Method and apparatus for delivering targeted content to website visitors

A method of selecting a website for delivery of targeted content to an audience member computer based on attitude values associated with audience members who participate in a computer implemented survey is disclosed. The survey response information, as well as website visitation information, and demographic information associated with the audience members may be collected and stored in a central database. An attitude value may be determined from the survey response information and/or the other information for the audience members. The attitude value may indicate the audience member's view about an issue, topic, product, service or the like. The attitude value in conjunction with other website visitation information may be used to select a website for delivery of the targeted content to the audience members.

FIELD OF THE INVENTION

The present invention relates to methods and apparatus for determining one or more optimal websites on which to display targeted content to a plurality of website visitors, referred to as audience members.

BACKGROUND OF THE INVENTION

The Internet is used by advertisers and other content providers to deliver website content, including but not limited to advertisements, to Internet audience members. There is a continuing need to deliver targeted content, meaning content that may be of particular interest to some but not all audience members, to audience members with particular attitudes or views. The ability of content providers and advertisers to select optimal websites for the delivery of targeted content to audience members with particular attitudes has been limited. Further, content providers and advertisers have been unable to select websites for the delivery of targeted content which are both likely to be visited by audience members with particular attitudes while at the same time unlikely to be visited by audience members with opposing attitudes. Accordingly, there is a need for improved methods and systems for delivering targeted content to audience members.

It is an advantage of some, but not necessarily all, embodiments of the present invention to provide methods and systems for selecting websites for the delivery of targeted content to audience members who are likely to have particular attitudes. It is also an advantage of some, but not necessarily all, embodiments of the present invention to provide methods and systems for selecting websites for the delivery of targeted content which are less likely to be visited by audience members who have opposing attitudes to those of the audience members to whom it is desired to deliver the targeted content.

Additional advantages of various embodiments of the invention are set forth, in part, in the description that follows and, in part, will be apparent to one of ordinary skill in the art from the description and/or from the practice of the invention.

SUMMARY OF THE INVENTION

Responsive to the foregoing challenges, Applicants have developed an innovative method of displaying content on a display connected to an audience member computer based on attitude values determined for audience members who participate in a computer implemented survey, and website visitation information and demographic information for the audience members, the method comprising: receiving at a central database survey response information transmitted over a computer network from participating audience member computers; receiving at the central database website visitation information for the participating audience member computers; receiving at the central database demographic information which is associated with the (i) participating audience members, and (ii) non-participating audience members from whom no survey response information is received; determining an attitude value for each of the participating audience members based on one or more of the survey response information using a non-audience member computer, the website visitation information and the demographic information; determining a Quality Visitation Index (QVI) value for a website from the website visitation information using the non-audience member computer, wherein the QVI value is based on a value selected from the group consisting of: a target group Reach Index, an opposing group Reach Index, a Net Support Score, a minutes per unique visitor Index, a pages per unique visitor Index, an ad clutter Index, a past performance Index, a minutes per page Index, and an ads per page Index; providing the content to the website based on the QVI value for the website; transmitting the content over the computer network to one of said participating or non-participating audience member computers as a result of one of said participating or non-participating audience member computers accessing the website; and displaying the content on the display connected to one of said participating or non-participating audience member computers.

Applicants have developed an innovative method of transmitting content for viewing on a display connected to an audience member computer based on attitude values determined for audience members who participate in a computer implemented survey, and website visitation information and demographic information for the audience members, the method comprising: receiving at a central database survey response information transmitted over a computer network from participating audience member computers; receiving at the central database website visitation information for the participating audience member computers; receiving at the central database demographic information which is associated with the (i) participating audience members, and (ii) non-participating audience members from whom no survey response information is received; determining an attitude value for each of the participating audience members using a non-audience member computer based on one or more of the survey response information, the website visitation information and the demographic information; determining a Quality Visitation Index (QVI) value for a website from the website visitation information and attitude values using the non-audience member computer; providing content to the website based on the QVI value for the website; and transmitting the content over the computer network to one of said participating or non-participating audience member computers as a result of one of said participating or non-participating audience member computers accessing the website.

Applicants have further developed an innovative method of determining content for display on a website, the method comprising: receiving at a central database survey response information transmitted over a computer network from participating audience member computers; receiving at the central database website visitation information for the participating audience member computers; receiving at the central database demographic information which is associated with the (i) participating audience members, and (ii) non-participating audience members from whom no survey response information is received; determining an attitude value for each of the participating audience; determining a Quality Visitation Index (QVI) value for a website from the website visitation information and attitude values; and providing content to the website based on the QVI value for the website.

DETAILED DESCRIPTION OF EMBODIMENTS OF THE INVENTION

Reference will now be made in detail to a first embodiment of the present invention, an example of which is illustrated in the accompanying drawings. With reference toFIG. 1, the computer network10may include a computer100which may be a special use computer with permanent programming to accomplish the methods described herein, or a general use computer programmed with software to permit it to accomplish the methods described herein. The computer100may receive information from and store information in a central database110via a connection124. The computer100may also be connected to a network200via a connection130. The network200is preferably the Internet. The connections124and130may be any connection means that permit the transmission of electronic information.

The central database110may comprise one or more individual databases and/or database tables for storing information used by the computer100. The information stored in the central database110may include survey response information112, demographic information114, website visitation information116, attitude value information118, Quality Visitation Index (QVI) information120, net support score information122, as well as any other information discussed herein which is capable of being stored in a database. The central database110may associate survey response information, demographic information, website visitation information, and attitude value information with an anonymous identifier for a participating audience member and/or participating audience member computer that the information relates to.

The network200may be connected to a plurality of participating audience member computers300, which in turn are connected to displays302, and which are associated with a plurality of participating audience members304. The participating audience members304may use the computers300to access websites from one or more web servers500which form part of the world wide web and are connected via the Internet200. “Participating” audience member computers300and “participating” audience members304are referred to as “participating” because each is used to participate in providing online survey response information to the computer100. Visual and audible website content may be transmitted from the one or more web servers500and displayed by the participating audience member computers300on the displays302for viewing and listening by the participating audience members304. The network200may also be connected to a plurality of non-participating audience member computers306which are associated with non-participating audience members310.

Online survey questions stored in the central database110may be transmitted from the computer100to the participating audience member computers300. Participating audience members304may use their respective computers300to transmit online survey response information (i.e., answers to the online survey questions) over the Internet200to the computer100. Website visitation information for the participating audience member computers300may also be transmitted for the participating audience members over the Internet200to the computer100. In an alternative embodiment, the online survey questions may be stored in one or more of the third party databases402associated with one or more third party computers400. In such embodiment, the online survey questions may be sent from the third party computers400to the participating audience members304. Thereafter, the survey response information may be sent from the participating audience member computers300to the computer100directly through the Internet, or alternatively through the one or more third party computers400.

The computer100may also be connected to or otherwise receive information from one or more computers400and associated databases or database tables402maintained by one or more third party data providers. The third party data provider computers400and associated databases or database tables402may store demographic information and/or website visitation information relating to a plurality of non-participating audience members310, and potentially relating to one or more of the plurality of participating audience members304. The third party data provider computers400may receive non-participating audience member demographic information from non-participating audience member computers306and/or from other online and/or offline sources. The non-participating audience member demographic information may be transmitted from the third party computers400over an Internet connection410to the computer100, or by an alternative means420such as a direct electrical signal connection or via electronic information storage media. Examples of third party data providers include, but are not limited to, the Nielsen Company, comScore, and Acxiom.

The computer100may be connected to or otherwise receive information from one or more web servers500. The web servers500may transmit website content over connection510and the Internet200to the participating audience member computers300as well as computers306and displays associated with the non-participating audience members310. Information may be transmitted between the computer100and the web servers500over the Internet200, or by an alternative means520such as a direct electrical signal connection or via electronic information storage media.

With reference toFIGS. 1 and 2, a method in accordance with an embodiment of the present invention may be carried out as follows. The method600may be used to select one or more websites to display content on the displays302connected to participating and/or non-participating audience member computers300and306. The content may be targeted for display as part of one or more websites which are visited by audience members304and310who are determined to likely have one or more particular attitudes represented by one or more attitude values.

With reference toFIG. 2, in step602the participating audience members304may use the participating audience member computers300to provide online survey response information112to the computer100. The online survey response information112may be provided as the result of a participating audience member304using the associated participating audience member computer300to request the online survey, or as a result of the computer100, or alternatively some other computer, directing an unsolicited online survey to a participating audience member computer300. The computer100may store the survey response information112in the central database110, and associate the survey response information for a particular participating audience member304with an anonymous identifier for the particular participating audience member computer300and/or the particular participating audience member304.

Preferably, but not necessarily, survey response information112may be collected from at least 1,000 participating audience member computers300, more preferably from at least 3,000 participating audience member computers, and most preferably from 4,000 or more participating audience member computers. It is also preferable to receive survey response information112from the participating audience member computers300over the course of multiple survey “waves” separated in time. Preferably, the survey “waves” are received more than a day apart, more preferably more than 30 days apart, and most preferably about three or more months apart. It is also preferable for the participating audience members304to provide survey response information112in response to more than two survey waves. The survey questions in each of the survey waves may be the same or different.

The survey response information112may also include demographic information associated with the participating audience members304. The participating audience member demographic information which is part of the survey response information112may include the following types of information: age, income, gender, census region, race, sexual orientation, education level, religious affiliation, frequency of attendance at religious services, union participation, frequency of Internet use information, and the like. It is appreciated that the foregoing list of demographic information is non-limiting and that embodiments of the present invention may utilize any types of demographic information that relates to audience members.

With renewed reference toFIG. 2, in step604demographic information114(other than that which may be included in the survey response information112) may be received by the computer100for participating and/or non-participating audience members. The demographic information114may be collected for the non-participating audience members310and the participating audience members304by the one or more third parties, or derived from other sources of online and/or offline information. The third parties may collect or derive the demographic information114in any known manner, including, but not limited to tracking the online behavior of the non-participating audience members310and/or participating audience members304. It is appreciated that the demographic information114which is associated with non-participating audience members310and/or associated with the participating audience members304may be collected by the host of the computer100instead of by one or more third parties in an alternative embodiment of the present invention.

The demographic information114pertaining to a particular participating audience member may be associated with the anonymous identifier for the participating audience member304in the central database110by the computer100. Similarly, demographic information114pertaining to a particular non-participating audience member may be associated with an anonymous identifier for the non-participating audience member310in the central database110by the computer100. Further, the demographic information114may be provided multiple times, preferably at least once per wave, and more preferably at least once per month.

The demographic information114, as it pertains to participating audience members304, may be stored in the central database110so as to be associated with the same anonymous identifier used in connection with the survey response information112. The demographic information114, as it pertains to non-participating audience members310, may not be specific to individual non-participating audience members, but instead descriptive of a large group of online audience members. For example, the demographic information114as it pertains to non-participating audience members310may be collected for a number of audience members in a common geographic area, such as the United States, or a number of audience members in any other group which may be characterized as having some common affiliation, such as political, income, ethnic, racial, religious, age, gender, or the like. More specifically, in a preferred embodiment of the present invention, the demographic information114pertaining to non-participating audience members310may be received or stored such that it pertains to individual non-participating audience members defined by age ranges, gender, household income ranges, census regions, and intensity of Internet use (Heavy/medium/light), etc.

With continued reference toFIGS. 1 and 2, in step606, website visitation information116pertaining to the participating audience member computers300, and potentially pertaining to the non-participating audience member computers306, may be received by the computer100. The website visitation information116may be collected for the participating audience member computers300and the non-participating audience member computers306directly by the computer100, or alternatively from the one or more third party computers400and/or associated databases402. It is appreciated, however, that embodiments of the present invention may be practiced without receiving website visitation information116pertaining to the non-participating audience member computers306.

While it is preferable to track such website visitation information for all participating audience member computers300over a period of one to three months or more (i.e., a wave), it is appreciated that, without departing from the intended scope of the present invention, some participating audience member computers may “drop out” of the tracking process and therefore website visitation information for such participating audience member computers may only be available over the course of more than one session, day, or week, as opposed to one to three months.

The website visitation information116may be received by the central database110from the computer100and stored therein. The tracking of the website visitation information116may be implemented by using software installed on participating and non-participating audience member computers300and306, by cookies for tracking such information, or any other manner of tracking the online behavior of an audience member.

The website visitation information116may include, but is not necessarily limited to, website URL information, website channel visitation information, website page visitation information, session information, online purchase information, search term information, visitation time information, visitation duration information, visitation date information, and website page clutter information. A session is defined by a visit to a website. Internet traffic metrics such as the number of unique visitors to a website, website channel, and/or website page during a time period (i.e., “unique visitors”), number of visits to a website, website channel, and/or website page during a time period (i.e., “visits”), number of website pages for a website that are viewed during a time period (i.e., “pages viewed”), and the number of minutes spent on a website during a time period, may be part of and/or derived from the website visitation information116. A unique visitor to a website during a time period is defined as an audience member computer that has visited the website one or more times during the time period. If an audience member computer visits the website more than once during the time period, the audience member computer is still counted only as one unique visitor during the time period.

A website channel may fit hierarchically between a website and a website page. An example of a website is MSN.com, and an example of a website channel is the collection of website pages which are accessed from the “Sports” button on the MSN.com home page. References herein to a “website” are intended to be inclusive of a website in its entirety, a website channel, and a website page unless otherwise defined.

Website page clutter information may be based on one or more of: page length, number of advertisements on a page, location of advertisements on a page, percentage of the surface area of a page taken up with advertisements information (e.g., by pixel count), and size of advertisements on a page information. More specifically, website page clutter may take into account the relative number and placement of pixels on a website page that are used to display advertisements as opposed to other content, as well as the prominence of such advertisements as compared with the non-advertising content on the page. For example, any one of the following may correlate with a higher website page clutter value: more advertisements as compared with fewer, smaller advertisements as compared with larger, and top of page advertisements as compared with bottom of the page.

In step608ofFIG. 2, weight factors may be determined for participating audience members based on a comparison by computer100of the demographic information114for participating audience members304with the demographic information for non-participating audience members310. The weight factors may be used to weight the website visitation information116and other characteristics pertaining to the participating audience members304so that the population of participating audience members in terms of demographic groupings by age, gender, etc., projects more closely to the demographic distribution of the overall online population in terms of the same demographic groups in the same time period.

In step610ofFIG. 2, attitude values associated with the participating audience members304may be determined based on the survey response information112, the demographic information114and/or the website visitation information116. The attitude values may indicate the participating audience member's political attitude, legislative attitude, regulatory attitude, corporate attitude, and/or product attitude.

In step612, the reach of each website to a target group of participating audience members having a selected attitude value or values, and the reach of all websites to an opposing group of participating audience members having an attitude value or values dissimilar to the selected attitude values of the target group may be determined. The determined reach may indicate the number of participating audience members in the target group and in the opposing group that visit each website.

In step614ofFIG. 2, one or more websites may be selected to include content which is targeted to the target group and which is not targeted to the opposing group based on a comparison of the reach of the website to the target group with the reach of the website to the opposing group. In one example, it may be preferred to select a website for delivery of targeted content which has the largest differential in terms of reach between the target group and the opposing group.

In step616ofFIG. 2, the targeted content may be displayed by the participating and non-participating audience member computers300and306as a result of the computers visiting the website or websites selected in step614.

The weight factors referenced in connection with step608ofFIG. 2may be determined using the method illustrated inFIGS. 10A and 10B. With reference toFIGS. 10A and 10B, in step800, each participating audience member in a selected analysis period and in the same demographic group (e.g., age group) may be assigned an equal initial weight value. The analysis period may be any period of time over which website visitation information is available for the participating audience members304. Preferably the analysis period will be more than one month, and more preferably at least about 3 months. The method illustrated inFIGS. 10A and 10Bis preferably carried out for each month's worth of information in the analysis period.

In step801ofFIG. 10A, the demographic distribution by percentage of the participating audience members304in terms of age group may be determined by the computer100from the demographic information114. Examples of age groups in years are 18-24, 25-34, 35-44, 45-54, 55-64, and 65 and over. It is appreciated that other age groups could be used without departing from the intended scope of the present invention. In step802, the demographic distribution by percentage in terms of age group of the online population for a geographic region such as the United States may be determined by the computer100from the demographic information114. The online population is comprised almost entirely, if not entirely, of the non-participating audience members310, but may include to some small degree the participating audience members304as well. In step804, an age weight factor may be calculated using the computer100by dividing the demographic distribution of the online population in terms of age group by the demographic distribution of the participating audience members304in terms of a corresponding age group. For example, for the age group 18-24, an age weight factor may be calculated by dividing the demographic distribution by percentage of the online population in the 18-24 year old range by the demographic distribution by percentage of the participating audience members304in the same age range. The age weight factor may be stored by the computer100in the central database110.

In step806ofFIG. 10A, the demographic distribution by percentage of the participating audience members304in terms of gender group may be determined by the computer100from the demographic information114. Examples of gender groups are male and female. In step808, the demographic distribution by percentage in terms of gender group of the online population may be determined by the computer100from the demographic information114. In step810, a gender weight factor may be calculated using the computer100by dividing the demographic distribution in terms of gender of the online population by the demographic distribution of the participating audience members304in terms of a corresponding gender group. The gender weight factor may be stored by the computer100in the central database110.

In step812ofFIG. 10A, the demographic distribution by percentage of the participating audience members304in terms of household income group may be determined by the computer100from the demographic information114. Examples of household income groups are: under $25,000, $25,001-$50,000, $50,001-$75,000, etc. In step814, the demographic distribution by percentage in terms of household income group of the online population may be determined by the computer100from the demographic information114. In step816, a household income weight factor may be calculated using the computer100by dividing the demographic distribution in terms of household income of the online population by the demographic distribution of the participating audience members304in terms of a corresponding household income group. The household income weight factor may be stored by the computer100in the central database110.

In step818ofFIG. 10A, the demographic distribution by percentage of the participating audience members304in terms of census region may be determined by the computer100from the demographic information114. In step820, the demographic distribution by percentage in terms of census region of the online population may be determined by the computer100from the demographic information114. In step822, a census region weight factor may be calculated using the computer100by dividing the demographic distribution in terms of census region of the online population by the demographic distribution of the participating audience members304in terms of a corresponding census region. The census region weight factor may be stored by the computer100in the central database110.

In step824ofFIG. 10A, the demographic distribution by percentage of the participating audience members304in terms of Internet use during a period of time (Heavy/medium/light) may be determined by the computer100from the demographic information114. Examples of Internet use groupings are: Heavy—more than 3430 minutes per month; light—less than 300 minutes per month; and medium—everyone else. In step826, the demographic distribution by percentage in terms of Internet use of the online population may be determined by the computer100from the demographic information114. In step828, an Internet use weight factor may be calculated using the computer100by dividing the demographic distribution in terms of Internet use of the online population by the demographic distribution of the participating audience members304in terms of a corresponding Internet use grouping. The Internet use weight factor may be stored by the computer100in the central database110.

In steps830-848, each of the subroutines pertaining to determination of the age group, gender group, household income group, census region, and Internet use groupings set forth in steps801-828may be repeated until the multiplication of the determined weight factor by the corresponding demographic distribution by percentage of the participating audience members304results in a product that is approximately the same as the demographic distribution by percentage of the online population of the same demographic metric. For example, steps830-848are repeated iteratively until the multiplication of the age group weight factor by the demographic distribution by percentage in terms of age of the participating audience members304results in a product that is approximately the same as the demographic distribution by percentage of the online population in terms of age. The process is further iterated until the resulting demographic distributions on a demographic category-by-category basis are also approximately the same for each demographic category such as gender, household income, census region, and Internet use. Values are considered to be “approximately the same” in the foregoing steps when continued iteration of the process does not result in any substantial change to the values from one iteration to the next. It should also be appreciated that the selection of the demographic information114used in the foregoing example is considered to be non-limiting of the present invention. Fewer, more, and/or different demographic information114may be used in steps801-848without departing from the intended scope of the invention.

Steps800-848are repeated for each of a number of individual time periods which may make up the analysis period. Preferably, steps800-848are repeated for each month of data that is available for the participating audience members304. For example, if the analysis period is a three month period, steps800-848may be carried out three times to generate three sets of weight factors corresponding each individual month's demographic distributions.

In step850ofFIG. 10A, for each participating audience member304for each preselected time period, the computer100may sum the weight factors determined in steps801-848across each time period (e.g., month) in the analysis period and across all weight factors as they apply to each particular participating audience member. The resulting sum may be stored in the central database110in association with the anonymous identifier for the participating audience member. For example, for a 20 year old, male participating audience member who earns $45,000 per year, lives in the Northeast U.S., and uses the Internet 500 minutes per month, the computer100may sum the 18-24 year old group, male gender group, $25,001-$50,000 household income group, Northeast U.S. census region, and medium Internet use weight factors calculated for each of three months of demographic information, and store such sum in association with the anonymous identifier for the participating audience member in the central database110.

In step852, the size of the total online population for the analysis period may be determined by the computer100from the demographic information114. For example, if the online population was 160 million individuals in month one, 170 million individuals in month two, and 180 million individuals in month three of the analysis period, the total online population for the analysis period would be 510 million online users.

In step854, the computer100may calculate a projection factor for each participating audience member304, which is the quotient of the size of the online population determined in step852divided by the sum of the weights calculated in step850. In step856, a projection weight for each participating audience member304may be calculated using the computer100by multiplying the weight assigned to the particular participating audience member in step800by the projection factor calculated in step854.

The projection factors for the participating audience members304which were determined as a result of carrying out the process set forth inFIGS. 10A-10Bmay be utilized in a the process shown inFIGS. 11A and 11Bto determine a Quality Visitation Index (QVI) value, which in turn is used to determine which website(s) may be selected to deliver targeted content to the participating and non-participating audience members. With reference toFIG. 11A, in step900an analysis period is selected which should preferably be the same analysis period used in connection with the process set forth inFIGS. 10A-10B.

In step902, the projection factors for the participating audience members304may by applied by the computer100to the website visitation information and other characteristics associated with the participating audience members to produce projected website visitation information and projected characteristic information. “Projected” information, essentially scales up or down the information related to an individual participating audience member so that the information relating to a particular participating audience member is proportional to the make up of the demographic groups (by age, gender, etc.) that the participating audience member is a part of. For example, the projection factor for a particular participating audience member304may be multiplied by the following website visitation information116that pertains to the same participating audience member for the analysis period: number of visits to websites; number of minutes spent on websites, channels, and/or pages; number of sessions; number of online purchases; and website visitation duration.

In step904, the computer100may determine the projected monthly traffic metrics for each website visited by one or more participating audience members for each month in the analysis period using the website visitation information116. The traffic metrics determined for each website may include, but are not necessarily limited to: the number of unique visitors; the number of visits; the number of pages viewed; which pages were viewed; the amount of time (e.g., number of minutes) spent visiting the website; number of advertisements per page; and percentage of the surface area of a page taken up by advertisements. The determination of the traffic metrics for a website may be influenced by the projection factors referenced above. For example, if a single participating audience member304has a projection factor of “2”, and the participating audience member spent 10 minutes visiting a website, it may be counted as spending 20 minutes visiting the website due to the projection factor.

In step906, the projected monthly traffic metrics determined in step904may be combined (i.e., summed) by the computer100. Discount factors may be applied to the monthly traffic metrics before combining them to account for the decreased value of traffic metrics that pertain to an earlier month. For example, if the analysis period consists of the preceding three months of traffic metrics, the traffic metrics for the first month in the analysis period may be multiplied by a discount factor of 0.5, and the traffic metrics for the second month may be multiplied by a discount factor of 0.75. The foregoing examples of discount factors are illustrative only, and not considered limiting to the intended scope of the present invention. The combined monthly traffic metrics may be stored in the central database110by the computer100.

In step908, the overall reach of each website visited by one or more participating audience members304may be calculated by the computer100using the website visitation information116. The overall reach may be the quotient of the number of projected participating audience member unique visits to the website divided by the total number of projected participating audience members for the analysis period. The overall reach of each website may be stored by the computer100in the central database110.

In step910, the computer100may determine the projected number of minutes spent visiting each website per projected participating audience member unique visitors (min/UV) using the website visitation information116. The (min/UV) for each website may be stored by the computer100in the central database110.

In step912, the computer100may determine the number of participating audience members304that were unique visitors to each website using the website visitation information116. The number of unique visitors for each website may then be compared with a threshold number of unique visitors that is required for the website to be further considered for delivery of targeted content. For example, if a website had only 40 unique visitors during the analysis period and the threshold value is 50 unique visitors during the analysis period, the computer100would determine that the subject website should not be considered further for the delivery of targeted content. The computer100may store an indication in the central database110of which websites are and/or are not to be considered further for the delivery of targeted content.

In step914, the computer100may determine which of the participating audience members qualify as being in the target group of participating audience members to which the targeted content is to be directed. The target group of participating audience members may be determined by using the computer100to determine one or more attitude values for each of the participating audience members. The determined attitude values for the participating audience members may then be compared by the computer100with a selected attitude value threshold and/or an attitude value range. If the attitude value for a particular participating audience member satisfies the selected attitude value threshold and/or range, then the participating audience member may be indicated to be part of the target group by the computer100.

The survey response information112may be used to determine an attitude value for a participating audience member304either directly or indirectly. For example, with reference toFIG. 3, the survey response information112may include the responses of the participating audience members304to an issue question700concerning government regulation of nuclear power plants. The participating audience members304may use the participating audience member computers300to indicate their attitude about such regulation by selecting one of the attitudes provided in the menu702which range from “strongly oppose” to “strongly support.” The survey response information112for a particular issue may result in a tally704which is graphically represented inFIG. 3to indicate the percentage number of participating audience members304who characterized themselves as having each of the corresponding attitudes. The survey response information112of each participating audience member304relating to each issue question700may be stored in the central database110.

With additional reference toFIG. 4, in addition to answers to the issue questions700, the survey response information112may further include answers to political orientation questions710, level of engagement questions720, and voting history/party affiliation questions730. Political orientation questions710are more general in character than issue questions700. An example of an issue question is provided inFIG. 3, as compared with the following examples of political orientation questions710:

Are you opposed to government regulation of business?

Are you opposed to government provided healthcare?

How often do you vote?

What elections do you normally participate in as a voter?

What political party or parties are you a member of?

The foregoing examples of issue questions700, political orientation questions710and voting history/party affiliation questions730are intended to be illustrative and non-limiting of the intended scope of the present invention. It is appreciated that one or more of these types of questions (i.e., issue, political orientation, and voting history/party affiliation) may not be included in the survey response information112without departing from the intended scope of the present invention.

Additionally, level of engagement questions720which may be included in the survey response information112may be used to determine one or more level of engagement values for each participating audience member304on one or more engagement scales illustrated byFIGS. 5-9. The three engagement scales illustrated inFIGS. 5-9are a general engagement scale, a political engagement scale, and an advocacy engagement scale. The number and type of engagement scales, as well as the associated definitions, levels and values used in connection with the scales are considered to be illustrative only and non-limiting of the invention which may be carried out without any engagement scales whatsoever.

With additional reference toFIG. 5, the survey response information112may indicate that a particular participating audience member304has taken one or more of the general engagement actions722listed inFIG. 5. Each of the illustrative general engagement actions722may be associated with an action value shown in the left column of chart724by the computer100. The computer100may compare the survey response information112for each participating audience member304with the actions722to determine the general engagement levels in the chart726shown inFIG. 6that should be attributed to the participating audience member. The action values that the survey response information112indicates should be attributed to a participating audience member304may be added together by the computer100to aggregate a cumulative general engagement value. With reference toFIG. 6, each of four illustrative general engagement value ranges726are illustrated, ranging from “non-engaged” which is associated with a cumulative general engagement value of 0 to a “high” level of engagement associated with a cumulative general engagement value in the range of 13-38. The cumulative general engagement value for each participating audience member304may be stored by the computer100in the central database110in association with the anonymous identifier for the participating audience member.

With reference toFIG. 7, the survey response information112may further indicate that a particular participating audience member304satisfies one or more of the political engagement definitions730shown in chart728. Based on a comparison of the survey response information112with the definitions730by the computer100, the participating audience member304may be associated with one of the political engagement levels732and associated political engagement values734on the illustrative political engagement scale. As indicated in the chart728, the political engagement levels732and associated values734may be hierarchal such that a participating audience member304must satisfy the requirements of the preceding lower level in order to be eligible to satisfy the definition730of the next higher level. The political engagement value734for each participating audience member304may be associated with the anonymous identifier for the participating audience member by the computer100in the central database110.

With reference toFIG. 8, the survey response information112may further indicate that a particular participating audience member304has taken one or more of the advocacy engagement actions shown in the chart736. In the illustrative example shown, each advocacy engagement action may be placed in one of four groups: private actions738, active involvement actions740, integrated political actions742, and public/high level involvement actions744. With reference toFIGS. 8 and 9, a particular participating audience member304may be associated with one of the advocacy engagement levels748and corresponding advocacy engagement values750shown in the chart746based on a comparison implemented by the computer100between (i) the advocacy engagement actions indicated in the participating audience member's survey response information112and (ii) the advocacy engagement level descriptions752. The advocacy engagement value750corresponding to the advocacy engagement level748that the participating audience member304qualifies for may be associated by the computer100with the anonymous identifier for the participating audience member in the central database110.

With renewed reference toFIGS. 6-9, one or more of the cumulative general engagement values726, the political engagement values734, and the advocacy engagement values750may be used in the determination of the attitude value118for each participating audience member. Determination of the attitude value118may be further based on website visitation information114and/or demographic information116. Preferably, the attitude value information118is determined from the combination of survey response information112, the website visitation information116, and the demographic information114associated with the particular participating audience member computer300.

With renewed reference toFIG. 11A, in step916, the computer100may determine the projected monthly traffic metrics for each website visited by the participating audience members304in the target group for each month in the analysis period using the website visitation information116. The traffic metrics determined for each website may include the same metrics as referenced in connection with step904, and may be influenced by the projection factors in the same manner as in step904.

In step918, the projected monthly traffic metrics determined in step916may be combined (i.e., summed) by the computer100in the same manner as set forth in connection with step906. Discount factors may be applied to the monthly traffic metrics before combining them to account for the decreased value of traffic metrics that pertain to an earlier month. The combined projected monthly traffic metrics may be stored in the central database110by the computer100.

In step920, the target group reach of each website visited by the participating audience members304in the target group may be calculated by the computer100using the website visitation information116. The target group reach may be the quotient of the number of projected unique visitors to the website audience members in the target group divided by the total number of projected participating audience members in the target group for the analysis period. The target group reach of each website may be stored by the computer100in the central database110.

In step922, the computer100may determine the number of minutes spent visiting each website per projected participating audience member unique visitor in the target group (target group min/UV) using the website visitation information116. Alternatively, or in combination with the target group min/UV, the computer100may determine website pages/UV. The target group min/UV may be determined by totaling the number of minutes spent visiting a website by all of the projected participating audience member computers associated with the target group divided by the number of participating audience member unique visitors who are in the target group. The target group pages/UV may be determined by totaling the number of pages visited by all of the projected participating audience member computers associated with the target group divided by the number of participating audience member unique visitors who are in the target group.

In step924, the computer100may determine the number of participating audience members304in the target group that were unique visitors to each website using the website visitation information116. The number of participating audience members304in the target group who were unique visitors for each website may then be compared with a threshold number of unique visitors that is required for the website to be further considered for delivery of targeted content in the same manner as set forth in connection with step912. The computer100may store an indication in the central database110of which websites are and/or are not to be considered further for the delivery of targeted content based on the outcome of this step.

In step926, the computer100may calculate a target group Reach Index for each website still under consideration for use in the delivery of targeted content. The target group Reach Index may be the quotient of the target group reach for each website determined in step920divided by the overall reach of each website determined in step908. The target group Reach Index may be stored by the computer100in the central database110.

In step928, the computer100may calculate a minutes per unique visitor Index for each website still under consideration for use in the delivery of targeted content. The minutes per unique visitor Index may be the quotient of the number of minutes spent visiting each website per projected participating audience member unique visitor in the target group determined in step922divided by the number of minutes spent visiting each website per projected participating audience member unique visitor determined in step910. The minutes per unique visitor index and/or the pages per unique visitor index may be restrained to a predefined range, 0.7 to 1.3 in a preferred embodiment. The target group min/UV and/or target group pages/UV for each website may be stored by the computer100in the central database110.

The minutes per unique visitor Index may be stored by the computer100in the central database110.

In step930, the computer100may calculate a minutes per page Index for each website still under consideration for use in the delivery of targeted content. The minutes per page Index may be the quotient of the average number of minutes per page for participating audience members304on a website divided by the average number of minutes per page for participating audience members on all websites in the same website category. For example, if the website under consideration is CNN.com, the average number of minutes per page that the participating audience members304spent on CNN.com would be divided by the average number of minutes per page that the online population spent visiting all news-related websites. The minutes per page Index may be restrained to a predefined range, 0.7 to 1.3 in a preferred embodiment. The minutes per page Index may be stored by the computer100in the central database110.

In step932, the computer100may calculate an advertisement (ad) clutter Index for each website still under consideration for use in the delivery of targeted content. The ad clutter Index may be the quotient of an ad clutter metric for a website divided by an ad clutter metric associated with other websites in the same website category. For example, the ad clutter metric(s) used may be an indication of the location of advertisements on a page, the size of advertisements on a page and/or the number of pixels dedicated to advertisements on a page. The ad clutter Index may be stored by the computer100in the central database110.

In step934, the computer100may calculate an advertisements (ads) per page Index for each website still under consideration for use in the delivery of targeted content. The ads per page Index may be the quotient of the average number of ads per page on the website under consideration divided by the average number of ads per page on other websites in the same website category. The ads per page Index may be stored by the computer100in the central database110.

In step936, the computer100may calculate a past performance Index for each website still under consideration for use in the delivery of targeted content. The past performance Index may be the quotient of a metric used to measure the past performance of a website used in an advertising campaign divided by a metric used to measure the performance of all other or a collection of other websites used in similar advertising campaigns. Examples of past performance metrics may include, but are not limited to click through rates and conversion rates, where a “conversion” may be a purchase, a donation, contacting a politician, or joining an online community. The past performance Index may be stored by the computer100in the central database110.

In step938, the computer100may determine which of the participating audience members qualify as being in an opposing group of participating audience members to which the targeted content is not to be directed. The opposing group may be defined as having attitude values which are the most dissimilar to those of the target group referenced in connection with step914. As with the target group, the opposing group of participating audience members may be determined by using the computer100to determine one or more attitude values for each of the participating audience members. The determined attitude values for the participating audience members may then be compared by the computer100with a selected opposing attitude value threshold and/or an attitude value range. If the attitude value for a particular participating audience member satisfies the selected opposing attitude value threshold and/or range, then the participating audience member may be indicated to be part of the opposing group by the computer100.

In step940, the computer100may determine the projected monthly traffic metrics for each website visited by the participating audience members304in the opposing group for each month in the analysis period using the website visitation information116. The projected traffic metrics determined for each website may include the same metrics as referenced in connection with step904, and may be influenced by the projection factors in the same manner as in step904. The projected monthly traffic metrics for each website visited by the participating audience members304in the opposing group, as well as in the target group, may be stored by the computer100in the central database110.

In step942, the projected monthly traffic metrics determined in step940may be combined (i.e., summed) by the computer100in the same manner as set forth in connection with step906. Discount factors may be applied to the monthly traffic metrics before combining them to account for the decreased value of traffic metrics that pertain to an earlier month. The combined monthly traffic metrics may be stored in the central database110by the computer100.

In step944, the opposing group reach of each website visited by the participating audience members304in the opposing group may be calculated by the computer100using the website visitation information116. The opposing group reach may be the quotient of the number of projected unique visitors to the website by projected participating audience members in the opposing group divided by the total number of projected participating audience members in the opposing group for the analysis period. The opposing group reach of each website may be stored by the computer100in the central database110.

In step946, the computer100may determine the number of participating audience members304in the opposing group that were unique visitors to each website using the website visitation information116. The number of participating audience members304in the opposing group who were unique visitors for each website may then be compared with a threshold number of unique visitors that is required not to be surpassed in order for the website to be further considered for delivery of targeted content in the same manner as set forth in connection with step912. The computer100may store an indication in the central database110of which websites are and/or are not to be considered further for the delivery of targeted content based on the outcome of this step.

In step948, the computer100may calculate an opposing group Reach Index for each website still under consideration for use in the delivery of targeted content. The opposing group Reach Index may be the quotient of the opposing group reach for each website determined in step944divided by the overall reach of each website determined in step908. The opposing group Reach Index may be stored by the computer100in the central database110.

In step950, a Net Support Score (NSS) may be calculated by the computer100by subtracting the opposing group Reach Index from the target group Reach Index or more preferably by dividing the opposing group Reach Index by the target group Reach Index. The Net Support Score may be used to identify websites for the delivery of targeted content which are (i) more likely to be visited by participating and non-participating audience members304and310who have attitude values (i.e., attitudes) that are similar to those of the target group, and (ii) less likely to be visited by participating and non-participating audience members who have attitude values (i.e., attitudes) that are similar to those of the opposing group. The NSS for each website may be ranked by the computer to identify those websites which are more favorable for the delivery of targeted content to participating and non-participating audience members. An example of the ranking of websites by a NSS value is shown inFIG. 12. The NSS for each website and an indication of the ranking of each website may be stored by the computer100in the database110.

In an alternative embodiment, the NSS may be calculated by multiplying the opposing group Reach Index by a minutes per unique visitor Index for the opposing group, and then subtracting or dividing the result from result of the target group Reach Index multiplied by a minutes per unique visitor Index for the target group. The minutes per unique visitor Index for the target group may be determined by the computer100as stated in connection with step922, above. The minutes per unique visitor Index for the opposing group may be determined by the computer100using the website visitation information116in the same manner as set forth for the target group in step922The (target group min/UV) for each website may be stored by the computer100in the central database110.

In step952, a Quality Visitation Index (QVI) value may be determined for each website by the computer100based on one or more of the target group Reach Index, opposing group Reach Index, NSS, minutes per unique visitor Index, ad clutter Index, past performance Index, minutes per page Index, and ads per page Index. More specifically, in one embodiment of the present invention one or more of the foregoing indices and the NSS may be multiplied together to produce a QVI value. In another embodiment of the invention, one or more of the indices and the NSS may also be multiplied by a discretionary factor which gives the particular index or the NSS heavier or lighter weight in the QVI determination. In still another embodiment of the invention, the exponential value of one or more of the indices and the NSS may be multiplied together to produce a QVI value.

The QVI value determined in step952may be compared with a threshold QVI value, a range of QVI values, or ranked against other QVI values for other websites to determine an optimal website for the delivery of targeted content. Examples of the ranking of websites by QVI values are shown inFIGS. 12 and 13. If the determined QVI value exceeds the threshold QVI value or falls within a prescribed QVI value range, the website in question may be selected for inclusion of content which is believed to be desirable to members of the target group. Alternatively, if the QVI value of a particular website ranks highly as compared to the QVI values of other websites, the website in question may be selected for inclusion of content which is believed to be desirable to members of the target group.

Once a website or websites are selected to be used to deliver the targeted content to the participating and/or non-participating audience members based on the determined QVI value for the website(s), the content may be transmitted to one or more web servers500(FIG. 1), and from the one or more web servers over the network200to one or more of the audience member computers300and/or306as a result of the audience member computers visiting the website in question. Thereafter the audience member computers may display the content on an associated display or connected display302. The content to be transmitted to the web servers500may be stored in memory associated with the one or more third party computers400or may be stored in memory associated with the computer100.

It will be apparent to those skilled in the art that variations and modifications of the present invention can be made without departing from the scope or spirit of the invention.