Patent Application
20060265429
1. Field of the Invention
The present invention relates to the field of computerized inventory systems, such as hotel reservations systems or other product and/or service reservation or inventory systems, which are used to determine and relay data related to products and/or services from selected product providers to customers. More particularly, the present invention relates to identification of trends in transactional activity between selected users and selected transaction systems so as to prioritize communications between selected users and transaction systems so as to focus limited marketing and communication resources on users and transaction systems exhibiting a selected trend.
2. Description of Related Art
Many of today's products and services are catalogued in computerized reservation or inventory systems. These systems may include simple or complex methodologies for maintaining inventory and providing product and/or service availability information. Either via direct access or remote access across a network, consumers can run queries and view availability information for selected products and/or services, as well as purchase or reserve such items. One example of such systems is a computerized reservation system (CRS). A CRS provides a communications network for travel agents and other consumers to access travel related information such as airline tickets, hotel reservations, car rentals, event tickets, leisure activities, etc. CRS systems have been in existence for a long period of time. Some of the current CRS systems are known or referred to under the following trade names and services marks: SABRE, AMADEUS, WORLDSPAN, SYSTEM ONE, APOLLO, GEMINI, GALILEO, and AXESS.
Consumer interaction with such systems has become more complex in recent years, thus introducing a host of technical problems related to the tracking of trends in transactions occurring via search systems that may be in communication with one or more CRS entities, a plurality of users, and individual product providers. Users may now interrogate multiple CRS entities via websites hosted by search systems that are configured to search for low-cost product options on a variety of CRS systems. For example, there exists a search system configured to provide a plurality of low airline fare prices and different flight itinerary options from various CRS entities for a given departure and return date combination entered by a user, thereby allowing a user to view these different options and make a determination as to which fare and flight itinerary meets their goals. Such a system is described more fully in U.S. Provisional Patent Application Ser. No. 60/573,546, filed on May 21, 2004, entitled, Systems, Methods, And Computer Program Products For Searching And Displaying Low Cost Product Availability Information For A Given Departure-Return Date Combination Or Range Of Departure-Return Date Combinations; the contents of which are incorporated herein. Such systems may also allow the user to search alternate computerized reservation systems hosted by individual hotels, hotel chains, airlines, or other product providers such that the user may initiate a variety of different transactions with one or more product providers via the search system.
In addition, third-party affiliates, such as “hotel guide” websites, now commonly offer search capabilities to individual customers for affordable hotel accommodations or other products by serving as “users” of the search system. Such third-party affiliates typically receive customer search requests and other transactions and subsequently pass on such search requests (as a user) to a search system that may then fully interrogate one or more CRS entities in response to the search request. In some cases, the third-party affiliate may also purchase a product (via the search system) from a product provider listed in the CRS in response to a customer input. Since many conventional search systems do not market to hotels, hotel chains, small airlines, or other individual product providers, third party affiliates often provide critical marketing services to the operators of such search systems and may assist both individual customers and search systems in obtaining more competitive product prices from the product providers by assuring a steady flow of individual customers to purchase the offered products.
While conventional search systems may provide an individual customer (either directly or via a third party affiliate) with a multitude of different product options including, in some cases, the lowest possible price for a given product at the time of the search, conventional search systems do not automatically identify and report trends in transactional activity between users (including third party affiliates) and product providers (such as an individual hotel). This technical problem is especially apparent in conventional search systems that may at least partially rely on third party affiliates for marketing efforts aimed at both individual customers and product providers. For example, conventional search systems lack the capability of automatically tracking and reporting trends in transactional activity between users (including both individual customers and third party affiliates) and product providers (which may include, for example, hotel CRS entities, and hotel chain CRS entities). Thus, the operator of the search system may not be aware of a product provider or a third-party affiliate that is exhibiting a rapid increase or decrease in transactions that may be due to a number of situations that may require the attention of the operator of the search system. For example, a third party affiliate exhibiting a rapid rise in transactional activity in a relatively short period of time may be engaging in risky internet marketing tactics such as “keyword stuffing” that may result in the third party affiliate being dropped as an internet site searched by large internet search engines. In another example, a steady marked decrease in transactional activity by a selected third party affiliate may indicate that the entity may be taking its business to another competing search system. In these and other examples, conventional search systems are incapable of automatically tracking and reporting such transactional trends to the operator of the search system. Thus, the operator of conventional search systems would be incapable of addressing such issues with third party affiliates or providing incentives for other product providers that may be exhibiting gradual upward transactional trends that may indicate prudent and successful marketing strategies.
Therefore, there exists a need for an improved system to solve the technical problems outlined above that are associated with conventional search systems. More particularly, there exists a need for a system configured to be capable of monitoring a product database to identify trends in transactional activity between a plurality of product providers and users of the product database such that an operator of the system may more effectively identify users (such as third party affiliates) and/or product providers that are exhibiting a rapid rise or fall in transactional acitivity over a selected number of time periods. There also exists a need for such a system that automatically generates a list of third party affiliates and product providers exhibiting a selected upward or downward trend in the number of transactions occuring over the selected number of time periods by automatically comparing a number of transactions determined during a selected time period to an average number of transactions historically recorded during a comparable time period and averaged over a selected number of time periods.
The needs outlined above are met by the present invention which, in various embodiments, also provides a system that overcomes many of the technical problems discussed above, as well other technical problems, with regards to monitoring a product database to identify trends in transactional activity between a plurality of product providers and a plurality of users (including third party affiliates) over a selected number of time periods. More specifically, the system of the present invention comprises, in one embodiment, at least one transaction system capable of performing transactions and a tracking system in communication with the transaction system. Furthermore, the tracking system tracks the number of transactions made by the transaction system for different time periods, determines an average number of transactions for the transaction system based on the transactions over different time periods, and compares the average number of transactions to the number of transactions for a selected time period to identify a trend in the number of transactions for the selected time period. For example, according to one embodiment, the tracking system determines the avearage number of transactions for an N number of time periods and the number of transactions for an N+1 time period and compares the average number of transaction for the N number of time periods to the number of transactions for the N+1 time period.
According to other system embodiments of the present invention the tracking system compares the transactions for successive time periods to the average number of transactions, wherein the comparisons define a slope. In other system embodiments, the tracking system applies a scaling factor to the determined slope wherein the scaling factor has a value that is dependent on the duration of the time periods. In other system embodiments, the tracking system determines a trend value representing the number of transactions for a selected time period for a plurality of transaction systems, and identifies at least one of transaction systems having upward trends and transaction systems having downward trends. Furthermore, the tracking system may identify transaction systems exhibiting identified upward or downward trends that exceed a threshold value.
The present invention also includes methods and computer program product embodiments for identifying trends in transactional activity of one or more transaction systems. The methods and computer program products comprise the steps of: providing at least one transaction system capable of performing transactions; tracking the number of transactions made by the transaction system for different time periods; determining an average number of transactions for the transaction system based on the transactions over different time periods; and comparing the average number of transactions to the number of transactions for a selected time period to identify a trend in the number of transactions for the selected time period. In some method and computer program product embodiments, the determining step further comprises determining the avearage number of transactions for an N number of time periods and the number of transactions for an N+1 time period. Furthermore, the comparing step further comprises comparing the average number of transaction for the N number of time periods to the number of transactions for the N+1 time period.
According to other method and computer program product embodiments, the method may further comprise comparing the transactions for successive time periods to the average number of transactions, wherein the comparisons define a slope. In some method embodiments, the method may further comprise applying a scaling factor to the determined slope wherein the applied scaling factor may be assigned a value that is dependent on the duration of the time periods (so as to allow for the emphasis of slopes computed using time periods of a selected duration). Furthermore, in some embodiments, the comparing step further comprises comparing the trend value for each transaction system to a first threshold value and identifying transaction systems having an associated trend value at least as great as the first threshold. Furthermore, the comparing step may also comprise comparing the trend value for each transaction system to a second threshold value, and identifying transaction systems having an associated trend value less that the second threshold.
Thus the systems, methods, and computer program products for identifying trends in transactional activity of one or more transaction systems provide a number of advanatages and solutions to the technical problems inherent in conventional search systems. Such advantages include, but are not limited to: providing a transactional tracking system such that an operator of a search system may be kept informed of transactional trends involving transaction systems, users (including, for example, third party affiliates), and product providers that utilize the transaction system or systems for hosting transactions, alerting an operator of the search system of transactional trends that may warrant attention to correct and/or incentivize certain business practices by transaction systems, users and/or product providers, identifying “rising stars” and/or “falling stars” within the ranks of third party affiliates that may substantially affect the business success of a particular search system, and allowing operators of the search system to fine tune the trend identification capabilities of the search system such that both long-term and short-term transactional trends may be accurately identified and tracked.
These advantages and others that will be evident to those skilled in the art are provided in the system, method, and computer program product of the present invention.
Having thus described the invention in general terms, reference will now be made to the accompanying drawings, which are not necessarily drawn to scale, and wherein:
The present inventions now will be described more fully hereinafter with reference to the accompanying drawings, in which some, but not all embodiments of the invention are shown. Indeed, these inventions may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will satisfy applicable legal requirements. Like numbers refer to like elements throughout.
The various aspects of the present invention mentioned above, as well as many other aspects of the invention are described in greater detail below. While the systems, methods, and computer program products of the present invention are described in a hotel reservation environment, it should be understood that this is only one non-limiting example of the possible use of the embodiments of the present invention. More specifically, the system, method, and computer program product embodiments of the present invention may be adapted to any number of products and services and are not limited to the monitoring of transactional trends between users (including both individual users and third-party affiliates) and a product source system offering low-price hotel accommodations. For example, the present invention may be used to automatically monitor transactional trends between users and product providers providing various products that may include, but are not limited to, travel tickets, cruises, restaurants, car rentals, sports events, and leisure activities.
The descriptions below disclose use of present invention to analyze product provider systems, such as inventory systems. It is understood that the present invention can be used in any system that handles transactions. A product provider system is a type of transaction system. Thus, the present invention is not limited to product provider systems. It has applicability in all types of transaction systems.
Thus, individual users 18 may access the the various product options either directly via a product source system 16 (such as a computerized reservation system listing low-cost travel products offered by a variety of product providers via its own internet website) or via a third-party affiliate 18a operating its own internet website (such as a low-cost hotel booking service) that in turn brings individual user 18 queries to the usually larger and more comprehensive product source system 16 that may be operated by a travel company, hotel chain, airline, or other entity specializing in presenting a variety of product options provided by various product providers. According to various embodiments, and as shown generally in
As shown in
The processor 20 of the transaction data tracking system 12 may be configured to determine the product provider or user 18a associated with the transaction initiated, and to determine a number of transactions between at least one of the plurality of users and at least one of the plurality of product providers during a selected time period (such as a day, week, month, or travel season). For example, in cases where the user 18a is a third-party affiliate, the transaction data tracking system 12 may identify the specific third-party affiliate 18a that initiated the transaction so as to track the business traffic provided by various third-party affiliates 18a that may serve as users of the product source system. Thus, the transaction data tracking system 12 of the present invention may be capable of identifying particularly profitable third-party affiliates 18a and/or specific product providers whose products are listed via the product source system 16. The processor 20 may also be capable of storing transaction information, including the determined number of transactions between the at least one of the users 18, 18a and at least one of the plurality of product providers, in a first data set in the memory device 22.
According to some embodiments of the system 10, the processor 20 periodically computes an average number of transactions between at least one of the users 18, 18a and at least one of the plurality of product providers during a selected time period (such as an “average” week) by computing an average number of transactions per the selected time period over the course of a selected number of time periods. For example, the processor 20 may determine the number of transactions between the users 18, 18a and a particular hotel chain (or other product providers) per week over a selected number of weeks in order to determine the average number of transactions occurring between users 18, 18a and the particular product provider during an average one-week time period. In a similar manner, the processor 20 may determine the number of transactions between specific third-party affiliates 18a and the product source system 16 per week over a selected number of weeks in order to determine the average number of transactions initiated by a particular third-party affiliate 18a during a typical one-week time period do determine the average amount of transactional activity initiated by a particular third-party affiliate 18a during an average time period. In addition, the transaction data tracking system 12 may be further configured to store (via the memory device 22, for example) an average number of transactions per week received by a given product provider or initiated by a particular third party affiliate 18a during both peak season (such as during the summer months or other peak travel season) as well as the average number of transactions per week during an off-season interval. Furthermore, in order to identify trends in the number of transactions occuring between users and a selected product provider (such as a particular hotel or hotel chain), as well as trends in the number of transactions initiated by a particular third-party affiliate 18a, the processor 20 of the transaction data tracking system 12 periodically compares the average number of transactions per the selected time period to the determined number of transactions stored in the first data set within a data cache 30 of the memory device 22. Thus, the transaction data tracking system may be capable of identifying particular product providers (and third-party affiliates 16a) that are exhibiting significant increases or decreases in transactional activity over the course of a selected number of time periods.
Also, as shown generally in
According to some embodiments the processor 20 of the transaction data tracking system 12 determines a slope of a component trend in the number of transactions occuring between users 18, 18a and at least one of the plurality of product providers during the selected time period. The component trend (F[X], shown, for example, as equation (2), below) may be defined as a component of the trend (FR[X], shown, for example, as equation (5) below) in the number of transactions occuring between users and a selected product provider (such as a particular hotel or hotel chain). The component trend (F[X]) may also be defined as a component of trends (FR[X], for example) in the number of transactions initiated by a particular third-party affiliate 18a. In other words, the component trend (F[X]) may be used in the determination of the trend (FR[X]) as indicated in equation (5) below. For example, the processor 20 may be capable of determining a slope that may be defined as a percentage increase (corresponding to a positive slope) or a percentage decrease (corresponding to a negative slope) in the determined number of transactions as compared to the determined number of transactions for the particular product provider during a corresponding time period ending some time before the selected time period. In addition, the processor 20 may also be capable of determining a percentage increase (corresponding to a positive slope) or a percentage decrease (corresponding to a negative slope) in the determined number of transactions during the selected time period as compared to the determined number of transactions initiated via a particular third-party affiliate 18a during the earlier corresponding time period. For example, the slope (S) of such a component trend may be defined as:
S=(N[0]+N[−1])/N[−1] (1)
Wherein N[0] is the number of transactions determined during the selected time period (such as the present week) and [N−1] is the number of transactions determined during the corresponding earlier time period (such as the week prior to the present week). Thus, the slope (S), may be defined in this example as the percentage increase (or decrease) in the number of transactions occurring between a particular user 18, 18a and a particular product provider over the course of two consecutive weeks.
Furthermore, according to some embodiments, the processor 20 of the transaction data tracking system 12 may be capable of determining a difference between the determined number of transactions and the average number of transactions over a selected number of time periods (such as a selected number of days, weeks, or months). The “selected time period” and/or the “selected number of time periods” may be adjusted by an operator of the system 10 of the present invention such that the slope may indicate a percentage increase or decrease and/or an overall increase or decrease (as compared to the average number of transactions determined by the transaction data tracking system 12) for a variety of different time periods, including daily, weekly, monthly, or any other selected time period.
In other embodiments of the system 10 of the present invention, the processor 20 of the transaction data tracking system 12 may be further configured to be capable of applying a scaling factor (K) to the determined slope (as defined above and shown, for example, as equation (1)), wherein the scaling factor has a greater absolute value corresponding to a greater selected number of time periods (such as 6 consecutive selected time periods) and a lesser absolute value corresponding to a lesser selected number of time periods (such as 2 consecutive selected time periods). According to other system embodiments, the transaction data tracking system 12 may be configured to be capable of receiving scaling factors (input by an operator of the system 10 of the present invention, for example) having a variety of different values that may be “tuned” to emphasize shorter term trends so as to be capable of detecting and highlighting a rapid short-term increase or decrease in transactional activity. Using such “tunable” scaling factors, an operator of the system 10 may, for example, be capable of using the transaction data tracking system 12 to identify short term trends exhibited by a third-party affiliate 18a (such as a rapid increase in transactional activity) that may indicate the affiliate's 18a use of questionable internet marketing techniques such as “keyowrd stuffing” that may result in long-term difficulties.
For example, a trend (F[X]) in the number of transactions determined between a user 18, 18a and a selected product provider may be determined by the processor 20 of the present invention wherein the processor computes a component trend (F[X]) as follows:
The component trend (F[X]) computed by the processor 20 in this example includes a sum of slopes determined over several selected number of time periods multiplied by appropriate scaling factors (K) having a value appropriate to the selected number of time periods. For example, K[0] shown in equation (2) is multiplied by the slope shown generally in equation (1) corresponding to the percentage increase or decrease in the determined number of transactions between a particular user 18, 18a and a particular product provider during during two consecutive weeks. In addition, the scaling factor K[1] (wherein K[1]>K[0]) is multiplied by the slope corresponding to the percentage increase or decrease in the determined number of transactions between a particular user 18, 18a and a particular product provider during during four consecutive weeks (represented by N[0] (determined number of transactions for the week currenrly ending), N[−1] (determined number of transactions for the last week), N[−2] (determined number of transactions for the week prior to last week), and N[−3]. Similarly, the scaling factor K[2] (wherein K[2]>K[1]>K[0]) is multiplied in equation (2) by the slope corresponding to the percentage increase or decrease in the determined number of transactions between a particular user 18, 18a and a particular product provider during during eight consecutive weeks. Thus, according to this particular embodiment of the system 10 of the present invention, the eight week slope is emphasized in the determination of the component trend (F[X]) by the processor 20 of the transaction data tracking system 12 using a scaling factor K[2] having an absolute value that is greater than the scaling factors (K[1] and K[0]) corresponding to the four week and two week slopes, respectively.
Thus, the transaction data tracking system 12 may be capable of deemphasizing short-term component trends that may provide false indications that a particular product provider or third-party affiliate 18a is exhibiting a large increase or decrease in transactional activity. The transaction data tracking system 12 may be capable of emphasizing longer-term trends that may be better indicative of the relative success or failure of a particular product provider and/or affiliate 18a in bringing individual users' 18 business to a particular product source system 16. For example, the processor 20 may, via the application of scaling factors (the “K” values in equation (2), for example) to the trend (F[X]) determination, be capable of discerning a sudden weekly drop in the number of transactions (that may be the result of a server problem or other short-term communication problem between individal users 18 and the product provider, affiliate 18a, or other product source system 16) from a month-long drop in the number of transactions that may indicate that a particular product provider is not providing acceptable levels of service or competitive prices. In addition, the system 10 of the present invention may be also capable of determining when third-party affiliates 18a exhibit a long-term drop in transaction activity that may indicate that the third-party affiliate 18a has moved to an alternate product source system 16 in order to satisfy the product queries of its individual users 18. Thus, the transaction data tracking system 12 of the system 10 of the present invention may allow the operator of a product source system 16 to better respond to product providers (or affiliates 18a) that are exhibiting long-term increases or decreases in transactional activity so as to be capable of either addressing problems or rewarding positive business practices that are manifested in long-term decreases or increases in transactional activity.
According to some additional embodiments, the transaction data tracking system 12 of the system 10 of the present invention may be further configured to be capable of deemphasizing low-frequency trends (such as seasonal trends in the number of transactions occuring between users 18, 18a and product providers). For example, according to some embodiments, the processor 20 of the transaction data tracking system 12 may be configured to be capable of utilizing the average number of transactions determined between at least one of the users 18, 18a and at least one of the plurality of product providers during a selected time period (such as an “average” week) to modify the trend (F[X]). For example, an average A[X] number of transactions occuring between a user 18, 18a and a particular product provider per week (the selected time period) over the course of a selected 8-week period (the selected number of time periods) may be computed as follows:
A[X]=(N[0]+N[−1]+N[−2]+N[−3]+N[−4]+N[−5]+N[−6]+N[−7])/8 (3)
Where N[X] is the determined number of transactions between a particular user 18, 18a (such as a particular third-party affiliate 18a) and a product provider during the indicated week (N[0] represents the number of transactions determined during the week currently ending and N[−7] represents the number of transactions during the week 7 weeks prior to the week currently ending).
Furthermore, the processor 20 of the transaction data tracking system 12 may be further configured, in some embodiments, to utilize the selected time period average A[X] computed according to equation (3) as well as the trend F[X] computed according to equation (2), in order to generate an average resultant computed factor FA[0], as follows:
FA[0]=Average of (F[X]*A[X])/Average of (A[X]) (4)
Where Average of (F[X]*A[X] may be defined as the average of the F[X]*A[X] taking into account each of the possible user 18, 18a and product provider combinations, and wherein Average of A[X] may be defined as the average A[X] taking into account each of the possible user 18, 18a and product provider combinations.
In addition, according to some system 10 embodiments, the processor 20 of the transaction data tracking system 12 may be further configured to be capable of removing low-frequency variability (such as seasonal transactional trends) from the determination of the overal trend (FR[X]) in the number of transactions occuring between the users 18, 18a and a product provider. For example, the processor 20 may be capable of utilizing the average resultant computed factor (FA[0]) and the component trend (F[X]) to determine the overall transactional trend FR[X] for a given user 18, 18a or product provider as follows:
FR[X]=F[X]−FA[0] (5)
Wherein F[X] is the component trend defined generally as the weighted sum of the slopes (see Equation (1)) in the transactions occuring between users and product providers over a selected number of time periods and wherein FA[0] is the resultant computed factor used to take account of seasonal or other low-frequency trends that may affect the transactional activity of all individual users 18, third-party affiliates 18a, and product providers listed in the product source system 16 of the system 10 of the present invention.
According to some alternate embodiments of the system 10 of the present invention, the processor 20 of the transaction data tracking system 12 may be further configured to be capable of generating a list of product providers exhibiting a trend (FR[X], for example) in the number of transactions occuring between users 18, 18a and at least one of the plurality of product providers during the selected time period that exceeds a selected trend value. For example, an operator of the system 10 may input a specific selected trend value (corresponding to a selected increase and/or decrease in transactional activity during a selected time period) that may be stored in the data cache 30 of the memory device 22 such that the processor 20 may generate a list of product providers exhibiting an upward or downward trend in transactional activity that exceeds the selected trend value (that may, for example, be directly comparable to the determined FR[X] (see Equation (5)). Thus, the system 10 of the present invention may be capable of identifying product providers listed via the product source system 16 that may have increasing and/or decreasing popularity with individual users 18 or third-party affiliates 18a that may issue queries and/or purchase orders for product options offered by the identifed product providers. Similarly, the processor 20 of the transactional data tracking system 12 may also be configured to be capable of generating a list of product providers exhibiting the determined difference between the determined number of transactions and the average number of transactions per the selected time period that exceeds a selected difference. Thus, an operator of the system 10 may alternatively choose to obtain a list of product providers (provided by the processor 20) that exhibit a difference in the overall number (instead of a percentage) of transactions when compared to the average number of transactions for the selected time period.
According to other embodiments of the system 10 of the present invention, the processor 20 of the transaction data tracking system 12 may be capable of generating a list of users 18, 18a (such as particular third-party affiliates 18a) exhibiting a determined trend of the number of transactions initiated by the users 18, 18a during the selected time period that exceeds a selected trend value that may be input by an operator of the system 10 and subsequently stored in the memory device 22 of the transaction data tracking system 12. Thus the system 10 of the present invention may also be configured to be capable of identifying users 18, 18a, and particularly, third-party affiliates 18a that are exhibiting an exceptional increase and/or decrease in transactional activity during a specified time period. In addition, the processor 20 of the transactional data tracking system 12 may also be configured to be capable of generating a list of users 18, 18a initiating a number of transactions that exceeds the average number of transactions per the selected time period by a selected difference. Thus, an operator of the system 10 may alternatively choose to obtain a list of users 18, 18a (such as third-party affiliates 18a) that exhibit a difference in the overall number (instead of a percentage) of transactions when compared to the average number of transactions for the selected time period.
In some system 10 embodiments, the processor 20 of the transaction data tracking system 12 may be capable of generating a list of users 18, 18a (such as particular third-party affiliates 18a) wherein the list includes (and may be ranked according to) trend values (such as FR[X], for example) determined by the processor 20 of the transaction data tracking system. According to such embodiments, the system 10 may generate listings of third party affiliates 18a that may include, but are not limited to: third party affiliate 18a identifying information (billing number or ID number, for example), third-party affiliate 18a name, SRC code (which may comprise the “source” code or other unique identifying information for a third party affiliate 18a), third party affiliate 18a website name and/or URL, average transactions initiated by the third-party affiliate 18a during the selected time period, determined trend (such as FR[X] value computer by the transaction data tracking system 12 for the listed third-party affiliate 18a), and the raw number corresponding to the overall increase or decrease in the number of transactions initiated by the listed third-party affiliate 18a.
As shown generally in
As shown in
Additionally, as shown in step 250b of
In addition, and also as shown in
According to some method embodiments of the present invention, the method may further comprise (as shown generally in
In addition, as shown in
Thus, one exemplary embodiment of the method of the present invention may comprise (as in step 510 of
In addition, the report or listing generated according to step 510 of the method embodiment described above may comprise data elements that may include (but are not limited to): third party affiliate 18a identification number, third party affiliate 18a name, SRC code (which may comprise the “source” code or other unique identifying information for a third party affiliate 18a); third party affiliate 18a website name or URL; average transactions initiated by the third party affiliate for the selected time period (such as a one-week period); the computed trend (FR[X], for example); and the raw number corresponding to the increase or decrease in transactions initiated by the third party affiliate 18a during the selected time period.
In addition to providing systems and methods, the present invention also provides computer program products for performing the operations described above. The computer program products have a computer readable storage medium having computer readable program code means embodied in the medium. With reference to
In this regard,
Accordingly, blocks or steps of the block diagram, flowchart or control flow illustrations support combinations of means for performing the specified functions, combinations of steps for performing the specified functions and program instruction means for performing the specified functions. It will also be understood that each block or step of the block diagram, flowchart or control flow illustrations, and combinations of blocks or steps in the block diagram, flowchart or control flow illustrations, can be implemented by special purpose hardware-based computer systems which perform the specified functions or steps, or combinations of special purpose hardware and computer instructions.
Many modifications and other embodiments of the inventions set forth herein will come to mind to one skilled in the art to which these inventions pertain having the benefit of the teachings presented in the foregoing descriptions and the associated drawings. Therefore, it is to be understood that the inventions are not to be limited to the specific embodiments disclosed and that modifications and other embodiments are intended to be included within the scope of the appended claims. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.
