Systems and Methods for Planning and Executing an Advertising Campaign Targeting TV Viewers and Digital Media Viewers Across Formats and Screen Types
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.
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 of claim 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 of claim 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 of claim 1 wherein the specific characteristics of the MPs in the list of MPs includes at least demographic characteristics.
5 . The computerized method of claim 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 of claim 1 wherein the specific characteristics of the MPs in the list of MPs includes at least reach characteristics.
7 . The computerized method of claim 1 wherein the model for the future campaign is optimized for at least one of cost or reach.
8 . The computerized method of claim 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 of claim 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 of claim 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 of claim 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 of claim 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 of claim 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 of claim 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 of claim 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 of claim 11 wherein the model for the future campaign is optimized for at least one of cost and reach.
18 . The computerized method of claim 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 of claim 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 of claim 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 of claim 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 of claim 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 of claim 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 of claim 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 of claim 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 of claim 21 wherein the model for the future campaign is optimized for at least one of cost and reach.
28 . The computerized method of claim 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 of claim 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 of claim 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.