Source: https://patents.google.com/patent/US20100198772A1/en
Timestamp: 2018-11-15 09:35:52
Document Index: 793954571

Matched Legal Cases: ['§119', 'Application No. 61', '§1', '§1', '§2', '§2', '§2']

US20100198772A1 - Determining conversion probability using session metrics - Google Patents
US20100198772A1
US20100198772A1 US12535375 US53537509A US2010198772A1 US 20100198772 A1 US20100198772 A1 US 20100198772A1 US 12535375 US12535375 US 12535375 US 53537509 A US53537509 A US 53537509A US 2010198772 A1 US2010198772 A1 US 2010198772A1
US12535375
US8346709B2 (en )
Methods, systems, and apparatus, including computer program products, for determining a probability that a traffic conversion of a content item associated with a content source (e.g., website) will occur based on past traffic patterns for that content source. A traffic conversion defines, for example, minimum traffic interactions of one or more associated user sessions with a content source. The minimum traffic interactions can be based on, for example, the duration of the one or more user sessions on the content source, or a quantity of pages associated with the content source navigated in the one or more associated user sessions.
This application claims the benefit under 35 U.S.C. §119(e) of U.S. Provisional Patent Application No. 61/150,202, entitled “Determining Conversion Probability Using Session Metrics,” filed Feb. 5, 2009, which is incorporated here by reference.
The Internet provides access to a wide variety of content items, e.g., video and/or audio files, web pages for particular subjects, news articles, etc. Such access to these content items has likewise enabled opportunities for targeted advertising. For example, content items of particular interest to a user can be identified by a search engine in response to a user query. The query can include one or more search terms, and these terms can indicate the user's current interests. By comparing the user query to a list of keywords specified by an advertiser, it is possible to provide targeted advertisements to the user.
Another form of online advertising is advertisement syndication, which allows advertisers to extend their marketing reach by distributing advertisements to additional partners. For example, third party online publishers can place an advertiser's text or image advertisements on web pages that have content related to the advertisement. As the users are likely interested in the particular content on the publisher webpage, they are also likely to be interested in the product or service featured in the advertisement.
Some advertisers, however, do not offer products or services or elicit information on their web sites. Instead, the goal of these advertisers is to build brand recognition or provide the user with information about their products or services. An example is an automobile manufacturer. An automobile manufacturer does not sell automobiles on its web sites; however, it provides much information about its products on its web sites. Thus, the goal of this advertiser is to attract users that will spend a relatively long amount of time and/or navigate many pages on its web site. There is, however, no pricing model available for bidding for the placement of advertisements to such users.
In general, one aspect of the subject matter described in this specification can be embodied in methods that include defining a traffic conversion for a web property, the traffic conversion defining a minimum traffic interaction of one or more associated user sessions with the web property; identifying traffic conversion bid data for the web property; receiving a request for a content item associated with the web property; determining conversion probability data, the conversion probability data defining a conversion probability that the traffic conversion will occur subsequent to a selection of the content item; and determining bid data for the content item request based on the traffic conversion bid data and the conversion probability data. Other embodiments of this aspect include corresponding systems, apparatus, and computer program products.
FIGS. 1A-1B are block diagrams of an example environment in which a traffic conversion system can be implemented.
In general, the subject matter of this specification relates to determining the probability that a traffic conversion will occur for a given content item (e.g., an ad). A traffic conversion defines a conversion based on minimum traffic interactions of one or more associated user sessions with a content source (e.g., a web property). Traffic interactions occur when a user uses a client device (e.g., a computer or a television set top device) to visit or access a content source. A traffic interaction with a content source is an interaction that relates to length of the session with the content source and/or the number of pages navigated on the content source. A minimum traffic interaction thus defines a minimum duration of the user session or related user sessions with the content source, or a minimum quantity of pages associated with the content source navigated during the user session or related user sessions. Content property owners, e.g., advertisers, can select from different minimum traffic interactions to measure a traffic conversion. For example, a web property owner can select the minimum traffic interaction of a user session duration of three minutes as a traffic conversion, or a minimum traffic interaction of a selection of five web pages on the web property (e.g., website) during a user session, or during multiple associated user sessions during a period of interest (e.g., 30 days) as a traffic conversion. Although the implementations described herein are with reference to a web property being the content source, other content sources are also envisioned, for example, television content (e.g., media or interactive media provided through use of a television set top box device or an interactive radio receiver).
§1.1 Advertising Environment
FIGS. 1A-1B are block diagrams of an example environment 100 in which a traffic conversion system 130 can be implemented. The online environment 100 can facilitate the identification and serving of content items, e.g., web pages, advertisements, etc., to users. A computer network 110, such as a local area network (LAN), wide area network (WAN), the Internet, or a combination thereof, connects advertisers 102 a and 102 b, an advertisement management system 104, publishers 106 a and 106 b, client devices 108 a and 108 b, and a search engine 112. Although only two advertisers (102 a and 102 b), two publishers (106 a and 106 b) and two client devices (108 a and 108 b) are shown, the online environment 100 may include many thousands of advertisers, publishers and client devices.
§1.2 Advertisement Publishing And Tracking
One or more advertisers 102 a and/or 102 b can directly, or indirectly, enter, maintain, and track advertisement information in the advertising management system 104. The advertisements can be in the form of graphical advertisements, such as banner advertisements, text only advertisements, image advertisements, audio advertisements, video advertisements, advertisement gadgets with or without interactive features, advertisements combining one of more of any of such components, etc., or any other type of electronic advertisement document. The advertisements may also include embedded information, such as a links, meta-information, and/or machine executable instructions, such as HTML or JavaScript™. The advertisement can be submitted, for example, as a single advertisement creative, in a group of related advertisements as an advertisement group, or in multiple advertisement groups that form an advertisement campaign.
A client device, such as client device 108 a, can submit a page content request to a publisher 106 or the search engine 112. In some implementations, the page content can be provided to the client device 108 a in response to the request. The page content can include advertisements provided by the advertisement management system 104, or can include executable instructions, e.g., JavaScript™, that can be executed at the client device 108 a to request advertisements from the advertisement management system 104. Example client devices 108 include personal computers, mobile communication devices, television set-top boxes, game consoles, etc.
Advertisements can also be provided for the publishers 106. For example, one or more publishers 106 a and/or 106 b can submit advertisement requests for one or more advertisements to the system 104. In some implementations, the system 104 includes an ad request module 105 configured to receive/identify a request for an ad. The system 104 responds by sending the advertisements to the requesting publisher 106 a or 106 b for placement on one or more of the publisher's web properties (e.g., websites and other network-distributed content). Alternatively, the system 104 responds by sending the advertisement directly to the client device 108 a in response to a client device request for page content from the one or more publishers 106 a and/or 106 b, typically via instructions embedded in the page content received by the client device 108 a from the publishers 106 a and/or 106 b.
In some implementations, a publisher 106 can combine the requested content with one or more of the advertisements provided by the system 104. This combined page content and advertisements can be sent to the client device 108 that requested the content (e.g., client device 108 a) as page content for presentation in a viewer (e.g., a browser or other content display system). The publisher 106 can transmit information about the advertisements back to the advertisement management system 104, including information describing how, when, and/or where the advertisements are to be rendered (e.g., in HTML or JavaScript™).
Publishers 106 a and 106 b can include general content servers that receive requests for content (e.g., articles, discussion threads, audio, video, graphics, search results, games, software, web page listings, information feeds, etc.), and retrieve the requested content in response to the request. For example, content servers related news content providers, retailers, independent blogs, social network sites, or any other entity that provides content over the network 110 can be a publisher.
Advertisements can also be provided through the use of the search engine 112. The search engine 112 can receive queries for search results. In response, the search engine 112 can retrieve relevant search results from an index of documents (e.g., from an index of web pages). The search engine 112 can also submit a request for advertisements to the system 104. The request for advertisements may also include the query (as entered or parsed), information based on the query (such as geo-location information, whether the query came from an affiliate and an identifier of such an affiliate), and/or information associated with, or based on, the search results.
Advertisements and associated usage data (e.g., click-through-rate, impressions, etc.) can be stored as advertisement data in an advertisement data store 114. In some implementations, an advertiser 102 can further manage the serving of advertisement by specifying an advertising campaign. The advertising campaign can be stored in campaign data in a campaign data store 116 that can, for example, specify advertising budgets for advertisements, when, where and under what conditions particular advertisements may be served for presentation, etc.
§2.0 Determining Traffic Conversion Probabilities
In some implementations, a traffic conversion system 130 that estimates the probability that a traffic conversion for a given ad and user session (or multiple associated user sessions) will occur can be used in conjunction with the advertising management system 104. In the example implementation of FIG. 1A, the traffic conversion system 130 is a subsystem of the advertisement management system 104. In other implementations, the traffic conversion system 130 can be a separate system that can operate independently of the advertisement management system 104.
The traffic conversion system 130 can be realized by instructions that upon execution cause one or more processing devices to carry out the processes and functions described below. The traffic conversion system 130 can be distributively implemented over a network, such as a server farm, or can be implemented in a single computer device.
§2.1 Traffic Conversion Operation
There are many ways in which advertisers can pay or be charged for their advertisements. For example, advertisers can pay for their advertisements based on one or a combination of a cost-per-click basis, a cost-per-impression basis, and/or a cost-per-conversion basis. With respect to the latter basis, advertisers often define a conversion as resulting in a purchase transaction from the advertiser's website (e.g., web property) or a user submitting user information through the advertiser's website.
A user session for a user can be identified in various ways. For example, a user account for a user (e.g., a user account for a search engine or other network system) can be used to identify user sessions for the user. Each user account can be keyed to a user identifier that is uniquely associated with a user, and the user identifier is also associated with user sessions for its account. Such an account-based user session is defined by the user logging into the user account and is maintained until the user logs out of the account. Upon granting permission to track the user's history (e.g., the user opts-in to allow the user's online activities to be tracked), historical data for the user's sessions and other user data are tracked and associated with the user identifier. At the user's option, only data approved by the user are tracked (e.g., if the account is for a search engine, only search queries and search result selections are tracked). The user can clear all historical data associated with the user account at any time, and can opt-out of such tracking at any time. Further, to protect the privacy of the user, the historical data can be anonymized so that the data cannot be associated with the user. Additionally, from the user account and the historical data, the user's associated user sessions with a particular web property can be determined.
Associated user sessions are user sessions that are associated by the same identifying characteristic, such as the user identifier, the persistent cookie stored on a client device, or a particular network address. For example, a user may log into a network account using a user identifier and establish a first user session, during which the user selects an ad and is directed to a corresponding web property. During a later user session, established using the same user identifier for the network account, the user may later re-visit the web property. As the sessions are associated with the same user identifier, they are associated user sessions.
Exemplary traffic conversions can be the minimum interaction based on a duration of the one or more associated user sessions with the web property (e.g., at least X total minutes on the web property during user sessions with the web property during a two-week period of interest), a quantity of web pages associated with the web property navigated in the user session (e.g., visited at least Y pages of the web property during a user session), and time spent on a particular page of the web property. Traffic conversions can also be based on, for example, engagement to a particular page or group of pages of the web property (e.g., as determined by computer mouse movements on the page(s)), or based on a quantity of interactions with virtual pages such as AJAX pages/pages viewed but with no actual page transitions.
In some implementations, advertisers can select from a set of predetermined/predefined traffic conversions and/or can provide custom traffic conversions, and the traffic conversion learning module 132 can be trained for the predefined traffic conversions, and/or the custom advertiser traffic conversions defined by the advertisers. For example, a set of predefined traffic conversions may include minimum traffic interactions based on visiting a page for 1 minute, 2 minutes and 5 minutes during a single user session, or during associated user sessions during a period of interest. An advertiser interested in a traffic conversion not included in the set of predefined traffic conversions may provide a custom traffic conversion (e.g., visiting a page for 4 minutes). An advertiser may have multiple ads, and can select different and/or multiple traffic conversions for each ad. The predictive models are used to generate conversion probability data that define for each traffic conversion (e.g., predefined or custom) a probability that the traffic conversion will occur subsequent to an ad event for a user session, such as a selection of the ad (i.e., an ad click) or an impression of the ad for a particular user session.
The traffic pattern data can be collected from or provided by, for example, advertisers 102, publishers 106, and search engines 112. For example, a vehicle manufacturer can provide traffic pattern data to the traffic conversion system 130 including for each user session from a reporting period, information about which vehicle pages were viewed, how long each vehicle page was viewed, what time the session started and ended, if the session involved special website features such as building a vehicle to user preferences or the “locate a dealer near you” feature, etc. In some implementations, the traffic pattern data can be stored in and accessed from the traffic pattern data store 134.
The collection of traffic pattern data and the relation between web properties, client devices 108, publishers 106, and the search engine 112 is explained with reference to FIG. 1B. A client device 108 requests page content from a search engine 112, blog 106 a, or other publishers 106 b (selection 1). For example, a user can use a client device 108 to visit a search engine 112 and search for vehicles. In response to the user query, the search engine 112 requests one or more ads from the advertisement management system 104 (e.g., from the ad request module 105) for ads related to the query. Based on keywords used in the search, the system provides ads relevant to the search keywords (e.g., an ad associated with web property 160). After receiving the ads the search engine provides a list of search results and the ads to be displayed on the client device 108.
After a number of interactions during numerous different user sessions for other client devices 108, traffic pattern data for the web property 160 can be used by the traffic conversion learning module 132 to generate a predictive model for one or more traffic conversions associated with the web property 160. As the traffic pattern data for the web property 160 can change over time, the traffic conversion learning module 132 can generate (or update) the predictive model at predetermined intervals (e.g., every two weeks) based on the most recent traffic pattern data. The traffic conversion learning module 132 can, for example, store the predictive model(s) and/or the conversion probability data in the traffic conversion data store 142.
The bid determining module 144 can receive traffic conversion bid data for web properties provided by the advertisers. The traffic conversion bid data defines bid amounts for the traffic conversions from the advertisers/web property owners. For example, a web property owner may be willing to bid $7.00 for a traffic conversion defining a minimum traffic interaction of five pages navigated on the owner's web property during a user session, or $6.00 for a traffic conversion defining a minimum traffic interaction level of ten minutes spent visiting the web property during a user session. The bid determining module 144 can access and store traffic conversion bid data in the traffic conversion bid data store 136 according to web property, web property owner, and/or type of traffic conversion associated with the traffic conversion bid. In some implementations, the bid determining module 144 can receive the traffic conversion bid data from the advertisement management system 104 or directly from the advertisers 102 (e.g., through a browser interface).
For example, a traffic conversion bid of $7.00 by a web property owner/advertiser for a particular minimum traffic interaction cannot be directly processed in a typical click-based ad auction, which is based on a bid that an ad will be selected (i.e., “clicked”) and not that a conversion will occur. To effectively participate in click-based auctions the bid determining module 144 converts the traffic conversion bid into a click-based bid that takes into account the amount of the traffic conversion bid and the likelihood that the traffic conversion will occur. In some implementations, the bid determining module 144 can determine the bid data in part by multiplying the conversion probability data for a given ad by the corresponding traffic conversion bid data. For example, the conversion probability data may include a conversion probability for a traffic conversion of an ad of 7% and the web property owner associated with that ad may have bid $6.00 for a traffic conversion defining a minimum traffic interaction level of five pages navigated on the owner's web property as a result of the selection of the ad. Thus the bid data for the ad would include the bid amount of $0.42 ($6.00*0.07).
For example, suppose the quality score of ads A, B, and C are “2,” “1,” and “1,” respectively. Assume a traffic conversion bid for ad A has been converted into a click-based bid by the bid determining module 144. The rank of ads A, B, and C can be based on the following:
A: Rank=quality score×converted traffic conversion bid=2.0×$0.42=0.84
B: Rank=quality score×cost-per-click bid=1.0×$0.40=0.40
C: Rank=quality score×cost-per-click bid=1.0×$0.45=0.45
The ads can be ranked as follows:
The advertisement management system 104 can determine ad rank data based on the auction results for the ads. For example, the ad rank data for ads A, B, and C would indicate that ad A should be placed in the most prominent ad slot position, C the next most prominent ad slot position and B the least prominent ad slot position.
§2.2 Monetization of Ads
Charging advertisers (e.g., web property owners) utilizing a traffic conversion advertising payment scheme can be implemented in a variety of ways. In some implementations, the advertisement management system 104 provides an ad (associated with a traffic conversion) to be displayed to a client device 108, and determines whether the ad was selected at the client device 108 and whether the traffic conversion occurred in the corresponding user session (e.g., from data provided by the advertiser 102, the publishers 106, or the search engine 112). In some implementations, assuming the ad was selected and the traffic conversion occurred, an account (e.g., an advertising account described in the advertisement data store 114) associated with the advertiser/web property is debited for an amount defined by the traffic conversion bid data. For example, if an advertiser/web property owner has a bid of $8.00 for a traffic conversion defining a minimum traffic interaction of more than ten minutes on the web property and the user session lasted twelve minutes then the advertisement management system 104 can debit the advertiser/web property owner's account for $8.00.
In some implementations, the advertisement management system 104 provides an ad to be displayed to a client device 108 and determines whether the ad was selected at the client device 108 (but not necessarily whether a traffic conversion occurred). In such an implementation, if the ad was selected, regardless of whether a traffic conversion occurred, then an account associated with the advertiser/web property owner is debited for an amount defined by the bid data. For example, if the ad was selected and an advertiser/web property owner had a bid of $8.00 for a traffic conversion defining a minimum traffic interaction of more than ten minutes and the conversion probability that the traffic conversion for the ad will occur is 7% then the advertisement management system 104 can debit the advertiser/web property owner's account for an amount defined by the bid data of a bid of $0.56 ($8.00*0.07). Likewise, if the ad was not selected, then the advertiser/web property owner would not be charged.
FIG. 2 is a flow diagram of an example process 200 for determining conversion probability data for a content item. The process 200 can, for example, be implemented in the traffic conversion system 130 and/or the advertisement management system 104.
A predictive model to predict conversion probabilities is generated (408). For example, the traffic conversion learning module 132 can be trained to generate a predictive model to predict conversion probabilities (e.g., conversion probability data) based on the session features for the past user sessions. For example, the traffic conversion learning module 132 can determine the conversion probability data based on a mathematical function derived from logistic regression of the session features for a plurality of predefined traffic conversions. However, other predictive models (e.g., statistical processes and machine learning algorithms) can also be used.
FIG. 5 is block diagram of an example computer processing system 500 that can be used to determine conversion probabilities, bid data, and/or content item rank data. The system 500 can be used to realize a variety of different types of computer devices, such as the client devices 108 or server and computer devices on which the advertising system 104 and the traffic conversion system 130 are implemented.
defining a traffic conversion for a web property, wherein the traffic conversion defines a minimum traffic interaction of one or more associated user sessions with the web property;
identifying traffic conversion bid data for the web property;
determining by one or more processing devices conversion probability data, the conversion probability data defining a conversion probability that the traffic conversion will occur subsequent to a selection of the content item; and
determining by the one or more processing devices bid data for the content item request based on the traffic conversion bid data and the conversion probability data.
2. The method of claim 1 wherein the traffic conversion defines the minimum traffic interaction based on a duration of the one or more user sessions on the web property.
3. The method of claim 1 wherein the traffic conversion defines the minimum traffic interaction based on a quantity of web pages associated with the web property navigated in the one or more user sessions.
determining whether the content item was selected at the client device; and
determining whether the traffic conversion occurred in the one or more user sessions.
if the content item was selected, then debiting an account associated with the web property for an amount defined by the bid data.
8. The method of claim 1 wherein determining bid data for the content item comprises:
multiplying the conversion probability data for a given content item by the traffic conversion bid data.
9. The method of claim 1 wherein determining conversion probability data comprises:
analyzing traffic pattern data for the web property to identify traffic interaction levels of a plurality of past user sessions with the web property, the traffic pattern data defining traffic patterns for the plurality of past user sessions on the web property; and
defining durations of each of the plurality of past user sessions on the web property and a quantity of web pages associated with the web property navigated in each of the plurality of past user sessions.
10. The method of claim 9 wherein determining conversion probability data comprises:
comparing the minimum traffic interaction defined by the traffic conversion to the traffic interaction levels identified by the analyzed traffic pattern data; and
generating the conversion probability data based on the comparison.
11. The method of claim 9 wherein determining conversion probability data comprises:
12. The method of claim 1 wherein the content item is an advertisement.
identify a traffic conversion for the web property, wherein the traffic conversion defines a minimum traffic interaction of one or more associated user sessions with the web property; and
determine conversion probability data, the conversion probability data defining a conversion probability that the traffic conversion will occur subsequent to a selection of the content item; and
a bid determining module configured to:
identify traffic conversion bid data for the web property; and
determine bid data for the content item request based on the traffic conversion bid data and the conversion probability data.
14. The system of claim 13 wherein the traffic conversion defines the minimum traffic interaction based on a duration of the one or more user sessions on the web property.
15. The system of claim 13 wherein traffic conversion defines the minimum traffic interaction based on a quantity of web pages associated with the web property navigated in the one or more user sessions.
16. The system of claim 13 wherein to determine the bid data for the content item request, the bid determining module is configured to multiply the conversion probability data by the traffic conversion bid data.
17. The system of claim 13 wherein the traffic conversion learning module is configured to:
define durations of each of the plurality of past user sessions on the web property; and
define a quantity of web pages associated with the web property navigated in each of the plurality of past user sessions.
18. The system of claim 17 wherein to determine the conversion probability data, the traffic conversion learning module is configured to:
compare the minimum traffic interaction defined by the traffic conversion to the traffic interaction levels identified by the analyzed traffic pattern data; and
generate the conversion probability data based on the comparison.
19. Software stored on a computer readable medium and comprising instructions executable by a processing device and upon such execution cause the processing device to perform operations comprising:
define a traffic conversion for a content source, wherein the traffic conversion defines a minimum traffic interaction of one or more associated user sessions with the content source;
identify traffic conversion bid data for the content source;
20. The software of claim 19 wherein the traffic conversion defines the minimum traffic interaction based on a duration of the one or more user sessions on the content source.
21. The software of claim 19 wherein the traffic conversion defines the minimum traffic interaction based on a quantity of web pages associated with the content source navigated in the one or more user sessions.
22. The software of claim 19 wherein the content item is an advertisement.
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