Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
  • G06Q30/00—Commerce
  • G06Q30/02—Marketing; Price estimation or determination; Fundraising

Definitions

• contracts to show ads are normally signed several weeks/months before ads get delivered.
• the duration of contracts ranges from one day to multiple years.
• regular contracts the advertisers purchase a designated number of ad views on a chosen space (web page).
• exclusive contracts they purchase all the ad views on a chosen space.
• infinite contracts they purchase all the leftover ad views on a chosen space after other regular contracts related to that space have been fulfilled.
• advertising on the Internet is similarly subject to physical limitation. For obvious reasons, it is a natural and often most selected choice for advertisers to request ad views on the home page of a web portal or ISP. However, since there is a finite amount of physical space on a web page, demand for ad space or ad views on popular web pages often exceeds supply. Thus, a significant number of ads do not always get placed on the most desired web pages.
• Fig. 1 is a simplified network diagram showing the structure of the Yahoo! network. At the top of the tree is the entire Yahoo! network. Under this node are various nodes, such as Yahoo! Shopping, Yahoo! Sports, Yahoo! Yellow Pages, Yahoo! Search, etc. Under each of these nodes, there may be a variety of descendant nodes, each of which may have a variety of additional descendant nodes. For example, under the Yahoo! Sports node are the NFL, NHL, NBA, etc. nodes, and under the NBA node are Standing, Statistics, Games, etc. nodes, and so on. The search result pages are also included as part of the tree. For instance, under the Yahoo!
• Search node are all the result pages from search words that are entered on the Yahoo! front page.
• the present invention relates to a system and method for collecting and deriving Internet user behavioral data. More specifically, the present invention relates to a system and method for collecting and deriving historical and demographic data based on Internet user behavior so as to allow alternative advertising inventory to be selected in place of sold out advertising inventory.
• the present invention includes a number of ad records.
• An ad record is generated for each ad appearing on a viewed web page.
• an additional record creation routine first creates one or more additional ad records based on one or more of the original ad records. This is performed to allow the computation of historical and demographic data for trees of web pages (all nodes descendant from a single node) and even entire web sites.
• a filtering routine then processes all the ad records to create a first group of records and a second group of records.
• the first group of records contains only registered user records, while the second group of records contains records for all users, registered and unregistered.
• a record For a registered user, a record includes a P cookie, a L cookie, a B cookie, and a Space ID; whereas, for an unregistered user, a record does not contain any P cookie or L cookie and only includes a B cookie and a Space ID.
• the first group of records is created by examining whether a record has a P cookie and/or L cookie; each record also contains the associated B cookie and Space ID.
• the second group of records is created by extracting from each user's (registered or unregistered) record the associated B cookie and Space ID.
• the two groups of records are thus, namely, a first group containing only registered user records with each record additionally having a P cookie and a L cookie, and a second group containing records for all users (registered and unregistered).
• the B cookie provides identification information about the user's particular browser.
• the P cookie provides demographic information, such as age, sex, occupation, etc., about a registered user.
• the L cookie provides a user name of a registered user.
• the Space ID provides identification information about the web page for which the record is generated.
• Each group of records is then processed in a different manner.
• a first sorting routine sorts these records based on the L cookie, i.e., by user name.
• An indexing routine then creates an index for each of these records using the P cookie. Since the P cookie includes demographic information, the index to be created essentially represents a demographic profile. In a preferred embodiment, the index is represented by a bit map and each bit of the bit map represents a demographic characteristic.
• a second sorting routine sorts the first group of records based on the Space ID. By sorting the Space ID, the records are then grouped by web pages. Hence, demographic information from records relating to the same web page can be obtained.
• a third sorting routine also sorts the first group of records based on the indices associated with these records. Since the indices represent demographic profiles, records having the same demographic profile are then grouped together. Collective Space ID information can then be examined from these grouped records to derive information on the web pages most frequently viewed by users having the same demographic profile. This information can then be used to identify alternative advertising inventory amongst the web pages.
• a first tallying routme first calculates the respective total number of visits to each of a number of web pages identified from the Space IDs of the second group of records.
• a second tallying routine determines a number of affinity relationships. One affinity relationship is determined for each pair of different web pages amongst the web pages identified from the Space IDs of the second group of records. This second tallying routine also maintains the respective cumulative totals for each of the determined affinity relationships. By using the respective total number of visits and the respective cumulative totals, information on the likelihood of a user visiting one web page and also visiting another web page can be determined. Such information can similarly be used to identify alternative advertising inventory. Reference to the remaining portions f the specification, including the drawings and claims, will realize other features and advantages of the present invention. Further features and advantages of the present invention, as well as the structure and operation of various embodiments of the present invention, are described in detail below with respect to accompanying drawings, like reference numbers indicate identical or functionally similar elements.
• FIG. 1 is a simplified network diagram showing the structure of the Yahoo! network; and Figs. 2A-E are simplified flow diagrams illustrating the operation of an exemplary embodiment of the present invention.
• Figs. 2A-E are simplified flow diagrams illustrating the operation of an embodiment of the present invention.
• the adlogs 20 are collectively an inventory which provides a record of all the ads which have been displayed to users during a predetermined time period.
• the predetermined time period can vary based on a number of factors, such as processing needs, system storage constraints, etc. Every time a user views a particular web page, information relating to all the ads appearing on that particular web page is recorded in the adlogs 20.
• an ad record is generated for each ad displayed on each viewed web page.
• each entry or ad record in the adlogs 20 contains various information about the user viewing the ad, including, for example, a B cookie, a P cookie, a L cookie, and a Space ID.
• the B cookie contains identifying information about the browser used by a particular user. Such information typically include, for example, a serial number assigned to a browser.
• the P cookie contains certain demographic information about a user, such as gender, date of birth, zip code, country, occupation, industry, and interests, etc.
• the information represented by the P cookie is generally obtained from the user at the time the user signs up or registers with a web portal or ISP. Hence, the P cookie is usually only applicable to a registered user.
• the L cookie contains the user name of a registered user.
• the Space ID contains identification information which indicates the specific web page the user has visited.
• the Space ID provides information about what web page has been viewed by the user.
• an additional record creation process 22 examines each ad record in the adlogs 20 to determine if additional ad records need to be created. This is done to compute data for trees of web pages and/or entire web. sites so as to more accurately reflect the distribution of the demographic data.
• some web portals such as Yahoo!, organize their web pages in a tree structure with nodes.
• an additional, identical record with the proper Space ID is generated for each and every node that is an ancestor of that particular node, to the extent that such identical record(s) is not already present in the adlogs.
• additional ad records may be generated for each and every node that is above that particular node.
• ad records for ads displayed on that web page are generated in the adlogs 20.
• an additional ad record is also generated respectively for each of the nodes above, namely, the NFL web page 14, the Yahoo! Sports web page 12, and the Yahoo! Network web page 10. Since each of these web pages are separate and distinct from each other, their respective ad records necessarily reflect their own corresponding Space IDs but otherwise contain the same demographic information as the originating records.
• All the ad records are then filtered by a filtering process 24 using different criteria to generate two groups of records. More specifically, a first group of records is generated for registered users, and a second group of records is generated for all users, registered or otherwise. Since only records of registered users would contain a L cookie, this is achieved by examining whether a L cookie is present in an record. Alternatively, a P cookie can also be used to generate the first group of records. Hence, after the filtering process 24, respective records for the two groups of users, namely, the registered users and all users, are identified and grouped together.
• records for the two groups are further sorted based on the L cookie and the B cookie, respectively.
• the first group is sorted by the L cookie and the second group is sorted by the B cookie.
• the two groups of records are then stored separately, for example, in databases 26, 40.
• the records for the two groups are treated differently, as will be further described below.
• the records for the registered users are sorted based on the L cookie.
• the L cookie contains information on the user name for a registered user. Thus, by sorting the L cookie, all the records and information relating to a particular registered user are grouped together.
• each of these records is then processed by an indexing process 28 to create an index for that particular record.
• An index is a bit map which represents the demographic data in each record.
• Each bit in the bit map is designated a particular demographic characteristic.
• the first bit of the bit map may represent the sex, e.g., male, of a user.
• other bits can be used to represent demographic characteristics such as between age 30-39, annual income exceeding $100,000, engineer as occupation, etc.
• additional bit(s) in a bit map are created based on the web page (obtained via the Space ID of each record) the user has visited. These bits reflect user history and interests, which are valuable additions to the demographic characteristics of the user.
• these records can be sorted by either Space ID or bit map and then processed accordingly, as will be further described below.
• these records are sorted by Space ID.
• Space ID provides the identification information used to indicate the specific web page the user has visited. By sorting the Space ID, all the records originating from the same web page are grouped together. Practically, this means that all the demographic information relating to each web page is collected and available for subsequent use.
• the records are then summarized at 32.
• information from the records are collected and stored. More specifically, for each Space ID, the respective bit maps or index information for all records having that Space ID is now available and stored in a database 34 for future access. In other words, demographic information for all users who have visited a particular web page is accessible from the database 34.
• the bit count for each bit of the bit map is calculated.
• the total number of users having a specific demographic characteristic who have visited that particular web page can be determined. For example, the total number of males who have viewed a particular web page can be determined.
• Additional demographic evaluations within a specified demographic group can further be performed by using the bit maps.
• the bit representing the age between 20-29 can further be selected to determine the total number of males within that particular age group. Additional refinements can be made using other bits of the bit map as well.
• various demographic profiles can be determined for a particular web page.
• the records for the registered users are sorted by bit map. By sorting the records based on their bit maps, records with identical bit maps are grouped together. Since each bit of a bit map represents a demographic characteristic and the bit map represents a demographic profile, users with identical demographic profiles are then grouped together.
• Additional information can be obtained from these records which have been grouped based on demographic profiles. This information is then formatted and stored in a database 38 for subsequent use. For example, for each group of records having a specific demographic profile, Space ID information can be extracted from each record within the group. By examining the collective Space ID information, the web pages most frequently visited by users having that specific demographic profile can be identified. Thus, information on web pages that are frequently visited by the respective demographic groups is available. Using such information, advertisers can be advised appropriately regarding the placement of their ads. Ads can then be more strategically tailored and positioned to maximize their exposure and efficacy on the targeted demographic groups.
• the records for all the users are sorted based on the B cookie and stored in database 40.
• the B cookie provides information used to identify a user's particular browser. Consequently, by sorting the B cookie, all the behavioral data originating from the same browser is grouped together. It is recognized that in certain situations, such as where an Internet-enabled computer is generally accessible to the public or where such computer is used by various family members, multiple users may use the same browser at various times thereby producing results which are representative of many users. From a statistical perspective, so long as the same browser is consistently used by the same general group of users, the behavioral data collected from that browser remains useful.
• the records for all the users are processed in a different manner. It should be noted that the respective processing of the first group of records and the second group of records is independent of each other. As noted above, the records for all the users are sorted by the B cookie. Sorting by the B cookie is preferred since unregistered users have not previously provided any registration or demographic information, therefore, records for the unregistered users do not contain any P cookies. These records, however, include the Space IDs since Space ID information is captured during a browsing session, regardless of the status of a user.
• the sorted records of all the users go through an affinity and tallying process 42. More specifically, for each B cookie, i.e., each browser, a cumulative total is tallied and kept for each individual unique Space ID, i.e., an individual tally for each of the web pages visited by that browser is maintained. The collective cumulative totals for various unique Space IDs from all the browsers are then combined and stored for subsequent use.
• an affinity relationship is determined for every pair of different Space IDs and the corresponding affinity count for that pair of Space IDs is incremented.
• affinity relationships amongst all the web pages visited by the same browser information can be obtained to predict the tendency and usage behavior of the user(s) using that browser in terms of the user(s) viewing one web page in connection with another.
• Information on the affinity relationships amongst the web pages visited by all the browsers is then collected. It should be understood that an affinity relationship can be made to correlate more than a pair of different web pages. Such relationship can involve, for example, three or more different web pages. A person with ordinary skills in the art will know of ways to implement such affinity relationship.
• the cumulative totals for web pages A, B and C are 100, 200 and 300, respectively and that the affinity counts for affinity relationships A-B, A-C and B-C are 50, 100 and 150, respectively.
• the percentage of users visiting web page A who also visited web page B is 50% and that the percentage of users visiting web page B who also visited web page A is 25%.
• the percentages are calculated as follows. Since the cumulative total for web page A is 100 and the affinity count for A-B is 50, that means that 100 users have visited web page A, and that out of those 100 users visiting web page A, only 50 of them also visited web page B, therefore, resulting in the 50% figure.
• the present invention as described herein is used in connection with identifying alternative advertising inventory amongst web pages, the present invention can be easily implemented for other areas of application such as identifying web pages which fit specified demographic profiles so as to facilitate searching of relevant web pages. For example, assume that a user is particularly interested in a specific web page amongst the results returned from a search. Using the present invention, other relevant web pages, similar to the one that the user is interested in, can be identified and shown to the user. A person of ordinary skill in the art will know of other ways and methods to apply the present invention.
• the present invention as described herein can be implemented using both hardware and/or software, or a combination thereof.
• the databases that are used to store the adlogs and other processed records are implemented using sorted flat files techniques.
• the various processes such as filtering, sorting, creating the index or bit map, etc. are preferably implemented using computer software such as C, C++, etc.

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