WO2017218712A1 - Calcul d'un score relatif à des opportunités dans un système d'insertion - Google Patents

Calcul d'un score relatif à des opportunités dans un système d'insertion Download PDF

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Publication number
WO2017218712A1
WO2017218712A1 PCT/US2017/037564 US2017037564W WO2017218712A1 WO 2017218712 A1 WO2017218712 A1 WO 2017218712A1 US 2017037564 W US2017037564 W US 2017037564W WO 2017218712 A1 WO2017218712 A1 WO 2017218712A1
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WIPO (PCT)
Prior art keywords
audience
score
persona
placement
opportunities
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PCT/US2017/037564
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English (en)
Inventor
Gary Shenk
Greg Isaacs
Barrett MORSE
Alexander MCFADYEN
Zachary BAKER
Nick Johnson
Matt MCELROY
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Branded Entertainment Network, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Application filed by Branded Entertainment Network, Inc. filed Critical Branded Entertainment Network, Inc.
Publication of WO2017218712A1 publication Critical patent/WO2017218712A1/fr

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

Definitions

  • Various embodiments generally relate to a system for placing product advertising within media and computing a score that assesses the fit or match between a target audience and a plurality of content opportunities based on aggregated audience data.
  • Product placement refers to the placement of product and brand advertising integrated within media such as movies, television programs, social media, songs, Web photos and videos and the like such that the advertising is integrated within the media.
  • media such as movies, television programs, social media, songs, Web photos and videos and the like
  • product placements do not disrupt the continuity of the media. Examples include an actor holding a specific beverage product in a movie where the beverage product's label is prominently featured, an actor driving a specific type of car within a television program, a song that mentions a specific product, or a photo of a celebrity published on a Web page in which the celebrity is wearing a specific brand of clothing.
  • Product placement is a form of advertising but is different from conventional advertising and is not addressed by existing computer-based advertising systems, tools and platforms.
  • an advertiser or as referred to herein a "brand” creates a brand brief that defines the market for a product or service to be advertised as part of an advertising campaign.
  • the brand brief defines the
  • a brand brief typically includes "personas", i.e. hypothetical individuals that represent target audiences, or segments of the potential audience. Multiple personas may be used to define the target audience.
  • Prior art advertising systems do not typically provide tools or facilities to ingest and use persona information as provided in brand briefs. Therefore, it would be advantageous to provide a system that enables a user or buyer that defines a media plan for an advertising campaign to work directly with personas supplied by a brand.
  • Various embodiments are directed towards a product placement system that enable a media buyer to interactively specify a placement campaign for the integration or placement of branded products within media such as movies, videos, songs, and celebrity photos and videos based on estimated prices for placements.
  • the placement system ingests information about productions that represent potential opportunities for placements and stores the data in a data warehouse.
  • a buyer specifies a target audience using a visual persona that represents a variety of attributes, such as demographic details and psychographic details. Persona may be combined and weighted to represent a target audience or multiple target audiences. Further, the component attributes of a persona may be weighted.
  • a Fit metric is computed for opportunities.
  • the "fit" metric may be used to order search results, rank selections of opportunities for a media buyer, determine prices, and provide an easy to understand metric for review by the buyer, and the like.
  • two scores are computed for each opportunity: an audience score that measures the overlap between the audience for an opportunity and the desired, or target, audience as defined by a brand using a brand persona; and an engagement score that measures the level of social engagement by an audience with the vehicle in which the opportunity is placed.
  • FIG. 1 is a generalized block diagram of a preferred embodiment of an online product placement system in which a product placement service enables a media buyer, or user to specify a media plan, and then searches for product placement opportunities that conform to the media plan.
  • FIG. 2A illustrates one embodiment of a user interface that enables a buyer to specify requirements for a product placement media plan.
  • FIG. 2B illustrates one embodiment of a user interface that enables a buyer to specify a channel mix for a product placement media plan and to interactively select and reject product placement opportunities provided by a product placement system.
  • FIG. 2C illustrates one embodiment of a user interface, referred to as a buyer interface, which summarizes the results of a single placement campaign based on a media plan.
  • FIG. 3A illustrates how personas are used in a media planning interface to define a target audience.
  • FIG. 3B illustrates an embodiment of a search results buyer interface.
  • FIG. 3C provides an embodiment of a buyer interface that enables the buyer to select personas, view characteristics of personas, create new personas and edit personas.
  • FIG. 3D is an embodiment of a buyer interface that enables a user to view and edit persona details.
  • FIG 3E illustrates an additional example of a buyer interface that may be used to edit detailed characteristics for a persona.
  • FIG. 4A is a simplified block diagram of a content data system (CDS) that collects and ingest data from external data sources and
  • CDS content data system
  • FIG. 4B illustrates an embodiment of processes performed by a brand placement system.
  • FIGS. 5A-C provide an example visual depiction of the data included in an opportunity data object
  • FIG. 6A illustrates the relationship between a target audience defined for a brand and a content audience for an opportunity.
  • FIG. 6B presents a simplified example of scoring a target audience, as represented by a brand persona, relative to an audience for a vehicle or opportunity.
  • FIG. 7 is a flow diagram that illustrates a method that creates personas for use in persona based matching (PBM).
  • FIGS. 8A-C is overall method for discovering an opportunity and then calculating an audience sore, an engagement score, and a Fit metric between the opportunity and a target audience.
  • FIG. 9 is a system diagram that shows components of one exemplary environment in which the invention may be practiced.
  • FIG. 10 is block diagram of exemplary software modules of a product placement server.
  • Impression - refers to a viewing or listening of a piece of media such as a movie, television program, social media, Web video, song, or photo by one person.
  • CPM - refers to a standard cost metric that means the price charged by a publisher for a conventional advertisement or placement in a piece of media for one thousand impressions or views.
  • Channel - refers to a category of media in which a product placement can be made. Channels include television, movies, music, social media, printed advertisements, Web video advertisement, Web image advertisements, and the like.
  • Media Vehicle or vehicle - refers to a specific piece of media such as a specific television program, film or movie, social media network such as FACEBOOK or INSTAGRAM, web advertisement, video, song or other piece of media in which a product placement may be made.
  • Vehicle power - refers to a rating of the intrinsic value of a
  • vehicle power is stated as a letter value, e.g. A, B, or C where A refers to vehicles that have more value, and are thus more costly to advertise in and C refers to vehicles that have less value and thus are less expensive to advertise in.
  • Branded product placement, product placement or placement - means the integration of a display, appearance, or mention of a product or brand within a vehicle.
  • the media may be audio or visual, or both, such as within a music video.
  • a placement is different than a conventional
  • advertisement in that it is integrated with the media content, i.e. there is continuity between the media content of the vehicle and the placement.
  • the storyline of the vehicle is not disrupted and the viewer does not perceive a placement as a separate advertisement.
  • a viewer can choose not to watch a commercial inserted into a television program and not miss the program content itself.
  • Integration of a product placement into a vehicle means that if the viewer doesn't see the placement they miss viewing or listening to at least a portion of the vehicle content.
  • product placement refers to advertisements for specific products as well as to more general advertisements for brands, e.g. when a company logo might appear rather than a specific product.
  • placements include an actor in a movie driving a specific model of car during a chase scene, an actor holding a specific, easily recognizable beverage, in a movie, film, or photo, or a mention of a specific product in a song. Pricing of placements has not previously been standardized in the way that pricing for conventional advertisements have. Thus, creating a model and an automated method for estimating the value and hence price of a placement is itself novel and unique.
  • conventional advertisement is that the advertiser creates an advertisement and control over every aspect, for example the content, and duration.
  • a placement is purchased by a media buyer prior to its being created; and it is created as part of the creation or production of the vehicle itself.
  • Product placement opportunity, or opportunity - means a potential placement in a vehicle that may be purchased by a media buyer.
  • Placement quality - refers to a rating of the relative importance or prominence of a brand or product placed within a vehicle. Factors used to assess placement quality include prominence of the item. For example, if the placement is for a soft drink in a TV show, if the soft drink is prominently displayed in the hands of a major star then the placement quality would be very high; on the other hand, if the soft drink is on a table in the corner then the placement quality would be low. Another factor that may be used to assess placement quality is the treatment of the item. For example, if the placement is for a particular brand of coffee, do the actors in the scene appear to be enjoying the coffee? Another factor is whether the placement is integrated into the storyline of the vehicle. Yet another factor is whether there is a verbal or nonverbal mention of the product in the vehicle. In one embodiment placement quality is specified using a scale of Premium,
  • the placement quality can only be evaluated after a placement has been produced, or created, and is integrated into a vehicle since many of the criteria used to evaluate placement quality, e.g . visibility of product, are under the control of the producer or director of the vehicle and cannot be known in advance of production. Note that as used herein the terms
  • Placement duration or simply duration - refers to the amount of time during a media segment, e.g. during a film or TV show or song, that a placement occupies. For example, if a placement consists of an actor holding a can of soda in a film the duration would be the length of time in which the actor appears holding the can of soda. Similar to placement quality, the duration of a placement can typically only be evaluated after a vehicle in which a placement appears has been produced since decisions affecting the duration of a placement are made during production.
  • Media buyer or buyer or user - means an individual that uses a mobile device, PC or other electronic device to access and use a product placement service available across a network, typically with the objective of specifying a media plan, purchasing placements, or evaluating results from implementation of a media plan by the placement service.
  • FIG. 1 is a generalized block diagram of a preferred embodiment of an online product placement system in which a product placement service enables a media buyer to specify a media plan, and then searches for product placement opportunities that conform to the media plan.
  • a media buyer hereinafter referred to simply as a buyer or user, uses a buyer application 115 that runs in a buyer computer 110 to perform some or all of the following functions: specify, define, edit or modify a media plan, specify filters, and view summary and detailed results from execution of a media plan.
  • Buyer application 110 is described in further detail hereinbelow with reference to FIGS. 2A-C.
  • Buyer application 115 may include one or more Web browser-based applications and/or mobile apps delivered across a network from a product placement service 130 and executed by buyer computer 110, one or more mobile applications, or it may be one more applications that are separately downloaded or installed from other media such as a USB drive or other external storage medium, into buyer computer 110 for execution by a buyer.
  • Product placement service 130 refers to a service that is available across a network 150 that enables a buyer to specify and implement a media plan across multiple types of media.
  • Product placement service 130 may be implemented by one or more server computers acting cooperatively or by a network service, or "cloud" service provided by a third party.
  • server computers acting cooperatively or by a network service, or "cloud" service provided by a third party.
  • FIGS. 7 and 8 One embodiment of a server-based approach to implementing product placement service 130 is described hereinbelow with reference to FIGS. 7 and 8.
  • Placement service 130 provides services across network 150 to a buyer computer 110 and to a management computer 120.
  • a manager of placement service 130 ensures that placement opportunities are available to a buyer using buyer application 115 running on buyer computer 110.
  • a manager uses a management application 125 that runs in management computer 120 to interact with management functions provided by product placement service 130.
  • Management functions may include defining or providing data for vehicles, opportunities and placements, determining and entering vehicle power values for opportunities, determining and entering placement quality values for placements after they have aired and maintaining a database of buyers with up-to-date buyer information.
  • Product placement service 130 maintains a database of product placement opportunities, also referred to herein simply as opportunities. Each opportunity refers to a potential product placement within a vehicle such as a television program, social media network, song or movie. Once an opportunity is included in a media plan and executed as part of a placement campaign it is referred to as a product placement or simply as a placement.
  • Product placement service 130 includes a content data system (CDS) 132, which is a data system that includes a data warehouse that receives and stores information about vehicles, opportunities, audience data, and social media engagementfrom various external data sources 140.
  • CDS 132 receives and stores external data from data sources 140 and processes the data to generate opportunity objects, or opportunities.
  • opportunities are then compared to target audiences defined by a buyer in order to determine audience scores, and to social engagement data to determine engagement scores for each opportunity.
  • Product placement service 130 also includes a brand placement system 132 that performs a variety of user requested processes such as creating a media plan, selecting opportunities for inclusion in a media plan, searching for and reviewing vehicles and opportunities, and defining target audiences.
  • Data sources 140 may be publicly available databases or services or private information services. Table 1 below, gives an example of data that may be obtained from data sources 140 for different channels. This information is available from a variety of companies and organizations including, for example, THE NIELSEN COMPANY, COMSCORE, and GOOGLE.
  • FIGS. 2A-C are embodiments of a user interface implemented by buyer application 115.
  • each of FIGS. 2A-2C correspond to an interactive Web page that is provided by placement service 130 to buyer computer 110 to be displayed by buyer application 115.
  • FIG.2A illustrates one embodiment of a user interface that enables a buyer to specify requirements for a product placement media plan.
  • Buyer interface 200 includes entry box 202 that enables the buyer to specify a project name, pull down menu 204 that enables the buyer to specify a brand or product line or company, entry box 210 that enables the buyer to enter a project goal, and date boxes 208 that enable the buyer to specify a date range, depicted as a starting date and ending date, for the campaign that executes the media plan.
  • buyer interface enables the buyer to specify product categories 206, and a campaign budget 212.
  • a set of segment controls 214 enable a buyer to specify one or more market segments, or target audiences to be addressed in the media plan.
  • Segment information that may be specified include gender, age, geography, income, occupation, buying preferences, race, nationality and the like. Multiple market segments may be defined as target segments using segment controls 214. The union of the various segments or audiences specified by a buyer is referred to as a "target audience.”
  • target audience One embodiment, that uses a visual representation of target segments or audiences, referred to as a persona is described with reference to FIGS.3A-D.
  • FIG. 2B illustrates one embodiment of a user interface that enables a buyer to specify a channel mix for a product placement media plan and to interactively select and reject product placement opportunities provided by a product placement system.
  • placement service 130 identifies and provides a list of available opportunities to buyer computer 110 for display to the buyer.
  • Buyer application 115 provides buyer interface 220 to the buyer, which enables him/her to view and further refine opportunities selected for inclusion in the media plan.
  • the buyer may indicate preferences as well as make comments and otherwise interact with opportunities.
  • a channel mix control 222 enables the buyer to specify the allocation of the budget among each media channel. While the channels illustrated in this example embodiment include film, TV, music, celebrity and digital (i.e. Web media), other channels, such as social media, may be included or channels illustrated may be omitted without departing from the scope and spirit of the subject invention. Further, in some embodiments channel mix control 222 specifies a target allocation of impressions, budget or CPMs. Using controls 224 the buyer can view opportunities, wishlist items and excluded opportunities.
  • an opportunity list 226 displays a list of opportunities identified by placement service 130 as being consistent with the media plan specified by the user and available for placements. Additionally, the buyer can perform keyword searches to select individual opportunities or groups of opportunities for inclusion or exclusion in the media plan. In this embodiment, two controls are available for each opportunity.
  • An include control 228 enables the buyer to indicate that he/she wants to include the opportunity and similar opportunities in the media plan. Included opportunities are added to the wishlist.
  • An omit control 230 enables the buyer to indicate that he/she wants to omit the opportunity and similar opportunities from the media plan. Omitted opportunities are added to the excluded list.
  • include control 228 is used to indicate that a specific opportunity should be included and omit control 230 is used to indicate that a specific opportunity should be excluded.
  • FIG. 2C illustrates one embodiment of a user interface, referred to as buyer interface 240, which summarizes the results of a single placement campaign based on a media plan.
  • Buyer interface 240 includes a delivery and impact panel 242 that displays campaign results for each channel included in the media plan.
  • Buyer interface 240 displays results information including the number of projected and actual impressions achieved for each channel, the projected CPM, and the projected and actual media value.
  • PBM persona based matching
  • a brand specifies a target audience as a series of personas, which are named, fictitious, individuals each of which represents a specific audience.
  • the union of the specific audiences is referred to as the brand audience or target audience.
  • the target audience is defined by a set of characteristics, which may typically include demographic details such as age, gender, ethnicity, and psychographic details such as personality traits, values, attitudes, interests, and lifestyles or behaviors that typify the desired audience for the brand.
  • the term persona as used herein refers to a visual representation of a fictitious individual that represents a specific, target, audience. As such, a persona represents or specifies the
  • characteristics of a desired audience which may include demographic, psychographic and behavioral characteristics.
  • the ability to refer to, select and manipulate audience characteristics using visual personas is a novel and unique characteristic of certain embodiments of system 100.
  • FIGS.3A-D present an embodiment of buyer application 115 that enables a buyer to specify a target audience using a visual, persona-based approach.
  • FIG.3A illustrates how personas are used in a media planning interface 300 to define a target audience.
  • the term target audience is used because the personas represent the audience that a brand, or buyer representing a brand, wants to reach through a product placement
  • brand persona may also be used to reflect the combination of one or more personas to represent the target audience.
  • Buyer interface 300 enables the buyer specifies a target audience for a campaign using personas.
  • the buyer uses a target audience control 302 to select personas for inclusion in the target audience.
  • the buyer has selected two personas, named Alyssa and Dylan, which in combination specify a brand persona, or target audience, for the campaign.
  • a buyer can adjust the percentage contribution, or relative weight, of each persona.
  • a slider, or other control may be available that lets the buyer adjust the contribution of a persona upward or downward.
  • FIG.3B illustrates an embodiment of a search results buyer interface 310.
  • brand placement system 132 initiates an opportunity search after a buyer creates a media plan using buyer interface 300.
  • An opportunity search searches for available opportunities that match the brand persona created using buyer interface 300.
  • a summary panel 312 summarizes data from the media plan, including personas, categories, flight date and name.
  • An opportunity summary panel 314 provides data that summarizes the opportunities determined by the opportunity search. In the example, 143 films, 398 TV shows, 21 Web ads, 232 celebrity endorsers and 1033 social media
  • a search box 316 enables a buyer to enter search criteria including opportunity name, cast member, network or keywords. Additionally, the search can be sorted according to various criteria, including a Fit score, an audience score, an engagement score, and media type.
  • results are displayed as rectangular boxes with a thumbs up icon, a name, and an indicator of the type of media. Clicking on the thumbs up icon indicates that the buyer wants to consider the opportunity for inclusion in the media plan.
  • results are returned along with one or more scores. Scores may include an engagement score, an audience score and a Fit score, which are discussed hereinbelow.
  • one or more of the scores is used to order the search results. Further, in certain embodiments one or more of the scores may be displayed to the buyer.
  • FIG. 3C provides an embodiment of a buyer interface 320 that enables a buyer to select personas, view characteristics of personas, create new personas and edit personas.
  • a persona filter panel 324 lets the buyer specify filters to apply when presenting or searching for available personas. Photos that represent personas that meet the characteristics defined in the persona filter panel 324 appear in a persona carousel 324.
  • a create custom control 326 allows a buyer to indicate that he/she wants to define a new or custom persona.
  • a clone persona is used as the basis for creating a new persona and a clone persona inherits the characteristics of the currently selected persona.
  • the buyer uses a persona detail interface 340 to edit the characteristics of the clone persona.
  • a characteristics panel 328 shows a representative image 330 and enables a buyer to specify the characteristics of a persona, such as a name, gender, age range, ethnicity, income range and whether there are children in the household.
  • characteristics for persona referred to as Alyssa
  • a textual description 332 provides a summary of the persona.
  • selecting image 330 opens a buyer interface 340 that shows and enables the buyer to edit additional characteristics of the selected persona.
  • characteristics panel 328 provides demographic details; however, generally a persona may include a wide variety of characteristics including demographic, psychographic, behavioral and social.
  • An example buyer interface 340 illustrated in FIG. 3D, enables a user to view and edit persona details.
  • Buyer interface 340 includes a sample of the full set of characteristics that characterize the selected persona. The example characteristics depicted in buyer interface 340
  • media Brittany prefers 344 such as television (TV) and Over the Top (OTT) programming (an industry term to denote nontraditional video programming such as that from NETFLIX and other streaming media providers, and certain cable TV providers), music, social media influencers, live streaming and digital/Web interests, and celebrities, other interests 346 and dislikes 348.
  • Other characteristics that may be available from buyer interface 340 but which are not depicted include social networks he/she uses, preferred brands, conversation topics, e.g . hashtags used in online comments, other media that they watch or engage with, related or similar personas.
  • FIG. 3E illustrates an additional example of a buyer interface 360 that may be used to edit detailed characteristics for a persona.
  • Buyer interface 360 enables a buyer to select one or more interests listed in a panel 362.
  • Panel 364 enables a user to select a category of interests, e.g. banking, and a detailed interest within the category using a panel 366, which shows three banking areas of detailed interest.
  • a hashtags panel 368 enables the buyer to enter hashtags that characterize areas of interest for the persona.
  • FIGS. 3A-D provide a visual means to specify a target audience which itself is composed of distinct populations or audiences, each of which is
  • FIGS. 4, and 6-10 are flow and component diagrams in which each graphical element, including rectangles, cylinders, and triangles, can be implemented by computer program instructions. These program instructions may be provided to a processor and then executed by the processor, thus creating means for implementing the actions represented by the graphical element.
  • the computer program instructions may be executed by a processor to cause a series of operational steps to be performed by the processor to produce a computer-implemented process such that the instructions, which execute on the processor to provide steps for
  • FIG. 4A is a simplified block diagram of a content data system (CDS) that collects and ingest data from external data sources 140 and incorporates internally generated data to create opportunity data objects that can be evaluated against target audiences.
  • Data sources 140 provide data required to : identify vehicles for placements, i.e. opportunities, and to provide data for viewing by a buyer, reporting, and analysis by placement service 130.
  • Data sources 140 includes (1) content and programming data such as electronic program guides (EPG) such as that provided by GRACENOTE and information pertaining to television and film vehicles in production and pre-production such as that provided by VARIETY, (2) viewership data, including audience demographics and impressions, for specific media such as film and television such as that provided by NIELSEN, RENTRAK and
  • COMSCORE consumption and behavior data
  • social activity and interests such as that provided by MRI and NIELSEN/SCARBOROUGH.
  • Other sources may be used for specific media channels such as social networks including SHAREABLEE and CRIMSON HEXAGON .
  • data from data sources 140 is ingested and stored using a cloud storage facility.
  • a data ingestion 410 component provides several methods for ingesting such external data, including (1) use of APIs supported by the provider of the data source, (2) use of a dashboard provided by the data source which enables a user to obtain data, (3) custom ingestion methods developed for data sources that have nonstandard formats, such as a cross-tabbed relational database, and (4) manual input, for example, extracting data from printed or electronic reports supplied by the data source by a staff person and entering the data into forms, database fields, or other files.
  • the term dashboard as a process within data ingestion 410 refers to steps typically performed by a staff person using an interface provided by the data source to obtain and ingest data.
  • data from data sources 140 is matched and processed to create intermediate results that are more convenient for subsequent processing steps.
  • EPG electronic program guide
  • Data retrieved and processed by data ingestion 410 is stored in a storage facility, referred to as pristine storage 415.
  • pristine storage 415 In certain
  • pristine storage 415 stores data in its original or source format, i.e. all subsequent transformations and processing such as
  • Pristine storage 415 is a data warehouse that stores historical data sets from a plurality of data sources 140 as well as internally generated data such as media plans.
  • a schema layer 420 performs data normalization
  • Standardization ensures that data in pristine storage 415 is transformed to use naming and formatting conventions used by brand placement system 134. For example, TV and film data may include viewership demographics but the age and income brackets may be quite different as the data comes from different vendors. Standardization is performed as part of schema processing and includes processes such as creating specific views of the data and generating opportunity data objects that describe opportunities.
  • Other types of normalization include: viewership numbers, sales metrics, viewership metrics, social media metrics (e.g. clicks vs. likes).
  • Schema layer 420 may be used to analyze viewers of a specific program, e.g. the TV program WALKING DEAD.
  • product data can be cross tabulated with TV program data to identify the percentage of viewers of WALKING DEAD who drink COCA COLA
  • Schema layer 420 may further be used to define a variety of reports, to be used by a scheduled reporting 435 process.
  • a UCS layer 425 acts as a secondary schema layer.
  • UCS layer 425 processes requests made by buyers using brand placement system 134 and generates appropriate schemas and queries that are processed by CDS 132.
  • UCS layer 425 also integrates internally generated data such as media values and audience and engagement metrics into results that it returns to brand placement system for display to a buyer.
  • FIG. 4B illustrates an embodiment of processes performed by brand placement system 134.
  • the brand supplies information from its brand brief to brand placement system 134. Typically, this is accomplished when a buyer, representing the brand, selects, edits or creates one or more personas that correspond to the brand brief, using buyer application 115 running in buyer computer 110.
  • Brand placement system 134 receives personas from a buyer and content information from data sources 140 and provides user interaction, planning, campaign management and execution, and reporting. In addition, brand placement system 134 runs a number of asynchronous processes.
  • brand placement system 134 relies on internal staff or contractors to analyze information about vehicles such as TV shows, films, and influencers to identify placement opportunities.
  • the staff then input a variety of information about the opportunities, which is stored in an opportunity database as opportunity objects.
  • staff may review the script for a movie and identify certain categories of products, e.g. jewelry or automobiles, that are referenced in the script.
  • computer intelligence techniques such as keyword search, natural language processing (NLP), machine learning, and artificial intelligence (AI) may be used to analyze vehicle data such as scripts, closed captions, and social media to automatically generate keywords, keywords, closed captions, and social media to automatically generate keywords, and phrases, etc.
  • NLP natural language processing
  • AI artificial intelligence
  • brand placement system 134 discovers opportunities and generates and stores corresponding data objects.
  • An opportunity data object typically includes program information, schedule information, viewership information, behavior information, and consumer purchase information; each of these types of information typically comes from a different one of data sources 140. Some of the component data included in an opportunity object may be stored at the time the opportunity is discovered; other elements of the opportunity object may be obtained or calculated on-the-fly, i.e. as needed for viewing, reporting, etc. Information from opportunity data objects is subsequently displayed to the buyer as opportunities that can be reviewed, selected and incorporated into a media plan.
  • Table 2 lists the types of information that are included in an opportunity object.
  • FIGS 5A-C provide an example visual depiction of the data included in an opportunity data object.
  • the illustrated opportunity includes
  • an opportunity data object such as that depicted, includes data collected from data sources 140, data that is collected and then processed to achieve a desired format, and new types of data such as vehicle power and media value that is generated by brand placement system 134.
  • An example of data generated by brand placement system 134 and incorporated into a data object is brand
  • categories 510 illustrated in FIG. 5B correspond to desirable placement categories that are available in episodes of the
  • FIGS. 6A-B illustrate a general framework for determining a measure of matching, referred to as an audience score, between a target audience defined for a brand campaign and the measured audience for an opportunity.
  • An audience score is a quantitative measure that defines the extent to which an opportunity matches or fits with a target audience for a brand as specified in a media plan.
  • audience score may be a relative measure, such as a ranking, of an opportunity in relation to other opportunities or the ranking of a target audience relative to other target audiences. For example, if 100 audiences have been defined, each corresponding to a different persona, then 100 different audience scores can be calculated and then ranked from 1 to 100. Alternatively, the scores can be further processed to obtain statistical measures such a mean and standard deviation.
  • FIG. 6A illustrates the relationship between a target audience defined for a brand and a content audience for an opportunity.
  • two audiences 602-604 each defined by a different persona, e.g. Alyssa and Dylan from FIG. 3A, and each represented in the figure by circles, constitute the target audience for a brand campaign.
  • the combination, or union, of the two personas, represented by the large circle 606, form a brand persona that also defines the target audience.
  • the target audience is the desired audience that a brand wants to reach with a placement campaign.
  • measurements of the audience for specific opportunity referred to as a content audience 608, are obtained by CDS 132.
  • the audience score is a measure of the overlap 610 between the target audience and the content audience. While the target audience and content target audience are illustrated as circles, in fact they are multidimensional in that each is characterized by a wide variety of characteristics including demographics, psychographics and behaviors.
  • FIG. 6B presents a simplified example of scoring a target audience, as represented by a brand persona, relative to an audience for a vehicle or opportunity. In this example, five different audiences are scored, each corresponding to a different brand persona. Each brand persona is
  • the actual audience for HOMELAND is obtained from data sources 140 and is processed and stored by CDS 132.
  • the unit of measurement on the horizontal (X) axis is number of standard deviations ( ⁇ ) from the mean ( ⁇ ), where the mean is the statistical mean amount that a defined population overlaps with the measured audience for a program or opportunity.
  • audience A3 receives the highest score at just under 3 standard deviations above the mean. A3, overlaps to a high degree with the actual HOMELAND audience.
  • the audience score for an opportunity may be a value from 1 to 100 or a percentage that reflects how close the opportunity is to a perfect match with the defined target audience.
  • the audience score in this case is the percentage overlap between an item of content, named "Great Show” and a single persona (Alyssa, from FIG. 3B).
  • the rule used for this simplified example is, for each characteristic, to calculate the fraction of the content audience that overlaps with the desired target audience.
  • the column labeled overlap identifies the items or range that are common to both the target audience and the content audience.
  • more granular analysis may be used. For example, different ethnic groups may be weighted based on their percentage of a population, certain interests may be weighted more highly than others, and the like. Further, audience fit may be computed in other ways. Yet further, this method applies to computing an audience fit when the brand target audience is composed of more than one persona since a brand persona is generated by taking the union of the characteristics for each individual persona specified for the brand.
  • Audience score is a novel measure that can be used, for example, to order the list of opportunities returned from a search by a buyer. Further, the audience fit may be displayed for each opportunity in a list, providing the buyer with a critical measure with which to compare placements.
  • audience fit is a measure that provides unique guidance to a media planner or buyer when reviewing and selecting placement
  • an engagement score measures the social media engagement of an audience with a particular vehicle. For example, the engagement score might indicate that viewers with a
  • an engagement score may be computed that measures the extent of the social activity or engagement by its audience. This score may be used to recommend opportunities to brands based on the social engagement of the brand's target audience with the opportunities.
  • An engagement score may be computed for the entire content audience for an opportunity, i.e. a measurement for the entire audience that viewed an opportunity or that regularly views the vehicle in which an opportunity is placed.
  • an engagement score may be computed only for the overlap between the content audience for an opportunity and a target audience desired by a brand.
  • Data sources 140 includes social data which is ingested and stored in pristine storage 415.
  • Social data may include data types such as those listed below in Table 4.
  • Fit (t, o) f(AS(t, o), ES(t, o)) Equation 1 where t is the target audience for a brand campaign, o in an opportunity, AS(t, o) is the audience score for the opportunity relative to the defined target opportunity, and ES(t,o) is the engagement score for the opportunity relative to the defined target opportunity.
  • Equation 2 Equation 2
  • Fit (t, o) AS(t, o) * g(ES(t, o)) Equation 2 where g(ES(t,o)) is a function of the engagement score ES(t,o).
  • ES(t,o) acts as an exponential on the audience score, AS(t,o), as shown in Equation 3 below:
  • Equations 2-3 the engagement score serves to modify the value of the audience score.
  • the underlying logic is that if a share of the target audience views a program or vehicle in which a placement is made, as represented by the audience score, there is potentially a material impact based on the portion of the viewers that then go out and communicate beneficially about the program.
  • Equations 2 and 3 capture the "network effect" of social media.
  • FIG. 7 is a flow diagram that illustrates a method for creating personas for use in persona based matching (PBM).
  • a buyer uses a user interface, such as that described with reference to FIGS. 3A-D, which enables him/her to define a target audience, or brand persona, that corresponds to a target audience for a media plan or campaign. This typically occurs as part of the process of defining or editing a media plan.
  • brand placement system 134 concurrently with defining the target audience, concurrently with defining the target audience, brand placement system 134 returns a list of existing personas, referred to herein as default personas, that correspond, at least partially, to the target audience.
  • this step is performed in real-time, i.e. personas are displayed to the buyer as they successively provide additional detail about the target audience.
  • the buyer associates a persona with the target audience.
  • a buyer can review and search for default, i.e. predefine personas
  • the buyer can select a default persona, clone it, and then define or modify the attributes of the default persona to create a new persona
  • the buyer can start from scratch and using the buyer interface can create a new persona.
  • default personas are presented to the buyer. These are provided from a database of personas 714 that enables the user to view and access data from pristine storage 415, which is provided via a schema layer 420 and a UCS layer 425.
  • the buyer decides whether to select one of the available default personas or to select a default persona and clone it, i.e. create a new copy that can be used as the basis for a new persona. If the buyer selects a default persona to represent the target audience then the method ends. If the buyer selects to create a clone persona, then at step 722 the selected default persona is cloned.
  • control can select a control to create a new persona and control flows to step 720 where a new persona is created.
  • the buyer can define or modify persona attributes using a user interface such as that described with reference to FIGS.3A-D.
  • the buyer saves the custom-created persona in persona database 714 and the method ends.
  • a persona has been associated with the target audience.
  • the buyer may repeat the method and associate additional personas with the target audience.
  • the audience scoring, engagement scoring and Fit analysis can then be performed to identify available opportunities that match the target audience defined by the buyer.
  • Method 800 for ingesting opportunity data, defining a target audience using personas and then calculating a fit metric between opportunities and the target audience is illustrated in FIG.8.
  • Method 800 includes 3 asynchronous sub-methods that are typically implemented as independent processes performed by placement service 130. The three sub-methods are illustrated in FIGS.8A-C.
  • FIG.8A illustrates a simplified embodiment of the steps performed to ingest data from data sources 140 and store normalized data in pristine storage 415. This method is described in addition detail in FIG.4A.
  • step 810 data from data sources 140 is ingested at step 810. Ingested data is stored in pristine storage 415. This data is then available to brand placement system 134, which performs the processing steps of FIGS.8A-B. [00112] At step 815 a buyer creates a brand persona, which specifies a target audience for their media plan.
  • FIG.8B illustrates a simplified embodiment of the steps performed by a buyer to create a brand persona that specifies a target audience for a placement campaign.
  • a buyer uses buyer application 115 to creates a brand persona that defines a target audience for a media plan.
  • a brand persona is a union of the characteristics specified in one or more personas.
  • a buyer may select one or more existing personas 820 for inclusion or may create one or more new personas, which are in turn stored as a new persona 820.
  • Persona 820 refers to a library or database of personas stored by content CDS 132. If more than one persona is selected then, in certain
  • the buyer can apply a weight to each persona.
  • the buyer can apply a weight to individual attributes of a person.
  • the selection of personas and weights are together referred to as a brand persona.
  • a brand persona defines the brand target audience for a media plan or campaign. This step is part of the overall step of defining a brand or product campaign, which may involve other steps such as
  • the brand persona together with any additional media plan information is stored in database 825 by CDS 132.
  • FIG.8C is a flow diagram of a simplified embodiment of a method for generating scores for a brand campaign that measure the fit between a target audience and a set of available placement opportunities.
  • an opportunity search is initiated.
  • brand placement system 134 may initiate an opportunity search automatically by as part of the process for specifying a media plan, as described in FIG. 3B.
  • a search may be initiated explicitly by a buyer using buyer application 115. The goal of the search is to obtain the "universe" of all available
  • the current method is not so limited and can be used for other types of brand campaigns, such as raising awareness, or improving retention. Further, the approach described by method 800 can be extended to cover campaigns that address multiple products and multiple brands.
  • step 835 opportunities that overlap, to some extent, the target audience are identified.
  • the demographic, psychographic and behavioral characteristics of a target audience are evaluated relative to each
  • an audience score is calculated for each of the opportunities identified in the preceding step.
  • the audience score is a measure of the degree of overlap between each opportunity and the target audience for a placement campaign.
  • data concerning social media engagement is used to expand the universe of opportunities by identifying other opportunities with which the target audience engages. For example, if persons in the target audience who express sentiment or reaction such as like, love, or interest dislike or anger for a TV show such as RAY DONOVAN also indicate a similar sentiment or reaction to another show, such as TROLL HUNTERS, then TROLL HUNTERS may be added to the list of opportunities. Data such as social media discussion, indications of sentiment such as LIKES, are analyzed to obtain this information.
  • an engagement score is calculated for each of the opportunities identified in the preceding step.
  • the engagement score measures the relative level of engagement with an opportunity by the target audience based on social media data.
  • a Fit score is calculated for each opportunity.
  • the Fit score is a function of both the audience score and the engagement score for the opportunity. In other embodiments, only an audience score or an engagement score may be calculated in which case the since score becomes the Fit score.
  • step 860 the search results, which include information about the opportunities identified, and at least a Fit score for each
  • the opportunity information returned by the search typically includes a selection of the data illustrated in FIG. 3B, such as a thumbnail, a name for the opportunity, an indication of the type of media, and other relevant data.
  • the Fit score, audience score and engagement score may also be used to (1) display for the buyer, (2) to order search results, (3) for purposes of reporting, and (4) provide proactive electronic communications such as recommendations, notifications, and alerts.
  • FIG.9 is a system diagram that shows components of one
  • system 900 of FIG.9 includes wide area network ("WAN”) / local area network (“LAN”) - (network) 905, wireless network 910, client devices 901-904, and a placement server 906.
  • WAN wide area network
  • LAN local area network
  • Buyer computer 110 and management computer 120 are identical to each other.
  • client devices 901-904 which may connect to either or both of wireless network 910 or network 905.
  • Network 150 is an embodiment of wireless network 910, network 905, or a combination of both.
  • Placement server 906 shows one embodiment, or implementation, of placement service 130.
  • data sources 140 are one embodiment of data sources 920.
  • client devices 901-904 include any computing devices that are capable of receiving and sending messages over a network, such as network 905 or wireless network 910.
  • Client devices 901-904 include personal computers, multiprocessor systems, microprocessor-based or programmable consumer electronics, mobile devices such as mobile telephones, smart phones, display pagers, tablet computers, handheld computers, laptop computers, wearable computers, or the like.
  • a Web-enabled client device can communicate across the Web. It may include a browser application that is configured to receive and to send web pages, web-based messages, or the like.
  • the browser application may send, receive and display graphics, text, multimedia, or the like, employing a network protocol such as Hypertext Transfer Protocol (HTTP), HTTP over SSL (HTTPS), and/or wireless application protocol (WAP).
  • HTTP Hypertext Transfer Protocol
  • HTTPS HTTP over SSL
  • WAP wireless application protocol
  • HTTP/S is used subsequently to refer to either of HTTP or HTTPS.
  • Client devices 901-904 may include client application programs that send and receive content to/from other computing devices. Examples of application programs include calendars, browsers and email clients and so forth. Client devices 901-904 may be configured to include an application program that enables a buyer to specify, edit and review a media plan and to view results from a corresponding placement campaign in cooperation with placement server 906. Client devices 901-904 may also be configured to include other application programs used by a media buyer, or
  • Wireless network 910 is configured to couple client devices 902- 904 with network 905.
  • Wireless network 910 may include any of a variety of wireless networks that provide a connection for client devices 902-904. Such networks may include mesh networks, wireless LAN (WLAN) networks, cellular networks, or the like. Wireless network 910 may further include network devices such as gateways routers, or the like. In essence, wireless network 910 may include virtually any wireless communication device or mechanism by which enables information to travel between client devices 902-904 and another computing device, network, or the like.
  • Network 905 is configured to couple placement server 906, and client device 901 with other computing devices, including through wireless network 910 to client devices 902-904.
  • Network 905 may include the Internet in addition to local area networks (LANs), wide area
  • WANs networks
  • direct connections combinations thereof or the like.
  • Placement server 906 represents one or more network computing devices that are configured to enable a media buyer to interactively specify a media plan, to execute a placement campaign based on the media plan, and to generate results and provide the results to client devices 901-904 for review by the buyer.
  • Placement server 906 is one embodiment of a network device that implements placement service 130.
  • Devices that may operate as placement server 906 include, but are not limited to personal computers, desktop computers, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, servers, network appliances, and the like.
  • placement server 906 is illustrated as a distinct network device, the invention is not so limited.
  • a plurality of network devices may be configured to perform the functions of placement server 906.
  • One such configuration is a "server farm" that includes multiple server computers operating cooperatively, each performing some of placement server 906 server functions.
  • One embodiment of the software modules that perform placement server 906 server functions is described with reference to FIG. 8 below.
  • Placement server 906 functions may also be provided by a cloud computing facility in which the services, features and functions ascribed herein to placement server 906 are delivered as a service over a network, such as the Internet, rather than by a specific server or cluster of servers.
  • Placement server 906 is capable of running application programs ("applications"). Applications that may be run by placement server 906 include transcoders, database programs, customizable user programs, security applications, encryption programs, VPN programs, web servers, applications servers, account management systems, and so forth.
  • Applications run by placement server 906 may also include a buyer interface, a management interface, a database manager, and other applications and processes such as those described below in conjunction with FIG. 10.
  • Placement server 906 provides web services which include any of a variety of network services that are configured to provide content, including messages, over a network to another computing device.
  • web services may include an application server, a web server, a messaging server, a File Transfer Protocol (FTP) server, a database server, a content server, or the like.
  • Web services may provide the content including messages over the network using any of a variety of formats, including, but not limited to WAP, HDML, WML, SGML, HTML, XML, cHTML, xHTML, JSON, REST, SOAP or the like.
  • Web services may also include server-side scripting languages such as PHP, Python, and Java servlets.
  • Web services may also include the server side of the Ajax web development method that enables a server to asynchronously respond to Ajax requests.
  • Placement server 906 includes a computer processor (CPU) and nonvolatile data storage for storing program code and data.
  • Data storage may include virtually any mechanism usable for storing and managing data, including but not limited to a file, a folder, a document, a web page or an application, such as a database, digital media including digital images and digital video clips, and the like.
  • Data storage may further include a plurality of different data stores.
  • data storage may represent an opportunity database, a user database and other databases such as those described below in conjunction with FIG.10.
  • data storage may also include network storage or cloud storage in which the physical storage media is accessed across a network.
  • Data sources 920 are accessed across network 905/910 from placement server 906. Typically, data sources 920 is accessed using Web services as previously described . Additionally, data sources 920 may provide data through a cloud storage facility that is accessed using protocols such as HTTP/S and FTP.
  • FIG.10 is block diagram of the exemplary software modules of buyer computer 110, management computer 120 and placement server 906.
  • buyer application 115 is a Web application, which is written using standard Web programming languages such as HTML, JAVASCRIPT, and JAVA, and is executed by a browser 1010 that runs on buyer computer 110.
  • Browser 1010 is typically a standard, commercially available, browser such as MOZILLA FIREFOX, MICROSOFT INTERNET EXPLORER, or GOOGLE CHROME. Alternatively, it may also be a client application configured to receive and display graphics, text, multimedia, and the like, across a network.
  • placement service 130 downloads web pages in HTML format to browser 1010 for viewing and interactive use.
  • the web pages may include client-side scripting instructions from a client-side scripting language.
  • client-side scripting instructions are embedded in HTML web pages and are interpreted or executed by a client- side scripting engine to perform functions not available through HTML commands such as advanced graphics, database access, and computations.
  • client-side scripting languages include JAVASCRIPT ® from ORACLE CORPORATION of Redwood Shores, CA, the Java open source programming language, ACTIVEX ® from the MICROSOFT CORPORATION of Redmond, WA.
  • browser 1010 issues HTTP/S requests to and receives HTTP/S responses from an application server 1020 running in placement service 130.
  • Application server 1020 receives the HTTP/S requests and invokes the appropriate placement server 906 service to process the request.
  • Application server 1020 may be a commercially available application server that includes a web server that accepts and processes HTTP/S requests transmits HTTP/S responses back along with optional data contents, which may be web pages such as HTML documents and linked objects (images, or the like).
  • browser 1010 may use Ajax to issue requests for XML or JSON-coded information that is delivered asynchronously by application server 1020.
  • request message will refer to a message sent by browser 1010 using HTTP/S, Ajax or other client-server
  • a response message will refer to a message sent in response, typically using the same
  • Application server 1020 establishes and manages buyer and manager sessions. Typically, application server 1020 assigns each session a unique session id. A session lasts from the time a buyer or manager logs in, or accesses placement service 130, until the time the buyer or manager logs out or stops interacting with placement service 130 for a specified period of time. In addition, application server 1020 typically manages server applications and provides database connectivity.
  • application server 1020 downloads to buyer computer 110 or management computer 120 the HTML,
  • JAVASCRIPT and other browser-executable code that make up buyer application 115 or management application 125, respectively.
  • placement server 906 includes the following modules: a buyer interface 1022, a management interface 1024, a media plan generator 1026, a campaign engine 1028, a results analyzer 1030 and a pricing engine 1032.
  • Placement service 130 further includes pristine storage 415 and five operational databases: a vehicle database 1040, an opportunity database 1042, a media plan database 1044, a user database 1046, a results database 1048 and a persona database 1050. It may be appreciated that each of the abovementioned databases may be
  • each of the modules is implemented as one or more computer files spread across one or more physical storage mechanisms.
  • each of the modules is implemented as one or more computer files spread across one or more physical storage mechanisms.
  • databases is implemented as one or more relational databases and is accessed using the structured query language (SQL) .
  • SQL structured query language
  • a non-relational database may be used .
  • Pristine storage 415 receives ingested data from data sources 140 and stores the data in normalized formats. Pristine storage 415 is updated period ically. In certain embodiments, pristine storage 415 is implemented as a separate server with data storage and a processor. In other words,
  • pristine storage 415 is implemented as a third party cloud service, such as AMAZON WEB SERVICES, which is accessible across a network.
  • a third party cloud service such as AMAZON WEB SERVICES
  • Buyer interface 1022, management interface 1024, media plan generator 1026, campaign generator 1028, results analyzer 1030, pricing eng ine 1032, and audience fit engine 1034 may each include, or may share the use of, a commercial database management system (DBMS) to access and search for data and objects that reside in the database.
  • DBMS database management system
  • RDBMS relational DBMS
  • POSTGRESQL an open source database provided by the POSTGRESQL GLOBAL DEVELOPMENT GROUP, ORACLE ® from the Oracle Corporation, SQL SERVER from the Microsoft Corporation, or the like.
  • ORACLE ® from the Oracle Corporation
  • SQL SERVER from the Microsoft Corporation
  • a non-relational database such as MONGODB
  • Buyer interface 1022 responds to requests from buyer application 115, i.e. it performs the back-end server processing .
  • Buyer interface enables a media buyer to log in to placement service 130, interactively create a media plan and view forecasts and results from the corresponding placement campaign.
  • Buyer interface 1022 provides buyer interface screens and data elements to buyer computer 110 and receives data from buyer computer 110.
  • upon request management interface 722 transmits web pages, scripts and other elements used by buyer application 115 to interactively display buyer interfaces 2A-H and 4A-D to buyer computer 110 for use by buyer application 115.
  • Management interface 1024 responds to requests from
  • management application 125 i.e. it performs the server processing corresponding to the client processing performed by management
  • Management interface 1024 enables staff persons to log in to placement service 130, review, add, edit and delete vehicles,
  • Media plan generator 1026 generates lists of opportunities, consistent with a media plan, for review, filtering and selection by a media buyer using buyer application 115. In some embodiments, media plan generator 1026 calculates vehicle power and placement quality of vehicles. Media plan generator 1026 stores media plans in media plan database 844.
  • Campaign engine 1028 executes media plans stored in media plan database 1044 by purchasing or causing to be purchased placements as indicated in a media plan.
  • Campaign engine 1028 maintains an updated status of placements during a placement campaign.
  • Results analyzer 1030 obtains campaign results data from data sources 140 via pristine storage 415 and generates prices, impressions, and other results data. Results analyzer 1030 stores results data in results database 1048. Results analyzer 1030 relies on pricing engine 1032 to perform results forecasts such as price and impressions and to determine media values and, in some embodiments, market values of placements.
  • Pricing engine 1032 forecasts results and determines results of placement campaigns. Pricing engine 832 stores results data in results database 1048.
  • Audience fit engine 1034 calculates the audience fit between opportunities and brand persona established by a buyer for a media plan. Audience fit results are stored along with the opportunities in opportunity database 1042.
  • database may refer to a relational database file that is accessed by a relational database manager, non-relational database manager, as a B-tree, R-tree, spreadsheet, flat file, comma separated value (CSV), or as any other type of suitable data structure stored within one or more computer files.
  • relational database manager non-relational database manager
  • non-relational database manager as a B-tree, R-tree, spreadsheet
  • flat file flat file
  • CSV comma separated value
  • Vehicle database 1040 stores records for each vehicle in which a placement may be made.
  • the records typically include metadata that describe properties of the vehicle such as the producer or director, artists, owner, contact information, and vehicle power.
  • Opportunity database 1042 stores records for each placement opportunity.
  • the records typically include metadata that describe properties of the opportunity such as the vehicle in which the opportunity occurs, the start and end point, the duration, a description of the scene, which actors are present, and the like.
  • Opportunity records may also store audience fit data relative to specific brand persona.
  • Media plan database 1044 stores records for each media plan prepared or being prepared by a buyer.
  • the records typically include metadata that describe properties of the media plan such as descriptive information provided by the buyer using buyer interface 200, target channel mix, opportunities selected for inclusion and exclusion, filters and other information captured using buyer interfaces 210 and 220, and opportunities to be included in the media plan.
  • User database 1046 stores a record for each buyer, management staff or other user of placement service 130. Each user record includes information such as name and contact information, username and password.
  • Buyer records may include information about buyer preferences.
  • Results database 1048 stores results from placement campaigns, typically generated by results analyzer 1030 and pricing engine 1032.
  • Results database may include price information such as market rates for conventional advertising, and price tables to be used for forecasting
  • Results database 1032 may also include historical information and information obtained from data sources 140.
  • Persona database 1050 stores persona created by a management user according to the method described with reference to FIG.7.

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Abstract

Divers modes de réalisation concernent un système d'insertion de produit qui permet à un acheteur de médias de définir un personnage. Un personnage est une représentation visuelle d'un individu fictif qui représente un public cible pour une campagne d'insertions. Une insertion est un affichage visible d'un produit qui est inséré dans un support de médias. L'invention effectue les opérations consistant à : stocker le personnage qui représente un public cible ; absorber des données relatives à des opportunités d'insertions qui identifient une ou plusieurs opportunités dont les caractéristiques chevauchent les caractéristiques du public cible ; calculer un score du public ; identifier une ou plusieurs opportunités dans lesquelles le public cible s'engage en utilisant des médias sociaux ; et calculer un score d'engagement qui mesure le niveau relatif d'engagement du public cible dans les opportunités identifiées.
PCT/US2017/037564 2016-06-14 2017-06-14 Calcul d'un score relatif à des opportunités dans un système d'insertion WO2017218712A1 (fr)

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