general purpose or special purpose processor, which is programmed with the instructions to perform the steps of an example embodiment. Alternatively, the features or steps may be performed by specific hardware components that contain hard-wired logic for performing the steps, or by any combination of programmed computer components and custom hardware components. While embodiments are described with reference to the Internet, the method and apparatus described herein is equally applicable to other network infrastructures or other data communications systems.
Various embodiments are described herein. In particular, the use of embodiments with various types and formats of user interface presentations and/or application programming interfaces may be described. It will be apparent to those of ordinary skill in the art that alternative embodiments of the implementations described herein can be employed and still fall within the scope of the claimed invention. In the detail herein, various embodiments are described as implemented in computer-implemented processing logic denoted sometimes herein as the “Software”. As described above, however, the claimed invention is not limited to a purely software implementation.
The referral can be a structured data object, such as a web form or an email form with defined data fields and enumerated value selections. The referral source can select from the various value options provided for each field. In other embodiments, a less structured referral can be provided as a group of free text fields that can be scanned for keywords and converted to a structured data object using well known techniques. In these various embodiments, the identity of the referral source, if provided, can be extracted from the referral. Similarly, the identity of the referred party, if provided, can also be extracted from the referral.
Referring now to
Once a policy is matched to the referral 510 by the policy engine 610, the selected policy is provided to consequence package engine 620. The consequence package engine 620 assigns a consequence package to the referral 510 based on the selected policy. For example,
Once the consequence package engine 620 assigns a consequence package to the referral 510, the actions defined by the assigned consequence package can be automatically performed leading to disposition 630 of the referral 510. Alternatively, the actions defined by the assigned consequence package may require that at least one step be performed manually by a customer service representative (CSR) 627. In this case, the consequence package and the referral can be provided to CSR 627. The CSR 627 can perform any required manual steps and then other steps defined by the assigned consequence package can be automatically performed leading to disposition 630.
As shown in
Policy generator 615 can be used to create a variety of policies to automatically handle a variety of referrals. Each policy so generated can be identified with a unique policy name or number and stored for ready access by the policy engine 610. A particular policy can be created to parse the information obtained and aggregated by data gatherer component 605. For example, the policy generator 615 can analyze the attributes and behaviors of the party(s) identified in the referral to determine if there has been a demonstrable change in status or behavior that may indicate a potential problematic or fraudulent use of an online marketplace account. The generated policy can perform this automated analysis, generate specific dataset and reports, and automatically recommend actions to be performed in response to the information in the referral and the other information aggregated by data gatherer component 605. The actions to be taken as automatically recommended by the policy are defined as consequence packages generated by the consequence package generator 625.
Consequence package generator 625 is typically used by a marketplace host system administrator to create or modify the system consequence packages that are used to respond to processed referrals. In one embodiment, consequence packages can be implemented as a set or rules or processing steps that can be automatically executed when triggered by an associated policy. Each created consequence package can include a specification of the events, data values, parameters, system status, time of day or date, and the like necessary to trigger the execution of the consequence package. Each consequence package can also include additional configurable consequence package triggering parameters that can be used to selectively vary a threshold at which the consequence package will be triggered. In this manner, one or more configurable consequence package triggering parameters can be selectively modified at run time to change the point at which the consequence package is triggered. Each consequence package so generated can be identified with a unique consequence package name or number and stored for ready access by the consequence package engine 620.
Consequence package generator 625 can be used to create a variety of consequence package to automatically handle a variety of referrals. The consequence package essentially defines the set of actions to perform in support of the policy triggered for a particular incoming referral. For example, a particular consequence package could include a rule as simple as automatically generating and sending an email to a pre-defined recipient when an associated policy is triggered. As such, a particular policy can include an identity of one or more consequence packages to execute upon the triggering of the related policy. As another example, a particular consequence package could include a rule that would refer the matter to a human CSR 627 for manual processing of the referral. Because each consequence package includes configurable consequence package triggering parameters, the one or more configurable consequence package triggering parameters can be selectively modified at run time to change the point at which the consequence package is triggered. In this manner, for example, the online marketplace can be quickly reconfigured at runtime to refer most or all matters to a human CSR 627 for manual processing of the referral if conditions in the online marketplace warrant such action. This way, the processing of referrals in the online marketplace can be quickly and configurably switched between an automatic or manual referral processing mode.
Because the process in various embodiments of selecting a policy associated with an input referral and then selecting a consequence package associated with the selected policy can be completely automated, the related sending of notifications related to the disposition of the referral can also be automated. For example, the referral source as identified in the referral and/or the referred party, if identified in the referral, can be automatically notified of the submittal, processing, and disposition of a related referral. This automatic notification (e.g. email, fax, instant message, automated voicemail, page, etc.) happens automatically and does not need to involve any Customer Support time or manual processing. For example, the notification to the User/Member can specify the policy that the party may have violated
As described above, various embodiments can automatically process referrals by selecting one or more policies and one or more consequence packages for disposing of a particular referral. In a similar fashion, multiple referrals can be aggregated into a single mass referral unit and disposed together as a mass referral unit. Further, duplicate or substantially similar referrals can be reduced to one or more fewer referrals to reduce the processing time in handling multiple duplicate referrals. In one example, multiple referrals may have been originated by the same referral source or may have originated from the same set of circumstances. In this case, the multiple similar referrals are collected over a given pre-determined time period as specified in a pre-defined policy. Upon the expiration of a pre-configured time period or referral quantity, the collected multiple referrals are aggregated into a single mass referral unit and a pre-defined consequence package is selected to process a set of actions associated with the mass referral unit. As described above, the set of actions defined by the consequence package may be one or more actions that would be available for disposing of a single referral. For example, a single email message can be sent to a pre-defined recipient as an action associated with the disposition of the mass referral unit. In another example, the mass referral unit can be forwarded to a human CSR 627 for manual processing as a mass referral unit. In this manner, the CSR 627 can manually dispose of multiple referrals in a single review and disposition step. In this way, CSR 627 efficiency and accuracy is greatly improved through the process of Mass Review in various embodiments. This essentially groups a series of similar online marketplace host Sellers/Users, for example, into one Mass Review case enabling a CSR 627 to quickly take action on all the online marketplace host Sellers/Users in that Mass Review case. Again, the various embodiments build all the proof and gather all the necessary information using the data gatherer 605 prior to presenting all the relevant aggregated data to the CSR 627 in such a way that the only thing that the CSR 627 has to do is make a decision without spending time on proof building or investigation.
As described above, various embodiments can automatically process referrals by selecting one or more policies and one or more consequence packages for disposing of a particular referral. Given the information from the input referral and the disposition produced for the related referral, data can be generated to identify correlations between the input referral and the resulting disposition. For example, a specific referral source (as identified in the referral) may be particularly accurate in submitting referrals the lead to a particular disposition result. Over time and with the collection of a set of historical data, a correlation can be drawn between the specific referral source and the resulting disposition. In the processing of subsequent referrals from the specific referral source for which correlation data has been collected, the processing of the referral can be streamlined or dispatched more quickly using the correlation data rather than processing the referral normally in a less timely fashion. Over time, the correlation data can be used to identify specific referral sources that represent the “top reporters” and for whom referrals can be processed more quickly. In another example, a specific referred party can be identified as a “frequent offender”, if the correlation data can be used to identify the specific referred party as being the object of several referrals that lead to a particular disposition. In another example, the result of appeals that may be handled in response to the disposition of a referral may also be factored into the correlation data. The referral, the disposition of the referral, and any appeal related to the referral may all be correlated to improve the speed and accuracy of the automated referral processing system of various embodiments. In general, the referral correlation data can be used to make the automatic referral processing operation more efficient over time as a greater wealth of historical, referral disposition, and referral appeal information is collected.
Referring now to
As shown in
Thus, computer-implemented system and method for automatic disposition of referrals in an online marketplace are disclosed. While the present invention has been described in terms of several example embodiments, those of ordinary skill in the art will recognize that the present invention is not limited to the embodiments described, but can be practiced with modification and alteration within the spirit and scope of the appended claims. The description herein is thus to be regarded as illustrative instead of limiting.
