MEDIA ACQUISITION WITH PROBABILISTIC MODELING
Data associated with one or more engagement events is generated for multiple users. The data associated with the one or more engagement events is aggregated for the users. Performance of one or more advertising campaigns is predicted based on the aggregated data.
1 . A method, comprising:
generating data associated with one or more engagement events for a plurality of users;
aggregating the data associated with the one or more engagement events for the plurality of users; and
predicting, by a computer processing device, performance of one or more advertising campaigns based on the aggregated data.
2 . The method of claim 1 , wherein predicting the performance of the one or more advertising campaigns comprises using a statistical inference to calculate a probability of distribution for a valuation of the engagement event of the one or more advertising campaigns.
3 . The method of claim 2 , wherein the statistical inference comprises a Bayesian inference.
4 . The method of claim 1 , further comprising:
generating a model of a relationship between the one or more engagement events for the one or more advertising campaigns, wherein predicting the performance of the one or more advertising campaigns is based on the generated model.
5 . The method of claim 1 , further comprising:
generating a bid value for an advertisement in the one or more advertising campaigns based on the predicted performance.
6 . The method of claim 5 , further comprising:
receiving user data and advertising network data associated with the advertisement in the one or more advertising campaigns; and
updating the bid value for the advertisement based on the user data and the advertising network data.
7 . The method of claim 1 , wherein the one or more engagement events comprises at least one of a paid event or a valued event.
8 . A system comprising:
a memory; and
a computer processing device, operatively coupled to the memory, to:
generate data associated with one or more engagement events for a plurality of users;
aggregate the data associated with the one or more engagement events for the plurality of users; and
predict performance of one or more advertising campaigns based on the aggregated data.
9 . The system of claim 8 , wherein to predict the performance of the one or more advertising campaigns, the computer processing device to use a statistical inference to calculate a probability of distribution for a valuation of the engagement event of the one or more advertising campaigns.
10 . The system of claim 9 , wherein the statistical inference comprises a Bayesian inference.
11 . The system of claim 8 , wherein the computer processing device is further to:
generate a model of a relationship between the one or more engagement events for the one or more advertising campaigns, wherein predicting the performance of the one or more advertising campaigns is based on the generated model.
12 . The system of claim 8 , wherein the computer processing device is further to:
generate a bid value for an advertisement in the one or more advertising campaigns based on the predicted performance.
13 . The system of claim 12 , wherein the computer processing device is further to:
receive user data and advertising network data associated with the advertisement in the one or more advertising campaigns; and
updating the bid value for the advertisement based on the user data and the advertising network data.
14 . The system of claim 8 , wherein the one or more engagement events comprises at least one of a paid event or a valued event.
15 . A non-transitory computer readable storage medium storing instructions, which when executed, cause a computer processing device to:
generate data associated with one or more engagement events for a plurality of users;
aggregate the data associated with the one or more engagement events for the plurality of users; and
predict, by the computer processing device, performance of one or more advertising campaigns based on the aggregated data.
16 . The non-transitory computer readable storage medium of claim 15 , wherein to predict the performance of the one or more advertising campaigns, the computer processing device to use a statistical inference to calculate a probability of distribution for a valuation of the engagement event of the one or more advertising campaigns.
17 . The non-transitory computer readable storage medium of claim 15 , wherein the computer processing device is further to:
generate a model of a relationship between the one or more engagement events for the one or more advertising campaigns, wherein predicting the performance of the one or more advertising campaigns is based on the generated model.
18 . The non-transitory computer readable storage medium of claim 15 , wherein the computer processing device is further to:
generate a bid value for an advertisement in the one or more advertising campaigns based on the predicted performance.
19 . The non-transitory computer readable storage medium of claim 18 , wherein the computer processing device is further to:
receive user data and advertising network data associated with the advertisement in the one or more advertising campaigns; and
updating the bid value for the advertisement based on the user data and the advertising network data.
20 . The non-transitory computer readable storage medium of claim 15 , wherein the one or more engagement events comprises at least one of a paid event or a valued event.