as) United States
`a2) Patent Application Publication (0) Pub. No.: US 2006/0230053 Al
`(43) Pub. Date: Oct. 12, 2006
`
`Eldering
`
`US 20060230053A1
`
`(54) CONSUMER PROFILING AND
`ADVERTISEMENT SELECTION SYSTEM
`
`(52) US. Che ee cceececceeeeseesesseeseeseeneesnnenesesneaees 707/101
`
`(75)
`
`Inventor: Charles Eldering, Doylestown, PA
`(US)
`
`(57)
`
`ABSTRACT
`
`Correspondence Address:
`TECHNOLOGY, PATENTS AND LICENSING,
`INC./PRIME
`2003 SOUTH EASTON RD
`SUITE 208
`
`DOYLESTOWN,PA 18901 (US)
`
`(73) Assignee: Prime Research Alliance E., Inc.
`
`(21) Appl. No.:
`
`11/450,252
`
`(22)
`
`Filed:
`
`Jun. 9, 2006
`
`Related U.S. Application Data
`
`(63) Continuation of application No. 09/807,887, filed on
`Apr. 19, 2001, now Pat. No. 7,062,510.
`
`Publication Classification
`
`(51)
`
`Int. CL
`GO6F 17/00
`
`(2006.01)
`
`Aconsumerprofiling and advertisement selection system is
`presented in which consumers or subscribers can be char-
`acterized based on their purchase or viewing habits. The
`result of this process is a consumer characterization vector
`describing the probabilistic demographics and productpref-
`erences of the subscriber or viewer. Advertisement charac-
`
`terization vectors describing an actual or hypothetical mar-
`ket
`for a product or desired viewing audience can be
`determined. The ad characteristics including an ad demo-
`graphic vector, an ad product category and an ad product
`preference vector is transmitted along with a consumer ID.
`The consumerID is used to retrieve a consumer character-
`ization vector which is correlated with the ad characteriza-
`
`tion vector to determine the suitability of the advertisement
`to the consumer. A price for displaying the advertisement
`can be determined based on the results of the correlation of
`
`the ad characteristics with the consumer characterization
`vector.
`
`|
`
`II
`
`PROFILER
`140
`
`CONSUMER
`PROFILE SERVER
`
`
`POINT OF
`
`PRIVATE NETWORK
`PURCHASE
`
`110
`
`
`
`
`AD SERVER
`
`130
`ra
`Se7
`J |
`6
`SETTOP
`
`
`: | <—”A—_CONSUMER
`ADVERTISER
`1
`
`144
`
`CONTENTI
`
`OPPORTUNITY eee
`PROVIDER
`+52
`160
`
`164
`
`AD
`182
`
`/“
`
`“
`
`Meta EX1011
`
`IPR2024-00529
`US. Patent No. 8,332,454
`
`Meta EX1011
`IPR2024-00529
`U.S. Patent No. 8,332,454
`
`

`

`Patent Application Publication Oct. 12,2006 Sheet 1 of 17
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`Patent Application Publication Oct. 12,2006 Sheet 12 of 17
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`

`Patent Application Publication Oct. 12,2006 Sheet 14 of 17
`
`US 2006/0230053 Al
`
`RECEIVE POINT OF
`800|PURCHASE INFORMATION
`
`
`DETERMINISTIC
`
`DEMOGRAPHIC INFORMATION
`AVAILABLE?
`
`READ PURCHASE
`ID INFO
`
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`
`

`

`Patent Application Publication Oct. 12,2006 Sheet 15 of 17
`
`US 2006/0230053 Al
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`900
`
`RECEIVE
`CONSUMER ID
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`AD PRODUCT CATEGORY
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`PREFERENCE
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`CORRELATION
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`
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`PREFERENCE
`
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`
`

`

`Patent Application Publication Oct. 12,2006 Sheet 16 of 17
`
`US 2006/0230053 Al
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`\
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`CONSUMER
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`PRICING —
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`OPPORTUNITY
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`
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`
`

`

`Patent Application Publication Oct. 12,2006 Sheet 17 of 17
`
`US 2006/0230053 Al
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`4
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`
`

`

`US 2006/0230053 Al
`
`Oct. 12, 2006
`
`CONSUMER PROFILING AND ADVERTISEMENT
`SELECTION SYSTEM
`
`CROSS REFERENCE TO RELATED
`APPLICATION
`
`[0001] This application is a continuation of U.S. patent
`application Ser. No. 09/807,887, filed Apr. 19, 2001, and
`entitled Consumer Profiling and Advertisement Selection
`System,the entire disclosure of whichis incorporated herein
`by reference.
`
`‘his application claims the benefit of International
`[0002]
`Application No. PCT/US99/28628,
`filed Dec. 2, 1999,
`entitled Consumer Profiling and Advertisement Selection
`System, which claims the benefit of co-pending U.S. patent
`application Ser. No. 09/204,888, filed Dec. 3, 1998, entitled
`Subscriber Characterization System; U.S. patent application
`Ser. No. 09/268,526, filed Mar. 12, 1999, entitled Adver-
`tisement Selection System Supporting Discretionary Target
`Market Characteristics, now U.S. Pat. No. 6,216,129; and
`USS. patent application Ser. No. 09/268,519, filed Mar. 12,
`1999, entitled ConsumerProfiling System, now U.S. Pat.
`No. 6,298,348.
`
`BACKGROUND OF THE INVENTION
`
`[0003] The adventof the Internet has resultedin theability
`to communicate data across the globe instantaneously, and
`will allow for numerous new applications which enhance
`consumer’s lives. One of the enhancements which can occur
`
`is the ability for the consumerto receive advertising which
`is relevant to their lifestyle, rather than a stream of ads
`determined by the program they are watching. Such “tar-
`geted ads” can potentially reduce the amount of unwanted
`information which consumers receive in the mail, during
`television programs, and when using the Internet. Examples
`of editorial targeting can be found on the World Wide Web,
`where bannersare delivered based on the page content. The
`productliterature from DoubleClick, “Dynamic Advertising
`Reporting and Targeting (DART),” printed from the World
`Wide Web site http:/Awww.doubleclick.net/dart on Jun. 19,
`1998 discloses DoubleClick’s advertising solution for
`matching advertiser’s selected targeted profiles with indi-
`vidual user profiles and deliver an appropriate banner. The
`user and advertisements are matched based on geographic
`location or keywords on the page content. The product
`literature from Imgis, “Ad Force,” printed from the World
`Wide Website http:/Avww.starpt.com/core on Jun. 30, 1998
`discloses an ad management system for targeting users and
`delivering advertisements to them. Users are targeted based
`on the type of content they are viewing or by keywords.
`
`[0004] From an advertiser’s perspective the ability to
`target ads can be beneficial since they have some confidence
`that their ad will at least be determined relevant by the
`consumer, and therefore will not be found annoying because
`it is not applicable to their lifestyle. Different systems for
`matching a consumerprofile to an advertisement have been
`proposed such as the U.S. Pat. No. 5,774,170, which dis-
`closes a system for delivering targeted advertisement to
`consumers. In this system, a set of advertisements is tagged
`with commercial
`identifier (CID) and, from the existing
`marketing database, a list of prospective viewers is also
`identified with CID. The commercials are displayed to the
`consumers when the CIDs match.
`
`[0005] Other systems propose methodsfor delivering pro-
`gramming tailored to subscribers’ profile. U.S. Pat. No.
`5,446,919 discloses a communication system capable of
`targeting a demographically or psychographically defined
`audience. Demographic and psychographic information
`about audience member are downloaded and stored in the
`
`audience memberreceiver. Media messages are transmitted
`to audience member along with a selection profile com-
`mand, which details the demographic/psychographic profile
`of audience membersthat are to receive each media mes-
`sage. Audience members which fall within a group identified
`by the selection profile command are presented with the
`media message.
`
`[0006] U.S. Pat. No. 5,223,924 discloses a system and
`method for automatically correlating user preferences with a
`TV program information database. The system includes a
`processor that performs “free text” search techniques to
`correlate the downloaded TV program information with the
`viewer’s preferences. U.S. Pat. No. 5,410,344 discloses a
`method for selecting audiovideo programs based on view-
`ers’ preferences, wherein each of the audiovideo programs
`has a plurality of programs attributes and a corresponding
`content code representing the program attributes. The
`method comprises the steps of storing a viewer preference
`file, which includesattributes ratings, which represents the
`degree of impact of the programsattributes on the viewer
`and, in response to the comparison of viewerpreferencefile
`with the program content codes, a program is selected for
`presentation to the viewer.
`
`In order to determine the applicability of an adver-
`[0007]
`tisement to a consumer, it is necessary to know something
`about their lifestyle, and in particular to understand their
`demographics (age, household size and income). In some
`instances, it is useful to know their particular purchasing
`habits. Purchasing habits are being used by E-commerce to
`profile their visitors. As an example, the productliterature
`from Aptex software Inc., “SelectCast for Commerce Serv-
`ers,” printed from the World Wide Website http://www.ap-
`tex.com/products-selectcast-commerce.htm on Jun.
`30,
`1998 discloses the product SelectCast for Commerce Serv-
`ers. The product personalizes online shopping based on
`observed user behavior. User interests are learned based on
`
`the content they browse, the promotions they click and the
`products they purchase.
`
`[0008] Knowledge of the purchasing habits of a consumer
`can be beneficial to a product vendor in the sense that a
`vendor of soups would like to know which consumers are
`buying their competitor’s soup, so that they can target ads at
`those consumers in an effort to convince them to switch
`
`brands. That vendor will probably not want to target loyal
`customers, although for a new product
`introduction the
`strategy may be to convince loyal customers to try the new
`product. In both cases it is extremely useful for the vendor
`to be able to determine what brand of product the consumer
`presently purchases.
`
`[0009] There are several difficulties associated with the
`collection, processing, and storage of consumer data. First,
`collecting consumer data and determining the demographic
`parameters of the consumercan be difficult. Surveys can be
`performed, and in some instances the consumer will will-
`ingly give access to normally private data including family
`size, age of family members, and household income. In such
`
`

`

`US 2006/0230053 Al
`
`Oct. 12, 2006
`
`circumstances there generally needs to be an agreement with
`the consumer regarding how the data will be used. If the
`consumerdoes not providethis data directly, the information
`must be “mined” from various pieces of information which
`are gathered about the consumer, typically from specific
`purchases.
`
`[0010] A relatively intrusive method for collecting con-
`sumer information is described in U.S. Pat. No. 4,546,382,
`which discloses a television and market research data col-
`
`lection system and method.A data collection unit containing
`a memory, stores data as to which ofthe plurality of TV
`modesare in use, which TV channel is being viewed as well
`as input from a suitable optical scanning device for collect-
`ing consumer product purchases.
`
`[0011] Once data is collected, usually from one source,
`some type of processing can be performed to determine a
`particular aspect of the consumer’s life. As an example,
`processing can be performed on credit data to determine
`which consumers are a good credit risk and have recently
`applied for credit. The resulting list of consumers can be
`solicited,
`typically by direct mail. Although information
`such as credit history is stored on multiple databases, storage
`of other information such as the specifics of grocery pur-
`chases is not typically performed. Even if each individual’s
`detailed list of grocery purchases was recorded, the infor-
`mation would be oflittle use since it would amount to
`nothing more than unprocessed shoppinglists.
`
`[0012] Privacy concerns are also an important factor in
`using consumer purchase information. Consumers will gen-
`erally find it desirable that advertisements and other infor-
`mation is matched with their interests, but will not allow
`indiscriminate access to their demographic profile and pur-
`chase records.
`
`[0013] The Internet has spawned the concept of “nega-
`tively priced information” in which consumers can be paid
`to receive advertising. Paying consumers to watch adver-
`tisements can be accomplishedinteractively over the Inter-
`net, with the consumer acknowledging that they will watch
`an advertisementfor a particular price. Previously proposed
`schemes such as that described in U.S. Pat. No. 5,794,210,
`entitled “Attention Brokerage,” of which A. Nathaniel Gold-
`haber and Gary Fitts are the inventors, describe such a
`system, in which the consumeris presented with a list of
`advertisements and their corresponding payments. The con-
`sumer chooses from the list and is compensated for viewing
`the advertisement. he system uses also software agents
`representing consumers to match the consumer interest
`profiles with advertisements. The matching is done using
`“relevance indexing” which is based on hierarchical tree
`structures. The system requires real-time interactivity in that
`the viewer must select the advertisement from the list of
`
`choices presented.
`
`Theability to place ads to consumers and compen-
`[0014]
`sate them for viewing the advertisements opens many pos-
`sibilities for new models of advertising. However,
`it
`is
`important to understand the demographics and product pref-
`erences of the consumerin order to be able to determine if
`an advertisement is appropriate.
`
`[0015] Although it is possible to collect statistical infor-
`mation regarding consumers of particular products and
`compare those profiles against individual demographic data
`
`points of consumers, such a methodology only allows for
`selection of potential consumers based on the demographics
`of existing customers of the same or similar products.
`
`[0016] U.S. Pat. No. 5,515,098, entitled “System and
`method for selectively distributing commercial messages
`over a communications network,” of which John B. Carles
`is the inventor, describes a method in which target household
`data of actual customers of a product are compared against
`subscriber household data to determine the applicability of
`a commercial
`to a household. Target households for a
`product or service are characterized by comparing or cor-
`relating the profile of the customer household to the profile
`of all households. A rating is established for each household
`for each category of goods/services. The households within
`a predefined percentile of subscribers, as defined by the
`rating, are targeted by the advertiser of the product or
`service.
`
`It will also frequently be desirable to target an
`{0017]
`advertisement to a market having discretionary characteris-
`tics and to obtain a measure of the correlation of these
`
`discretionary features with probabilistic or deterministic
`data of the consumer/subscriber, rather than being forced to
`rely on the characteristics of existing consumers of a prod-
`uct. Such correlation should be possible based both on
`demographic characteristics and product preferences.
`
`[0018] Another previously proposed system, described in
`USS. Pat. No. 5,724,521, entitled “Method and apparatus for
`providing electronic advertisements to end users in a con-
`sumerbest-fit pricing manner,” of which R. Dedrick is the
`inventor, utilizes a consumer scale as the mechanism to
`determine to which group an advertisement is intended. A
`consumer scale matching process comparesthe set of char-
`acteristics stored in a user profile database to a consumer
`scale associated with the electronic advertisement. The fee
`charged to the advertiser is determined by wherethe set of
`characteristics fall on the consumer scale. Such a system
`requires specification of numerous parameters and weight-
`ing factors, and requires access to specific and non-statistical
`personal profile information.
`
`[0019] For the foregoing reasons, there is a need for a
`consumerprofiling system which can profile the consumer,
`provide access to the consumerprofile in a secure manner,
`and return a measurementofthe potential applicability of an
`advertisement. There is also a need for an advertisement
`
`selection system which can match an advertisement with
`discretionary target market characteristics, and which can do
`so in a manner whichprotects the privacy of the consumer
`data and characterizations.
`
`SUMMARY OF THE INVENTION
`
`[0020] The present invention supports the receipt of con-
`sumer purchase information with which consumer charac-
`terization vectors are updated based on product character-
`ization information. The consumercharacterization vectors
`
`include a consumer demographic vector which provides a
`probabilistic measure of the demographics of the consumer,
`and a product preference vector which describes which
`products the consumer has typically purchased in the past,
`and thereforeis likely to purchase in the future. The product
`characterization information includes vector information
`which represents probabilistic determinations of the demo-
`graphics of purchasers of an item, heuristic rules which can
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`
`be applied to probabilistically describe the demographics of
`the consumer based on that purchase, and a vector repre-
`sentation of the purchase itself.
`
`In a preferred embodiment a computer-readable
`[0021]
`detailed purchase record is received, along with a unique
`consumeridentifier. A demographic characterization vector
`corresponding to the consumercanberetrieved.In the event
`that there is no existing demographic characterization vector
`for that consumer, a new demographic characterization
`vector can be created. In a preferred embodiment the new
`demographic characterization vector contains no informa-
`tion. A set of heuristic rules is retrieved and contains a
`probabilistic measure of the demographic characteristics of
`a typical purchaser of an item. A new demographic charac-
`terization vector is calculated based on the purchase, the
`existing demographic characterization vector, and the heu-
`ristic rules.
`
`Ina preferred embodiment the calculation of the
`[0022]
`demographic characterization vector is performed by calcu-
`lating a weighted average of a product demographics vector
`and the existing demographic characterization vector. A
`weighting factor is used in which the weighting factor is
`determined based on the ratio of the current product pur-
`chase amountto a cumulative product purchase amount. The
`cumulative product purchase amount can be measuredas the
`amount spent on a particular category of items(e.g. grocer-
`ies, clothes, accessories) over a given period oftime such as
`one month or one year.
`
`Ina preferred embodiment the heuristic rules are in
`[0023]
`the form of a product demographics vector which states the
`demographics of known purchasers of an item. Each product
`can have an associated product demographics vector.
`
`invention can be used to develop
`[0024] The present
`product preference descriptions of consumers which
`describe the brand and size product that they purchase, and
`which provide a probabilistic interpretation of the products
`they are likely to buy in the future. The product preference
`description can be generated by creating a weighted average
`of an existing product preference vector describing the
`consumer’s historical product preferences (type of product,
`brand, and size) and the characteristics of recent purchases.
`
`[0025] The present invention can be realized as a data
`processing system or computer program which processes
`consumer purchase records and updates their demographic
`and productpreference profiles based on the use of product
`characterization information. The data processing system
`can also be used to receive information regarding an adver-
`tisement and to perform a correlation between the adver-
`tisement and the consumer’s demographic and productpref-
`erences.
`
`[0026] The present invention can be realized as software
`resident on one or more computers. The system can be
`realized on an individual computer which receives informa-
`tion regarding consumer purchases, or can be realized on a
`network of computers in which portions of the system are
`resident on different computers.
`
`[0027] One advantage of the present invention is that it
`allows consumerprofiles to be updated automatically based
`on their purchases, and forms a description of the consumer
`including demographic characteristics and product prefer-
`ences. This description can be used by advertisers to deter-
`
`mine the suitability of advertisements to the consumer.
`Consumers benefit from the system since they will receive
`advertisements which are more likely to be applicable to
`them.
`
`[0028] The present invention can be used to profile con-
`sumers to support the correlation of an advertisement char-
`acterization vector associated with an advertisementwith the
`
`consumer characterization vector to determine the applica-
`bility of the advertisement to the consumer.
`
`invention is the
`[0029] Another feature of the present
`ability to price access to the consumer based on the degree
`of correlation of an advertisement with their profile. If an
`advertisement is found to be very highly correlated with a
`consumer’s demographics and product preferences, a rela-
`tively high price can be charged for transmitting the adver-
`tisement to the consumer. From the consumer’s perspective,
`if the correlation between the advertisement and the con-
`sumer’s demographics or product preferences is high the
`consumer can charge less to view the ad, since it is likely
`that is will be of interest.
`
`[0030] The present invention also describes a system for
`determining the applicability of an advertisement to a con-
`sumer, based on the reception of an ad characterization
`vector and use of a unique consumer ID. The consumer ID
`is used to retrieve a consumer characterization vector, and
`the correlation between the consumer characterization vec-
`tor and the ad characterization vector is used to determine
`
`the applicability of the advertisement to the consumer. The
`price to be paid for presentation of the advertisement can be
`determined based on the degree of correlation.
`
`Theprice to present an advertisement can increase
`[0031]
`with correlation, as may be typical when the content/oppor-
`tunity provider is also the profiling entity. The price can
`decrease with correlation when the consumeris the profiler,
`and is interested in, and willing to charge less for seeing
`advertisements which are highly correlated with their demo-
`graphics, lifestyle, and product preferences.
`
`[0032] The present invention can be used to specify pur-
`chasers of a specific product. In a preferred embodimentthe
`advertisement characterization vector contains a description
`of a target market including an indicatorof a target product,
`ie., purchasers of a particular product
`type, brand, or
`product size. The advertisement characterization vector is
`correlated with a consumercharacterization vector which is
`
`retrieved based on a unique consumer ID. Thecorrelation
`factor is determined and indicates if the consumer is a
`purchaser of the product the advertisement is intended for.
`This feature can be used to identify purchasers of a particular
`brand and can be used to target ads at those consumers to
`lure them away from their present product provider. Simi-
`larly, this feature can be used to target ads to loyal consum-
`ers to introduce them to a new product in a product family,
`or different size of product.
`
`invention is that
`[0033] One advantage of the present
`discretionary target market parameters can be specified and
`do not necessarily need to correspond to an existing market,
`but can reflect the various market segments for which the
`advertisement
`is targeted. The market segments can be
`designated by demographic characteristics or by product
`preferences.
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`
`[0034] Another advantage of the present invention is that
`demographic samples of present purchasers of a product are
`not required to define the target market.
`
`[0035] The present invention can be used to determine the
`applicability of an advertisement to a consumer based on
`demographics, product preferences, or a combination of
`both.
`
`Ina preferred embodimentofthe present invention
`[0036]
`the correlation is calculated as the scalar product of the ad
`characterization vector and the consumer characterization
`vector. The ad characterization vector and consumer char-
`
`acterization vector can be composed of demographic char-
`acteristics, product purchase characteristics, or a combina-
`tion of both.
`
`Ina preferred embodimentpricing for the display-
`[0037]
`ing of said advertisement is developed based on the result of
`the correlation between the ad characterization vector and
`the consumer characterization vector. In a first embodiment
`the pricing increases as a function of the correlation. This
`embodiment can represent the situation in which the party
`which determines the correlation also controls the ability to
`display the advertisement.
`
`In an alternate embodimenttheprice for displaying
`[0038]
`the advertisement decreases as a function of the degree of
`correlation. This embodiment can represent the situation in
`which the consumer controls access to the consumer char-
`
`acterization vector, and charges less to view advertisements
`which are highly correlated with their interests and demo-
`graphics. A feature of this embodimentis the ability of the
`consumer to decrease the number of unwanted advertise-
`
`ments by charging a higher price to view advertisements
`which are likely to be of less interest.
`
`[0039] One advantage of the present invention is that it
`allows advertisements to be directed to new markets by
`setting specific parameters in the ad characterization vector,
`and doesnot require specific statistical knowledge regarding
`existing customers of similar products.
`
`[0040] Another advantageis that the system allows ads to
`be directed at consumers of a competing brand, or specific
`targeting at loyal customers. This feature can be useful for
`the introduction of a new product to an existing customer
`base.
`
`[0041] Another advantage of the present invention is that
`the correlation can be performed by calculating a simple
`scalar (dot) product of the ad characterization and consumer
`characterization vectors. A weighted sum orotherstatistical
`analysis is not required to determine the applicability of the
`advertisement.
`
`[0042] The present invention can be realized as a data
`processing system and as a computer program. The inven-
`tion can be realized on an individual computer or can be
`realized using distributed computers with portions of the
`system operating on various computers.
`
`[0043] An advantageof the presentinventionis the ability
`to direct advertisements to consumers which will find the
`advertisements of interest. This eliminates unwanted adver-
`lisements. Another advantage is the ability of advertisers to
`target specific groups of potential customers.
`
`[0044] These and other features and objects of the inven-
`tion will be more fully understood from the following
`
`detailed description of the preferred embodiments which
`should be read in light of the accompanying drawings.
`
`BRIEF DESCRIPTION OF THE DRAWINGS
`
`[0045] The accompanying drawings, which are incorpo-
`rated in and form a part of the specification, illustrate the
`embodiments of the present invention and, together with the
`description serve to explain the principles of the invention.
`
`[0046]
`
`In the drawings:
`
`[0047] FIGS. 1A and 1B showuserrelationship diagrams
`for the present invention;
`
`[0048] FIGS. 2A, 2B, 2C and 2D illustrate a probabilistic
`consumer demographic characterization vector, a determin-
`istic consumer demographic characterization vector, a con-
`sumer product preference characterization vector, and a
`storage structure for consumer characterization vectors
`respectively;
`
`[0049] FIGS. 3A and 3B illustrate an advertisement
`demographic characterization vector and an advertisement
`product preference characterization vector respectively;
`
`[0050] FIG.4 illustrates a computer system on which the
`present invention can be realized;
`
`[0051] FIG.5 illustrates a context diagram for the present
`invention;
`
`[0052] FIGS. 6A and 6B illustrate pseudocode updating
`the characteristics vectors and for a correlation operation
`respectively;
`
`[0053] FIG.7 illustrates heuristic rules;
`
`[0054] FIGS. 8A and8Billustrate flowcharts for updating
`consumer characterization vectors and a correlation opera-
`tion respectively; and
`
`[0055] FIG. 9 represents pricing as a function of correla-
`tion.
`
`[0056] FIG.10 illustrates a representation of a consumer
`characterization as a set of basis vectors and an ad charac-
`terization vector.
`
`DETAILED DESCRIPTION OF THE
`PREFERRED EMBODIMENT
`
`In describin