Invented by Kumar Nagaraja Rao, William Rene Waldron, Neung Soo Ha, Billie Jo Kline, Michael Morgan, Nielsen Co US LLC

In today’s digital age, cross-platform campaigns have become increasingly popular among advertisers. With the rise of social media, mobile devices, and streaming services, it’s no longer enough to rely solely on traditional advertising channels like television and print. Instead, advertisers need to reach consumers across multiple platforms to ensure their message is heard. However, measuring the effectiveness of cross-platform campaigns can be challenging. With audiences spread across various devices and platforms, it can be difficult to get an accurate picture of how many people are actually seeing an ad. This is where methods to estimate total audience in cross-platform campaigns using deduplicated audiences come in. Deduplication is the process of identifying and removing duplicate entries from a dataset. In the context of cross-platform campaigns, it involves identifying individuals who have seen an ad on multiple platforms and removing those duplicates to get a more accurate count of unique viewers. There are several methods for deduplicating audiences in cross-platform campaigns. One approach is to use a probabilistic matching algorithm, which uses statistical models to identify individuals who are likely to be the same person across multiple devices. Another method is to use deterministic matching, which relies on data such as email addresses or phone numbers to identify individuals across platforms. Once the deduplication process is complete, advertisers can get a more accurate picture of their total audience across all platforms. This information can be used to optimize campaigns, adjust targeting strategies, and measure the overall effectiveness of a cross-platform advertising campaign. The market for methods to estimate total audience in cross-platform campaigns using deduplicated audiences is growing rapidly. As more advertisers shift their focus to cross-platform campaigns, the need for accurate audience measurement will only continue to increase. Companies that specialize in audience measurement and deduplication, such as Nielsen and comScore, are well-positioned to capitalize on this trend. In conclusion, the market for methods to estimate total audience in cross-platform campaigns using deduplicated audiences is an important and growing area of the advertising industry. By using advanced deduplication techniques, advertisers can get a more accurate picture of their total audience across all platforms, which can help them optimize their campaigns and measure their effectiveness. As the importance of cross-platform advertising continues to grow, so too will the demand for accurate audience measurement.

The Nielsen Co US LLC invention works as follows

The examples include determining a duplicated panel audience size that is representative of panelists who have been exposed to both television and digital media. They also determine the panel duplication reached based upon the duplicated panel audience size.

Background for Methods to estimate total audience in cross-platform campaigns using deduplicated audiences

Audience measurement is the process of measuring how many people are exposed to media content or advertisements, whether they be on television, radio, Internet etc. Typically, media exposure is monitored by panelists who are statistically selected as representing particular demographic groups. The Nielsen Company, LLC and other audience measurement companies enroll households and individuals to take part in measurement panels. Enrolling in these panels allows households and individuals to agree to let the audience measurement company monitor their exposure to media output, such as television, radio, computers, smart devices, etc. The collected data on media exposure is then processed using various statistical methods to determine the size of the audience and/or the demographic composition for the media of interest. Advertisers, broadcasters and content providers as well as manufacturers, retailers and product developers can all benefit from the demographic and/or audience information. The audience size and demographic data is used to place advertisements, value commercial time during a program, and/or generate ratings for a piece of media.

Example methods and apparatuses disclosed herein allow for determining audience duplication when cross-platform campaigns are used. The examples disclosed herein can analyze television-based campaigns delivered through televisions and Internet-based campaigns delivered via computers, mobile devices, tablets (e.g. an Apple iPad), and multi-media phones. The examples disclosed herein can be used to give media providers campaign exposure data to help them make better decisions, such as where to allocate advertising dollars or how to distribute ads. These examples can be beneficial to advertisers, marketers, service providers, product manufacturers and other entities that pay for advertising within the campaign.

Disclosed Examples then use the overlap multiplyers to determine a duplicate factor in a campaign media (e.g. a current campaign media). As an example, disclosed examples can obtain audience metrics for the TV platform and digital platform in a media campaign. Digital media and online mediums are interchangeable in the examples. The examples disclosed also map the campaign of a media to a specific genre (e.g. comedy, drama or news). Then, based on genre and media hierarchy levels, calculate an overlap multiplier for the media campaign. The examples disclosed determine the duplication multiplier based on audience metrics and the crossover multiplier. The examples disclosed herein use the duplication factor on the total audiences to determine a duplicated total audience. This is then subtracted from the total to get the deduplicated audience for the cross platform media campaign. In some examples the operations are repeated on different media hierarchy layers to obtain deduplicated audience levels at different levels of media hierarchy (e.g. at the episode, program, or originator levels .).

FIG. FIG. 1 illustrates an example environment 100 that can be implemented according to the teachings in this disclosure for estimating deduplicated audiences across platforms media campaigns. The example shown in FIG. The example cross-platform campaign comprises a television campaign delivered through television media access devices (104), and a digital campaign delivered by Internet-enabled device 106. In the example illustrated, both the television campaign as well as the digital campaign are the same campaign. However, they are delivered using digital and media. A user could, for example, watch a broadcast episode of?Comedy Show? The user can watch the episode during its regular broadcast time using a television media device 104. The user can then rewatch the same episode. The user may then rewatch the same episode via on-demand via a television media-access device 104 or an Internet-enabled 106 the next day, and subsequently rewatch the same?Comedy Show? Twenty days later, via an Internet-enabled 106.

The television media access devices (104 in the example) include different types of devices that allow television media to be accessed. The television platform (e.g. the television media device) can include televisions, smart TVs and/or other devices that are able to access television media, such as streaming and/or broadcast television media. Internet-enabled device 106 in the example illustrated includes multiple types of devices which can access digital media. For example, the Internet-enabled devices 106 (e.g., the digital platform) may include one or more of computers, tablet devices, smart phones, smart televisions and/or any other device that can access digital media (e.g., web pages, streaming radio and/or streaming video, pictures, downloadable video, streaming/downloadable music, etc.).

In the example shown, a TV measurement company 108 recruits viewers to join a panel of television (TV), audience member panels 110 a. They consent to their viewing habits being monitored. In some cases, the TV panel member 100 a uses Nielsen’s National People Meter panel. In the example shown, the TV measurement entity 108 maintains a database for television panels 112 that stores panel member data such as demographics and media preferences. Audience members exposed to television media. The TV measurement entity 108 records impressions on different television media that the television panel database 112 is exposed to. This includes advertisements, programming and/or television media.

In the example shown in FIG. The TV measurement entity includes a TV metrics calculation 109. The example TV metrics calculation 109 determines TV audience metrics, such as reach, audience size and so on. The TV metrics calculator 109, for example, may use Equation 1 to calculate the reach of the TV audience.

r\n?\ne\n?\na\n?\nc\n?\nh\nT\n?\nV\n=\nA\n?\nu\n?\nd\n?\ni\n?\ne\n?\nn\n?\nc\n?\ne\nT\n?\nV\nU\n?\nE\nEquation\n?\n?\n1

In Equation 1, the variable audienceTV represents the number audience members who watched the media program using a television platform 104. The population of the audience is represented by an universe estimate (UE). The universe estimate (UE), for example, may be an audience within a geographical area, such as a town, a county, a state or region.

In the example shown, the TV metrics calculater 109 calculates TV audience metrics for different media hierarchy levels. The TV metrics calculator can, for example, determine the audience reach of a show called “Comedy Hour” The TV metrics calculator 109 can calculate audience reach at three different levels: episode, program and/or originator. In some cases, the TV metrics calculator performs calculations separately for each group of demographics (e.g. each bucket). The TV metrics calculator may, for example, process TV impressions from the television panel database 112. This will determine the total TV audience reach of males aged 18-34 in an episode called?Comedy Hour?. To simplify the formula in some cases, the superscript “” is used. (d)? In all notations, (which represents a group of demographics (d)) will be ignored. “For example, (reachTV d) is replaced by (reachTV), which represents TV reach within the demographic group (d).

In the example illustrated, an audience measuring entity (AME), 102, operates the TV measurement unit 108. The AME 102 in the illustrated example works with a total measurement entity 116 that has registered users. In the example shown, the AME 102 is partnered with the total measurement entity 116. This could be a social networking site such as Facebook, Twitter, MySpace etc. ), a multi-service site (e.g., Yahoo!, Google, Experian, etc. Online retailer sites (e.g. Amazon.com or Buy.com) Any other website that keeps user registration records. When users register to use the online services of the total measurement entity 116, they may agree to the terms of service and/or privacy policies of the entity.

The total digital measuring entity 116 in the example illustrated maintains a database of total digital users 118 for user registration data such as demographics and media preferences. Registered users exposed to digital media. The total digital measurement entity (116) monitors the online activities of registered users to measure impressions of different digital media that the digital audience members (110 c) are exposed to. The total digital measurement entity in this example records impressions of digital media into the total digital user database.

In the example shown in FIG. The total digital measurement entity (116) includes a total metrics calculator (117). The total digital metrics example calculator 117 determines digital audience metrics, such as reach, audience size and so on. “For example, the digital metrics tool 109 can use Equation 2 to calculate the reach of the digital audience.

r\n?\ne\n?\na\n?\nc\n?\nh\ndigital\n=\nA\n?\nu\n?\nd\n?\ni\n?\ne\n?\nn\n?\nc\n?\ne\nd\n?\ni\n?\ng\n?\ni\n?\nt\n?\na\n?\nl\nU\n?\nE\nEquation\n?\n?\n2

In Equation 2, the audiencedigital variable represents the total number of viewers who watched the media program using an Internet-enabled platform 106. The audience population is represented by the universe estimate (UE). The universe estimate (UE), for example, may be a geographical area, such as a town, state, region, country, etc.

In the example shown, the total metrics calculator 117 calculates the digital audience totals at various media hierarchy levels. The total digital metrics calculator can, for example, determine the audience reach of a comedy program called “Comedy Hour” using its total digital metrics. The total digital metrics calculator 117 can calculate audience reach at different levels, such as the episode, program, and/or originator (e.g. in a media hierarchy). In some cases, the total digital metrics calculater 117 performs the calculations separately for each group of demographics (e.g. each bucket of demographics). The total digital metrics calculator may, for example, process digital impressions from the total database of digital users 118 in order to calculate total digital audience reach at the episode level for males aged 18-34. To simplify the formula in some cases, the superscript “” can be used. (d)? In all notations, (which represents a group of demographics (d)) will be ignored. “For example, (reachdigital D) is replaced by (reachdigital), which represents the total digital reach in the demographic group (d).

In the example shown in FIG. The total digital metrics calculator (117) calculates digital audience metrics on a platform-level. The total digital metrics calculator, for example, calculates one set of metrics, such as reach, audience size etc. For mobile devices, there is a separate set of metrics. The total digital metrics calculator example 117 can map the users on the different platforms because the users of digital media are registered with the entity for total digital measurement 116. The total digital metrics calculator can also separate audiences between digital platforms. If a user watches an episode of “Comedy Hour”, for example, the total digital metrics calculator 117 will count them in both the PC and mobile audience counts. The example total digital metric calculator 117 counts the user twice in the digital audience count.

In some examples, to measure impressions of digital media (e.g., web pages, streaming radio and/or streaming video, pictures downloadable video, streaming/downloadable music, etc. The total digital measurement entity (116) installs PC meters on Internet-enabled devices of digital audience members to monitor their viewing habits. Other impression collection techniques, such as those described in U.S. Patent Application Ser. No. 13/513,148 (now U.S. Pat. No. No. 8,370,489) filed on May 31st, 2012, entitled “Methods to Determine Impressions using Distributed Demographic Data”, Patent application No. No. 14/127,414 (now U.S. Pat. No. No. 8,930 701, filed on December 18, 2013 entitled “Methods to collect distributed user information for media impressions and search terms? U.S. patent application Ser. No. No. 13/514 148 and U.S. Patent application Ser. No. The entire text of 14/127.414 is hereby incorporated by reference. Total digital measurement entity 116 logs impressions on different digital media that the digital audience members (110 c) were exposed to using Internet usage data.

As shown in the example illustrated on FIG. Some of the TV audience members are also digital audiences 110 c. This results in a subset 120 of audience members who overlap. In some cases, the overlapped audience members 120 occur when people in the television audiences 110 a subscribe to services offered by the total measurement entity 116. In the illustrated example the television audience members (110 a) include a subset cross-platform home audience panel members (110 b) that are also members of the digital audiences 110 c, and access digital media through the Internet-enabled device 106. In the illustrated example, the television panel database 112 stores panel member data about those CPH audiences panel members 110b in a CPH database 114 to be used in tracking their digital viewing habits.

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