US20160119689A1 - Systems and Methods for Planning and Executing an Advertising Campaign Targeting TV Viewers and Digital Media Viewers Across Formats and Screen Types - Google Patents

Abstract

Systems and methods are disclosed for analyzing a fused sample of viewership data to determine a behavior profile of online viewers who watched and/or didn't watch certain TV advertisements, where the TV advertisements are aligned with campaign targeting characteristics desired by an advertiser/client working with a demand side platform. Then, a campaign targeting plan is developed for dividing an advertising budget between digital media and TV impressions. The digital media portion of the campaign profiles Media Properties (MPs) contained in a historical database from past digital advertising campaigns across multiple digital formats and screens, and aligns digital ad placement with MPs having desired targeting characteristics. An optimized apportionment is automatically produced between TV and digital media spending based on an advertiser/client's goals of duplicating or not duplicating viewership of an advertisement between TV and digital media, or alternately based on cost alone. Alternately, the apportionment can be guided interactively.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS
• This application claims the benefit of U.S. Provisional Patent Application No. 62/069,213 filed Oct. 27, 2014.
BACKGROUND OF THE INVENTION
• 1. Field of the Invention
• The present invention relates generally to systems and methods for planning and managing advertising campaigns that include both digital media advertising and TV advertising across one or more digital formats and screens.
• 2. Prior Art
• In the RTB (Real-Time Bidding) environment for electronic media impression auctions, an electronic advertising agency/consolidator operating a demand-side platform receives billions of daily auction opportunities for electronic media impressions from partners like Google®, Yahoo®, etc. These partners operate auctions for ad impressions and then place electronic ads based on auction results. A partner's auction is considered an external auction with respect to a demand-side platform where an internal auction may also be operated to determine which advertisements, also referred to herein as ads, and bids are submitted to the external auction. Each ad impression opportunity includes information parameters about the ad impression—for example, the target website, geolocation of the user, ad size, user cookie, etc, that are used for targeting purposes. The demand side platform then processes hundreds of ads in their system, supplied by advertiser clients along with desired filtering/targeting parameters, against information parameters supplied by the partner, and filters out any ads that do not qualify (for example the ad does not want to target Youtube.com®). For ads that are not removed due to a mismatch with targeting parameters, the demand-side platform then evaluates the corresponding bids that represent how much each client advertiser is willing to pay. The winning bid in the internal auction is then sent to the external auction to compete for the impression opportunity.
• Note that in some scenarios, the electronic advertising agency/consolidator operating a demand-side platform and the advertiser/client may in fact be the same entity—for instance when they comprise a large organization with an internal advertising department capable of acting as a demand-side platform. Also, in such an instance, there may be no internal auction—just a submission to an external auction.
• With the ever increasing growth of digital advertising, advertiser/clients are dealing with splitting their ad budget between TV and digital media. Digital media includes any electronic media format other than TV—essentially all digital formats that can be planned and delivered electronically. Digital media locations where an ad may be placed are called Media Properties. A Media Property or MP as described herein represents a specific instance of a media platform for electronically delivering information to a viewer. An MP as referenced herein usually refers to a website or URL on the Internet, however may also refer for example and without limitation to an App ID, a Game ID, or other digital electronic media including for example electronic billboards—small and large. Even digital watches with wireless connectivity are a form of MP.
• As used in describing the invention as defined herein, television or TV includes:
• Connected TV;
• VOD (Video on Demand);
• Broadcast TV;
• Cable TV; and
• TV programming provided online.
• VOD is further defined as systems that allow users to select and watch/listen to video or audio content when they choose to, rather than having to watch at a specific broadcast time. IPTV technology is often used to bring video on demand to televisions and personal computers. Television VOD systems can either stream content through a set-top box, a computer or other device, allowing viewing in real time, or download it to a device such as a computer, digital video recorder (also called a personal video recorder) or portable media player for viewing at any time.
• Television programming in general may be therefore viewed on conventional TV sets, or on any digital media viewing device, including without limitation PC/laptops, tablets, smartphones, and even digital watches. A viewer may be either a person, cookie, household, or any group of persons that watch the same programming—regardless of whether or not they watch simultaneously.
• Current tools for helping advertisers split their budget between TV and digital media only deal with MP categorizations in aggregate, and typically only with respect to demographic characteristics such as age and gender. Methods are needed to more precisely plan and predict cross format ad campaigns where both TV and digital media are targeted in the same campaign. In particular, it would be useful to plan a campaign such that viewers who did not watch certain TV ads get to see them on digital media. It would also be useful at times to reinforce the viewing of certain TV ads by targeting the same viewers on digital media in order to increase the frequency of viewership of those ads.
• Specific problems faced by a planner at an advertiser/client may include (written from the perspective of the planner):
• • Roughly how much incremental reach can I get by spending a portion of my TV budget on online video?
  • How do I get a controlled amount of additional frequency of impressions against targets that have likely seen my ads on TV?
  • Exactly how much should I spend on online video ads based on various goals: budget, frequency, reach, viewable?
  • How can I execute the digital and television portions of the campaign as easily as possible on an electronic platform, where planning and execution are integrated?
  • Exactly how much of the next campaign's share of budget should I spend on video?
  • How much should I spend on VOD and other avenues that provide incremental reach? How can I execute and track my ad spend across all formats easily?
• More specifically, a planner may have the following needs and goals (written from the perspective of the planner):
• • 1. As a Planner, I need the latest data to be included in the TV Planning tool so that I can be confident in the results of the tool, by recognizing that the data from my historical TV buy is correct.
  • 2. As a Planner, I need to have access to the correct and up-to-date data from the demand-side platform so that I can compare costs and reach versus my TV buy data historically.
  • 3. As a Planner, I need to view the impact of shifting away some of my historical TV budget to online video advertising (executed via a demand-side platform) so that I can assess the impact of this shift on the unduplicated reach gains I can achieve.
  • 4. As a Planner, I need to be able to easily execute a campaign with a demand-side platform for the online video ad portion based on the hypothetical TV and OLV (digital media) spend that I create in the planner, so that I can save time and reap the benefits around transparency and delivery that the demand-side platform offers.
  • 5. As a Planner, I need to be able to apply a discount to the ‘rack rates’ that are quoted as ‘spend’ in the Nielsen TV data so that discounts I received from networks are included in the analysis, making my hypothetical spend plan more realistic.
  • 6. As a Planner, I need to be able to ‘save’ a draft spending plan that I can access later so that I don't have to set up the analysis again after I've considered the plan over some time.
  • 7. Preferably, the planning tool must be available via a public-facing website so I can easily perform prototype plans.
  • 8. As a Planner, I need to be able to have the planning tool figure out the optimal amount of online video ad spend based on at least three different types of goals given the overall historical TV budget: maximize unduplicated reach at the same budget, maximize frequency at the same budget, and the most cost-effective reach across all available digital and TV formats and screens, so that I can tune my spend optimization to my particular marketing goal.
DEFINITIONS
• • Planner—a user of the invention including one who operates/uses the user interface. A planner may belong to a DSP organization or to an advertiser/client organization.
  • Media avails or “avails”: Unsold units of time available for broadcasters to sell to advertisers. The number of impressions available for purchase on a daily or monthly basis for a given media property.
  • TV Base Plan: A TV advertising campaign that has already been run and where historical viewer information is available
  • OT CPM: Cost-per-Impression (per 1,000 impressions) for on-target impressions
  • Incremental reach: Viewers reached (by the invention) that were not reached by the TV Base Plan
  • PTV—“Programmatic TV”
  • CPM—cost per 1,000 impressions
  • CPP—cost per (GRP) point
  • eCPM—ad revenue generated per 1,000 impressions
  • eCPP—ad revenue generated per (GRP) point
  • VOD—Video on Demand
  • OLV—Online Video
  • MVPD (Multichannel Video Programming Distributor)
  • Xscreen or Cross-Screen—Campaigns that target multiple diverse screens: TV; Desktop; tablet; smartphone; etc.
  • HH—Household
  • Demo and Demo Targeting—Demographic Segment (Age and Gender)
  • Strategic Targeting—Targeting other than Demographic. Strategic targeting can include without limitation and for example any or all of: buying behavior; income; ethnicity; education; children; home; auto; and pets.
  • Media Property or just “Property”—Any screen type where an advertisement may appear
  • Daypart—Portions of a day where media may be viewed
  • Demand-Side Platform (DSP) An organization that performs an advertising agency function for advertisers/clients to plan and operate advertising campaigns on their behalf. A DSP (such as TubeMogul, Inc.) may develop and operate a proprietary system for planning and executing advertising campaigns, including profiling Viewers and Media Properties. Such as DSP operated system is also a source of data from previous advertising campaigns. Note that a DSP may represent client companies, or alternately be captive to a company or operate as a department within a company.
  • Fusion—A source of 3^rdparty data (e.g., Nielsen) that merges multiple and diverse datasets of viewership information into a single database.
  • NPN—A source of 3^rdparty data such as Nielsen's “National People Meter”
  • SSP—Supply Side Partner
  • DSP—Demand Side Platform
  • Sites—Websites
  • DT—Desktop
  • Linear TV—Conventional time-and-channel-based TV
  • KPI—Key Performance Indicator
  • Comscore—a 3^rdparty provider of data regarding advertising campaigns
  • Nielsen—a 3^rdparty provider of viewership data and related tools
BRIEF DESCRIPTION OF THE DRAWINGS
• FIG. 1 shows an overview block diagram describing system components and data flow for a demand side platform according to the invention, with a focus on planning and executing a future cross format campaign.
• FIG. 2 shows a flow chart describing a process for planning a cross format campaign with emphasis on reaching unexposed TV viewers.
• FIG. 3 shows a flow chart describing a process for planning a cross format campaign with emphasis on reinforcing viewership.
• FIG. 4 shows a flow chart describing a process for planning a cross format campaign with emphasis on achieving the lowest cost per impression.
• FIG. 5 shows a matrix defining different data sets used for cross format advertising campaign planning.
• FIG. 6 shows how the various data sets ofFIG. 5 are linked and analyzed in creating a cross format advertising campaign.
• FIG. 7 shows one exemplary user interface for the planning stage of a cross format campaign.
• FIG. 8 shows an exemplary user interface for the planning stage of a cross format campaign where a planner may observe the effect of shifting portions of their TV advertising budget to digital media.
• FIG. 9 shows an alternative functionality for guiding the split between TV ad spending and digital media ad spending.
• FIG. 10 shows the user interface for a planning tool according to the invention which allows planners to adjust their campaign and observe projected results in terms of on-target impressions, GRPs, and cost.
• FIG. 11 shows a planning tool for a cross format platform focused on GRP or CPM results and including advanced (strategic) targeting choices.
• FIG. 12 shows an additional planning tool for a cross format campaign including a graph indicating incremental reach.
• FIG. 13 shows an additional planning tool for a cross format campaign where results are shown in terms of CPP (cost per GRP point) and cost for on target impressions.
• FIG. 14 shows an additional planning tool for cross format campaign including target placements for both TV and digital media.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
• Systems and methods are disclosed for analyzing a fused sample of viewership data to determine a behavior profile of online viewers who watched and/or didn't watch certain TV advertisements, where the TV advertisements are aligned with campaign targeting characteristics desired by an advertiser/client working with a demand side platform. Then, a campaign targeting plan is developed for dividing an advertising budget between digital media and TV impressions. The digital media portion of the campaign profiles Media Properties (MPs) contained in a historical database from past digital advertising campaigns across multiple digital formats and screens, and aligns digital ad placement with MPs having desired targeting characteristics. An optimized apportionment is automatically produced between TV and digital media spending based on an advertiser/client's goals of duplicating or not duplicating viewership of an advertisement between TV and digital media, or alternately based on cost alone. Alternately, the apportionment can be guided interactively.
• FIG. 1 shows an overview block diagram describing system components and data flow for a demand side platform according to the invention, with a focus on planning and executing a future cross format campaign based on 3^rdparty TV and digital viewership information combined with historical digital media viewership information compiled over past campaigns by the demand side platform. InFIG. 1, the overview block diagram100 for a system according to the invention includes a DSP (demand-side platform)114 that interacts with advertiser/clients116;supply side partners102; andsources124 of third party viewership data. The demand-side platform114 utilizes automation software operating on one or more servers/processors112 to bid forad slots104 to be shown toviewers108 via media property orTV programming106. Online advertising and/or TV programming supply side partner(s)102 typically provide a sale opportunity or bidrequest package110—typically including ad slot data—to the demand-side platform114. The demand-side platform will, in turn and if appropriate, provide aresponse118 to supplyside partner102, that response including a bid and either an advertisement or information describing an advertisement. The decision to bid, and how much to bid, is automatically calculated by software running on the one ormore servers112 where targeting andplanning information120 supplied by advertiser/client116 is processed. Such information may include for example and without limitation: desired on-target impressions; campaign targeting parameters; campaign runtime; campaign budget; maximum bid; and TV campaign data and desired campaign strategy. During the campaign planning stage, the DSP provides campaign cost estimates122 and estimates for results to advertiser/clients116.
• FIG. 2 shows a flow chart describing a process for planning a cross format campaign where an advertiser/client wishes to plan the campaign such that viewers who did not watch certain ads on TV get to see them on digital media, thereby increasing the reach of the campaign—the process referred to as optimization by de-duped reach. In step S202 a fused data set of viewership data is received that includes both TV viewing and digital media viewing of advertisements, and where for a plurality of specific viewers watching TV advertisements the data set includes digital media viewership data for those specific viewers. In step S204, a list of proposed or historical TV advertisements is received for a particular advertiser/client. In step S206, the fused data set is analyzed for each respective TV advertisement to:
• • (i) identify those viewers in the fused data set who are categorized as NOT WATCHING the TV advertisement;
  • (ii) identify viewer characteristics of the viewers categorized as NOT WATCHING the TV advertisement; and
  • (iii) produce a list of MPs visited by the viewers in the fused data set categorized as NOT WATCHING the TV advertisement, and identify specific characteristics of those MPs;
• In step S208, targeting criteria from an advertiser/client is received for a future campaign. In step S210, a historical database containing data from online advertising campaigns is analyzed, and based on the received targeting criteria for the future campaign and the data from online advertising campaigns, a model for the future campaign is produced that includes a proposed budget split between TV and online placement of advertisements.
• FIG. 3 shows a flow chart describing a process for planning a cross format campaign where an advertiser/client wishes to plan a campaign such that the viewing of certain ads on TV is reinforced by targeting the same viewers on digital media in order to increase the frequency of viewership of those ads—the process referred to as optimization by increased frequency. In step S302, a fused data set of viewership data is received that includes both TV viewing and digital media viewing of advertisements, and where for a plurality of specific viewers watching TV advertisements the data set includes digital media viewership data for those specific viewers. In step S304, a list of proposed or historical TV advertisements is received for an advertiser/client. Instep306, the fused data set is analyzed for each respective TV advertisement to:
• • (i) identify those viewers in the fused data set who are categorized as WATCHING the TV advertisement;
  • (ii) identify viewer characteristics of the viewers categorized as WATCHING the TV advertisement; and
  • (iii) produce a list of MPs visited by the viewers in the fused data set categorized as WATCHING the TV advertisement, and identify specific characteristics of those MPs;
• In step S308, targeting criteria is received from an advertiser/client for a future campaign. In step S310, a historical database containing data from online advertising campaigns is analyzed, and based on the received targeting criteria for the future campaign and the data from online advertising campaigns, a model for the future campaign is produced that includes a proposed budget split between TV and online placement of advertisements.
• FIG. 4 shows a flow chart describing a process for planning a cross format campaign where an advertiser/client wishes to plan a campaign such that the lowest cost per impression is achieved without regard to whether or not a TV viewer sees the same ad on digital media—the process referred to as optimization by “cheapest to reach”. Instep402, a fused data set of viewership data is received that includes both TV viewing and digital media viewing of advertisements, and where for a plurality of specific viewers watching TV advertisements the data set includes digital media viewership data for those specific viewers. Instep404, a list of proposed or historical TV advertisements is received for an advertiser/client. Instep406, the fused data set is analyzed for each respective TV advertisement to:
• • (i) identify those viewers in the fused data set who are categorized as WATCHING OR NOT WATCHING the TV advertisement;
  • (ii) identify viewer characteristics of the viewers categorized as WATCHING OR NOT WATCHING the TV advertisement; and
  • (iii) produce a list of MPs visited by the viewer in the fused data set categorized as WATCHING OR NOT WATCHING the TV advertisement, and identify specific characteristics of those MPs.
• Instep408, targeting criteria is received from an advertiser/client for a future campaign. In step S410, a historical database containing data from online advertising campaigns is analyzed, and based on the received targeting criteria for the future campaign and the data from online advertising campaigns, a model for the future campaign is produced that includes a proposed budget split between TV and online placement of advertisements.
• For the processes ofFIGS. 2, 3, and 4, the campaign model includes target lists for both TV demographics and MPs targeted for digital media. The lists are combined and sorted to produce an overall target list for a campaign. The combined list can be then sorted by cost efficiency (cost per on-target impression) to produce a prioritized targeting list for the future campaign.
• Note that TV viewership information used in the process may be related to past advertising campaigns for TV or may alternately be projected TV viewership information. Characteristics of MPs may include without limitation one or more of demographic information; the cost of purchasing impressions on the MP; a historical “reach” for the MP which reflects how frequently impression opportunities arise for that MP. Note that ad campaigns usually have a specified run time, and if a particular MP has a very small reach it may contribute little value to a campaign if impression opportunities for that MP appear infrequently.
• Optimization for a campaign targeting both TV and digital media can be performed for cost and/or for reach, including optimization for CPMs (Cost per 1,000 on-target impressions) and/or GRPs (Gross Rating Points).
• A campaign planner at an advertiser/client needs the latest data to be included in a cross format planning tool so that they can be confident in the results of the tool, by recognizing that the data from their historical TV buy is correct. This is accomplished by:
• • building a historical record of the previous year's data
  • using the planning tool by month, quarter, or year
  • handling updates from a 3^rdparty (e.g., Nielsen) when they correct data
  • identifying when there are gaps in the datasets, indicating where for some reason all the data is not available
  • acquiring datasets from a 3^rdparty that tracks viewership equivalent to the following datasets available from Nielsen:
    • National People Meter;
    • Netview & VideoCensus;
    • Fusion; and
    • Monitor Plus
• Note that 3^rdparty viewership data suppliers may supply data indicative of a viewer panel and/or actual viewership data acquired by monitoring a large number of viewers over time. The most prominent supplier of viewership data today in the United States is Nielsen, however other sources of viewership data exist, and without limitation such other sources may include for example Barb in the UK, OZTam in Australia, and Rentrak in the US. The embodiments described herein do not rely on any specific supplier of viewership data, and any specific mention of data packages supplied by, for example Nielsen, are only exemplary.
• FIG. 5 shows a matrix defining different data sets used for cross format advertising campaign planning. Four data sets502-508 of the five total data sets are examples of those available from third-party viewership data suppliers such as, for example, Nielsen. As shown inFIG. 5, theNational People Meter502 shows minute by minute TV viewing and when supplied by Nielsen contains for example 55,000 respondents—the majority of whom have Internet access and recording devices for Internet activity. The data set entitled NetView &VideoCensus504 when supplied by Nielsen contains for example 200,000 respondents with Internet activity tracking. TheFusion data set506 contains approximately 255,000 respondents where TV and Internet usage is fused and extrapolated. The data set entitled Monitor plus508, when supplied by Nielsen, shows TV activity with related cost data.Data set510, supplied by a demand-side platform, provides Internet site (MP) data and related advertising data. For each supplied data set, descriptions forContents512,Sample Size514, and Key Elements for thePlanner516 are shown.
• FIG. 6 shows how the various data sets ofFIG. 5 are linked and analyzed in creating a cross format advertising campaign. Note in particular for linkage number “3”602 that demographic characteristics of those viewers tracked for Internet and TV usage are linked to TV and online video ad data. For linkage number “4”604 inFIG. 6, sites (MPs) visited by viewers who saw particular TV ads are linked with sites they did NOT visit. This linkage is required for de-duped (un-duplicated) reach. Sites (MPs) unseen by those who saw a TV ad can be used by the DSP to generate a cross format campaign for incremental reach as described herein.
• FIG. 7 shows one exemplary user interface for theplanning stage702 of a cross format campaign, where an advertiser/client'scurrent plan704 for TV advertising is analyzed706 to provide a baseline. Theaudience708 for the plan is entered, includingGender710, which can be Male, Female or All genders. The targetedage bracket712 for the TV plan is entered by independently positioningslider nodes716 and718 on horizontalage bracketing tool714 to visually bracket the targeted ages. A functionality of the user interface ofFIG. 7 includes a histogram graph showing aviewer population distribution720 that appears under horizontalage bracketing tool714, and can be optionally truncated at either or both ends as either or both ofslider nodes716 and718 are moved to indicate the age distribution within the specifically bracketed ages. Also, as either or both ofslider nodes716 and718 are moved, the targeted (bracketed)population712 is automatically updated. At the bottom left, a Discount from Rack Rate722 can be entered.Timeframe724 to be analyzed for the plan is entered and a summary ofresults726 is automatically presented to the planner. The exemplary and non-limiting summary ofFIG. 7, includes: Reach; Reach (%); gross impressions; GRPs; average frequency; total cost; eCPM; and eCPP.
• FIG. 8 shows an exemplary user interface for the planning stage of a cross format campaign where a planner on behalf of a client advertiser may observe the effect of shifting portions of their TV advertising budget to digital media, in this figure referred to as online video ads or (OLV). Here, in thebox802 at the upper left, the planner Optimizes by Target by choosing from three basic strategies for the cross format campaign that can be automatically calculated according to the invention based on the data sets supplied:
• • (i) “Are the cheapest to reach”—where the campaign combines TV and digital media without concern for whether or not digital media viewers in the fused data set saw or did not see ads on TV;
  • (ii) “Didn't see my ad on TV”—where the strategy is focused on de-duplication in order to increase the reach of the combined campaign; and
  • (iii) “Saw my ad on TV”—where the strategy is focused on reinforcing TV viewership with online impressions in order to increase the frequency of the combined campaign.
• Alternately, a planner can manually optimize the campaign by manipulating aslider bar804 located at the left side of the display shown inFIG. 8. The position of the bar affects both the reach and cost of the campaign, and as the slider bar is manipulated the resultant parameters shown on the right side of the screen inFIG. 8 are automatically calculated and change accordingly to display the calculated parameters. Asslider bar804 is moved horizontally, a choice is automatically made forreach808 with respect to proportions ofOLV810 versus TV Only812. Also with respect to impressions, a choice forCPM814 is automatically made with respect to a percentage shift towards OLV.
• On the right-hand side of the user interface display ofFIG. 8,parameters816 guide the plan for this advertising placement that was set in other screens are shown and include the brand; the demographic age/gender parameters; and the timeframe. As key parameters on the left hand side ofFIG. 8 with respect to shifting between TV and OLV are changed by a planner utilizing this user interface, results are automatically updated by underlying processes according to embodiments of the invention. For instance, a new percentage forunduplicated reach818 is displayed as well as a change inaverage frequency820. Estimated numbers ofimpressions822 are updated along withfinancial savings824 resulting from the plan. Finally, at the bottom right ofFIG. 8 is a summary826 for the plan, includingparameters726 that were shown with respect toFIG. 7. ForFIG. 8 however, these projected results are shown separately with respect to aTV Schedule828; and Online Video Ad Schedule830; and aCombined Schedule832.
• FIG. 9 shows an alternative functionality for guiding the split between TV ad spending and digital media ad spending. Similar toFIG. 8, but with a different graphical appearance, choices for automatic optimization bytarget802 is shown in the upper left corner of the user interface display ofFIG. 9. Similar toFIG. 8, the basic strategy is chosen by the planner to be one of “cheapest to reach”; “did not see my TV ad”; and “did see my TV ad”. Below targetingchoice802, a radial dial mechanism forbudget adjustment902 is presented at the left whereby the planner can choose the percentages for the split between TV and Online Video. A unique fan shapedgraphical input mechanism906 is presented to the planner where by draggingnode904 left or right around the arc offan906, a budget shift can be defined between TV and Online Video. Alternately, ashift percentage908 may be entered, or adollar amount910 can be entered to define the shift.
• Asfan dial906 is rotated, resultant projected parameters are automatically calculated and displayed at the right along with example online placements. At the top right of the display, prominent boxes are shown with parameter changes to help guide the planner including: a New Incremental Reach912; a Change inFrequency914; a Change inImpressions916; andPer CPM Savings918. At the center-right of the display is agraph920 showing a percentage reached of the population with respect to the percentage split between OLV and TV. Specific graphs for TV-Only922, OLV+TV924, and OLV-Only926 are shown along with anoverall CPM savings928.
• At the bottom of the user interface display ofFIG. 9 is aresult summary930, which is similar to summary826 ofFIG. 8, and also asummary932 of online placements characterized by viewer interest area—including for example and without limitation: men's lifestyle; sports; automotive; and fitness. Included for each of these viewer interest areas is either a projected cost as shown in the display example, or alternately projected impressions. Which of cost or impressions are shown for the placement breakdown at the lower right ofFIG. 9 is controlled byselector934.
• FIG. 10 shows the user interface for a planning tool which allows planners to adjust their campaign and observe automatically projected results in terms of on-target impressions, GRPs, and cost. This tool was previously shown and described in co-pending U.S. Patent Application Publication No. 2014-0278912 entitled: “Systems and Methods for Predicting and Pricing of Gross Rating Point scores by Modeling Viewer Data”. When used in conjunction with cross format planning tools such as those shown inFIGS. 7, 8, and 9, the user interface shown inFIG. 10 now incorporates data and planning for a cross format campaign targeting both TV advertising and digital media advertising.
• At the top of the exemplary user interface display ofFIG. 10 is an information bar1002 that contains: the name of the placement; a mechanism for choosing the campaign and editing options; the particular planner's email address; and a search tool. At the top left side are selectors for planning according toCPM1004 orGRP1006. Under these selectors is an audience targeting mechanism similar to that previously shown inFIG. 7, and includesselection702 for age and gender, and in particular includeshorizontal selector bar718 with individually positionedslider nodes716 and718 that are manipulated by the planner to bracket the lower and upper bounds respectively of the targeted age bracket. As withFIG. 7, agraphical histogram720 of the age distribution bracketed byselector bar718 is also shown. Placement parameters are entered here such as for example and without limitation aGRP goal1008 that may be entered as well as aFrequency Cap1010. At the bottom left of the user interface display ofFIG. 10 are additional placement parameters such as budgeting controls1012, includingdates1014 and abudget1018. A planner may further select particular dayparts to address by clicking thedaypart selector1016 which brings up a user interface facility for daypart selection. An inventory tier1020 to be utilized is chosen at the bottom left. A planner may choose one or more classifications or segmentations of MPs to be addressed by a campaign, herein labeled “Inventory Tiers”1020. For this non-limiting example, available classifications include tiers ranging from MPs that are very well-recognized to those that are less recognizable. For example,Tier 1 can represent sites a user's friends and family would recognize.Tier 2 can represent MPs with lower brand recognition or awareness.Tier 3 can represent brand-safe sites that are niche or reach. “Brand safe” refers to MPs where there is nothing controversial such as guns, sex, violence, or alcohol, etc. “Niche” means there is a smaller audience, such as for instance a site for vegan cooks. “Reach” sites are MPs with huge audiences and many demographics such as YouTube, CBS, etc. Reach sites provide broad exposure, however with little specific brand alignment.
• On the right-hand side of the user interface display ofFIG. 10 are forecasted results including at the top projectedCPP1022; projected On Target CPM and %1024; and a GRP Goal and Expectedvalue1026. A mechanism is also included to RevertChanges1028. Agraph1030 of projected GRP results is shown with respect to budget, and anannunciator1032 is shown positioned on the graph in response to a value entered asbudget1018. Projectedtotal impressions1034 are shown at the bottom right along with projectedtotal GRPs1036 and projectedUniques1038.
• FIG. 11 shows a planning tool for a cross format platform focused on GRP or CPM results and including advanced/strategic targeting choices that go beyond simple age and gender to include viewer characteristics such as for example and without limitation: income; marital status; education; presence of children; homeownership; and ethnicity. Also included are exemplary choices for advanced targeting of buyer behavior—which could be either modeled or actual behavior—in this instance targeting a specific product or service that a shopper might buy and also targeting a frequency for their purchase of that product or service. Also included are choices of different target screen formats for display platforms including platform variations for both TV and digital media, ensuring that planners using the tool perFIG. 11 have the ability to optimize for de-duplication or reach across all formats and screen types.
• At the top ofFIG. 11, afacility1102 for loading previous media plans is provided and includes adate range1104 and atimeframe specification1106 that provides for specification of quarters or a full year. Below that, a facility forbudget entry1108 is provided for planning a new campaign with a specifieddate range1110 andbudget1112. Next, campaign goals are specified that include advanced/strategic targeting1114; age bracket targeting1128; and shopper targeting1130. Advanced/strategic targeting1114 includes targeting for:income1116;marital status1118;education1120; presence ofchildren1122;home ownership1124; and ethnicity1126. Age bracket targeting1128 utilizes a horizontalage bracketing tool714 as previously shown inFIG. 7, with independently positionedslider nodes716 and718 to visually bracket the targeted ages.Age bracketing tool714 is linked withhistogram graph720 showing a viewer population distribution that appears under horizontalage bracketing tool714, and can be optionally truncated at either or both ends as either or both ofslider nodes716 and718 are moved. Shopper targeting1130 shows for this example targeting shoppers who buytoothpaste1132, however this is exemplary and drop-down arrows allow editing to target a wide variety of products and services.Frequency1134 for a viewer's purchase of a product or service can also be targeted. At the bottom of the user interface display ofFIG. 11 is the ability to select differentcross screen formats1136 for targeting. An exemplary list of screen types shown for targeting includes without limitation: TV; Addressable TV; Online video; VOD; Mobile; Tablet; and Network extension.
• FIG. 12 shows an exemplary user interface for an additional planning tool for a cross format campaign, where a planner may view/edit1202 a plan. Aneditable strategy summary1204 is shown in the upper left, includingdate range1206,budget1208, and targeting criteria similar to those shown inFIG. 11, including gender targeting1210 and age bracket targeting1128, plus advanced/strategic targeting including for example and without limitation:income1214;marital status1216;education1218; presence ofchildren1220;home ownership1222; and ethnicity1224.
• At the top right of the user interface display ofFIG. 12 is agraph1238 showing % Reach with respect to Budget, and with the results broken down with separate subgraphs for different display platform types including: TV; online; mobile; and VOD. The Incremental Reach fromDigital1242 has been automatically calculated and is specifically shown at the point on the graph corresponding to the specified budget amount. Anannunciator balloon1240 is shown aligned with the specified budget number on the horizontal axis of the graph, and includes within annunciator balloon1240 a display of the specified budget number and the average CPM.
• A prioritized list ofplacement targets1226 is shown at the lower left that resulted from the process shown inFIG. 2 for a campaign where the overriding strategy is incremental reach via non-duplication between TV and digital media. Here a “Combined”list1228 is shown, however the list can be shown specifically focused on any of the following formats by selecting the appropriate tab: TV; Addressable TV; Online video; VOD; Mobile; Tablet; and Network extension. The displayedplacement list1228 can be sorted by spend or sorted by format1236. Network names are displayed1230 with logo and editable checkboxes for inclusion/exclusion.Horizontal bar graphs1232 are included to visually indicate relative spending, and forecasted dollar spend1234 is additionally shown. At the bottom center of the user interface display, agraph1244 of relative media format mix is shown with horizontal bars for each format type including a percentage for each format as well as CPMs and CPPs. To the right of themedia mix graph1244 are prominent boxes indicatingaverage CPM1246 andaverage CPP1248.
• FIG. 13 shows an additional planning tool for a cross format campaign. Here, the results are shown in terms of CPP (cost per GRP point) and cost for on target impressions. Also shown are prioritized lists of placement targets, where a different prioritized list has been established for each of a plurality of display platform types. At the upper left of the user interface screen ofFIG. 13 is a strategy summary for a cross format plan that was previously shown as part of the user interface ofFIG. 11.Date range1110 andbudget1112 are shown along with a targetingsummary1114 including conventional age/gender demographic targeting as well as advanced/strategic targeting for: income; marital status; education; presence of children; homeownership; and ethnicity. At the top right of the user interface display ofFIG. 13 is agraph1316 showing GRPs versus budget with a specifiedbudget1320 indicated by a horizontal dotted line, andannunciator balloon1318 shown vertically above the specified budget location on the horizontal axis, where the annunciator balloon additionally indicates the budget number. At the right ofgraph1316 are prominent boxes displaying:CPP1322; On target CPM and %1324; andGRPs1326.
• At the bottom of the user-interface display ofFIG. 13 is aplacement summary1304 similar tosummary1226 ofFIG. 12, however here the tab forMobile1302 has been selected, and thereforeplacements1304 shown below indicate placement specifically planned for viewing on mobile devices. For each entry, alogo1306 is typically displayed next to a network name, and for networks where reservations are appropriate or required for placement a button marked “Reserve”1312 is shown. Note that some network categories such as1308 have subnetworks1310 where placements may be individually planned, and an arrow icon at the left of the network name allows expansion below to revealavailable subnetworks1310, in this example ESPN.com and FOXSports.com. Most of the parameters shown on the user interface ofFIG. 13 that guide placements for an advertising campaign are editable, and in addition to editing individual fields, sites can be added to the placement list by selectingbutton1314.
• FIG. 14 shows an additional tool for reviewing a cross format campaign prior toexecution1402, includes target placements for both TV and digital media, and including campaign start and end dates, and projected costs. Abutton1440 is provided to move from this tool to a tool as shown for example inFIG. 10 from where a final view of the projected campaign can be examined followed by executing the campaign. At the top of the exemplary user-interface display ofFIG. 14 is aTV Reservation List1404, displaying a summary of networks that have been added to the reservation list where reservations are appropriate or required for placement on a particular network. At the left ofReservation List1404, placement names are shown1408, including projected GRPs, network name, and an annunciator icon that includes the particular type of placement, such as TV or OLV. Date ranges1410 are shown for each placement along with network name andlogo1412. Also shown for each reserved placement are: projectedCPM1414; projectedimpressions1416; andstatus1418. For each reserved placement, atool icon1420 is shown that allows the planner to observe and edit options for the particular reserved placement. Also, for each reserved placement a “Send”button1422 is provided to send the request for placement reservation as well as amaster button1424 that enables the planner to send all reservation requests at once.
• The bottom of the exemplary user-interface display ofFIG. 14 is a summary ofOnline Placements1406. Here, for each placement, the Placement name is shown along with: Date ranges1434; projectedCPMs1436;Impressions1438; and projectedCost1442. When a planner wishes to see more detail for a given placement such as network anddaypart information1432, an arrow annunciator icon such as that shown for theSports category1426 can be clicked, displaying additional detail on specific network placements falling within the selected (Sports) category. In this example, there are two sub-placements within the Sports placement category: ESPN.com shown as aMobile placement1428 and FOXSports.com shown as anOnline placement1430. Note thatDaypart information1432 is then viewable for both the ESPN and FOXSports placements.
• The processes performed as described herein are implemented as engines (sequential machines) running on one more processors, wherein the engines:
• • receive input from a user/planner through a realtime user interface;
  • access various databases;
  • compute estimated campaign results in realtime;
  • report those estimated results to the user/planner through the realtime user interface;
  • enable and control the execution of the advertising campaign; and
  • report to the user/planner the results of the actual advertising campaign.
• Note that the quantity and complexity of the data and tasks involved in operating the invention make implementation of the invention impossible without the aid of one or more sequential machines—typically sequential processes operating on the one or more processors referred to above—and also use of a hardware communications infrastructure—typically the Internet. During the analysis and actionable processes involved, millions of data elements must be considered and without using a machine as part of the invention, implementation of the claimed processes would not be possible. Typically a Demand Side Platform (DSP) MUST both analyze and respond to an ad slot opportunity in less than 100 milliseconds. Performing the claimed processes with “pencil and paper” is impossible for many reasons, as is performing the process without the Internet. In fact, the entire process with respect to online advertisements requires an intimate usage of the Internet for the Demand Side Platform to communicate with: supply-side platforms; advertising exchanges; advertising networks; and attribution partners. The DSP must receive bid request packages, place bids, and supply the ads themselves in milliseconds via the Internet. Then, after a campaign has run, the DSP automatically receives attribution data from attribution partners. The preceding description names only some of the automated processes and actions involved in implementing the invention as claimed.
• The claims reflect a computerized process since, at this time, computing resources have evolved to include “Cloud-based” computing as described above in the Background section. As such, it is also impossible to predict where (physically) the claimed processes will be executed and/or if they will be distributed across multiple machines. It is also impossible to predict the specific ownership of machines whereupon the claimed processes will be executed, and therefore against whom the claims would protect against should the claims instead have been written as system claims as opposed to the method claims attached hereto.
• The foregoing detailed description has set forth a few of the many forms that the invention can take. It is intended that the foregoing detailed description be understood as an illustration of selected forms that the invention can take and not as a limitation to the definition of the invention. It is only the claims, including all equivalents that are intended to define the scope of this invention.
• At least certain principles of the invention can be implemented as hardware, firmware, software or any combination thereof. Moreover, the software is preferably implemented as an application program tangibly embodied on a program storage unit, a non-transitory machine readable medium, or a non-transitory machine-readable storage medium that can be in a form of a digital circuit, an analog circuit, a magnetic medium, or combination thereof. The application program may be uploaded to, and executed by one or more machines comprising any suitable architecture. The various processes and functions described herein may be either part of microinstruction code or part of one or more application programs, or any combination thereof, which may be executed by one or more CPUs, whether or not such machine(s) or processor(s) are explicitly shown. In addition, various other peripheral units may be connected to machine platforms such as one or more data storage units and printing units.

Claims (30)

What is claimed is:

1. A computerized method for planning an advertising campaign targeting both TV and online impressions, whereby one or more processors perform the computerized method, comprising:

receiving a fused data set of viewership data that includes TV viewing and digital media viewing of advertisements, and where for a plurality of viewers watching TV advertisements the fused data set includes digital media viewership data for those viewers;

receiving a list of TV advertisements for an advertiser/client;

analyzing the fused data set to:

for each of the listed TV advertisements, identify those viewers in the fused data set who are categorized as not watching the respective listed TV advertisement;

identify viewer characteristics of the viewers categorized as not watching the respective listed TV advertisement, and

produce a list of MPs visited by the viewers in the fused data set categorized as not watching the respective listed TV advertisement, and identify specific characteristics of those MPs;

receiving targeting criteria from the advertiser/client for a future campaign; and

analyzing a historical database containing data from digital media advertising campaigns, and based on the received targeting criteria for the future campaign and the data from digital media advertising campaigns, producing a model for the future campaign that includes a proposed budget split between TV and digital media placement of advertisements.

2. The computerized method ofclaim 1 wherein the categorization of viewers not watching the listed TV advertisements includes viewers who did not watch the listed TV advertisements in the past.

3. The computerized method ofclaim 1 wherein the categorization of viewers not watching the listed TV advertisements includes one or both of viewers who did not watch the listed TV advertisements in the past or viewers who are projected to not watch the listed TV advertisements in the future.

4. The computerized method ofclaim 1 wherein the specific characteristics of the MPs in the list of MPs includes at least demographic characteristics.

5. The computerized method ofclaim 1 wherein the specific characteristics of the MPs in the list of MPs includes at least characteristics related to cost of purchasing impressions on each MP.

6. The computerized method ofclaim 1 wherein the specific characteristics of the MPs in the list of MPs includes at least reach characteristics.

7. The computerized method ofclaim 1 wherein the model for the future campaign is optimized for at least one of cost or reach.

8. The computerized method ofclaim 1 further comprising generating a target list of MPs visited by the viewers in the fused data set categorized as not watching the listed TV advertisements, and that are described in the historical database with respect to:

a demographic profile of each MP;

a historical cost of purchasing impressions on each MP; or

a historical reach of each MP.

9. The computerized method ofclaim 8 further comprising generating a combined target list for the future campaign by:

creating a combined list of TV demographic targets combined with the target list of MPs; and

sorting the combined list with respect to cost efficiency for on-target impressions.

10. The computerized method ofclaim 9 further comprising executing the future campaign by initially targeting advertising opportunities in the combined list that have a lowest cost for on-target impressions.

11. A computerized method for planning an advertising campaign targeting both TV and online impressions, whereby one or more processors perform the computerized method comprising:

receiving a fused data set of viewership data that includes TV viewing and digital media viewing of advertisements, and where for a plurality of viewers watching TV advertisements the fused data set includes digital media viewership data for those viewers;

receiving a list of TV advertisements for an advertiser/client;

analyzing the fused data set to:

for each of the listed TV advertisements, identify those viewers in the fused data set who are categorized as watching the respective listed TV advertisement;

identify viewer characteristics of the viewers categorized as watching the respective listed TV advertisement, and

produce a list of MPs visited by the viewers in the fused data set categorized as watching the respective listed TV advertisement, and identify specific characteristics of those MPs;

receiving targeting criteria from the advertiser/client for a future campaign; and

analyzing a historical database containing data from digital media advertising campaigns, and based on the received targeting criteria for the future campaign and the data from digital media advertising campaigns, producing a model for the future campaign that includes a proposed budget split between TV and digital media placement of advertisements.

12. The computerized method ofclaim 11 wherein the categorization of viewers watching the listed TV advertisements includes viewers who watched the listed TV advertisements in the past.

13. The computerized method ofclaim 11 wherein the categorization of viewers watching the listed TV advertisements includes one or both of viewers who watched the listed TV advertisements in the past and viewers who are projected to watch the listed TV advertisements in the future.

14. The computerized method ofclaim 11 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set categorized as watching the listed TV advertisements include at least demographic characteristics.

15. The computerized method ofclaim 11 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set categorized as watching the listed TV advertisements include at least characteristics related to cost of purchasing impressions on each MP.

16. The computerized method ofclaim 11 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set categorized as watching the listed TV advertisements include at least reach characteristics.

17. The computerized method ofclaim 11 wherein the model for the future campaign is optimized for at least one of cost and reach.

18. The computerized method ofclaim 11 further comprising generating a target list of MPs visited by the viewers in the fused data set categorized as watching the listed TV advertisements, and that are described in the historical database with respect to:

a demographic profile of each MP;

a historical cost of purchasing impressions on each MP; or

a historical reach of each MP.

19. The computerized method ofclaim 18 further comprising generating a combined target list for the future campaign by:

creating a combined list of TV demographic targets combined with the target list of MPs; and

sorting the combined list with respect to cost efficiency for on-target impressions.

20. The computerized method ofclaim 19 further comprising executing the future campaign by initially targeting advertising opportunities in the combined list that have a lowest cost for on-target impressions.

21. A computerized method for planning an advertising campaign targeting both TV and online impressions, whereby one or more processors perform the computerized method comprising:

receiving a fused data set of viewership data that includes TV viewing and digital media viewing of advertisements, and where for a plurality of viewers watching TV advertisements the fused data set includes digital media viewership data for those viewers;

receiving a list of TV advertisements for an advertiser/client;

analyzing the fused data set to:

for each of the listed TV advertisements, identify those viewers in the fused data set who are categorized as watching or not watching the respective listed TV advertisement;

identify viewer characteristics of the viewers categorized as watching or not watching the respective listed TV advertisement, and

produce a list of MPs visited by the viewers in the fused data set categorized as watching or not watching the respective listed TV advertisement, and identify specific characteristics of those MPs;

receiving targeting criteria from the advertiser/client for a future campaign; and

analyzing a historical database containing data from digital media advertising campaigns, and based on the received targeting criteria for the future campaign and the data from digital media advertising campaigns, producing a model for the future campaign that includes a proposed budget split between TV and digital media placement of advertisements.

22. The computerized method ofclaim 21 wherein the categorization of viewers watching or not watching the listed TV advertisements includes viewers who watched or did not watch the listed TV advertisements in the past.

23. The computerized method ofclaim 21 wherein the categorization of viewers watching the listed TV advertisements includes one or both of viewers who watched or did not watch the listed TV advertisements in the past and viewers who are projected to watch or not watch the listed TV advertisements in the future.

24. The computerized method ofclaim 21 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set include at least demographic characteristics.

25. The computerized method ofclaim 21 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set include at least characteristics related to cost of purchasing impressions on each MP.

26. The computerized method ofclaim 21 wherein the specific characteristics of the MPs in the list of MPs visited by the viewers in the fused data set include at least reach characteristics.

27. The computerized method ofclaim 21 wherein the model for the future campaign is optimized for at least one of cost and reach.

28. The computerized method ofclaim 21 further comprising generating a target list of MPs visited by the viewers in the fused data set categorized as watching or not watching the listed TV advertisements, and that are described in the historical database with respect to:

a demographic profile of each MP;

a historical cost of purchasing impressions on each MP; and

a historical reach of each MP.

29. The computerized method ofclaim 28 further comprising generating a combined target list for the future campaign by a computerized method further comprising:

creating a combined list of TV demographic targets combined with the target list of MPs; and

sorting the combined list with respect to cost efficiency for on-target impressions.

30. The computerized method ofclaim 29 further comprising executing the future campaign by initially targeting advertising opportunities in the combined list that have a lowest cost for on-target impressions.

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