FORECASTING ELECTRONIC EVENTS
A system and methods are provided for forecasting the volume of future events that match specified attributes regarding type of event (e.g., serving of an advertisement impression, a page view, fraudulent activity), attributes of entities involved in the events (e.g., users, content items, system components), and/or other factors. A forecast query is received with one or more terms identifying target criteria of a campaign (e.g., an ad campaign, some other content-serving campaign). The query is decomposed into a first set of terms corresponding to attributes for which one or more predefined models exist, and a second set of terms for which no models exist. The predefined model for the first set of terms (or for a third term that is a superset of the first set of terms) is then used to estimate a number of future events that match the query terms.
1 . A computer-system-implemented method for performing volume forecasting, the method comprising:
receiving a forecast query containing a first term and a second term that specify targeting criteria associated with a campaign;
accessing one of:
a first predefined model that estimates a number of events that match the first term, if the first predefined model exists; and
a third predefined model that estimates a number of events that match a third term that encompasses the first term, if the first predefined model does not exist;
using the computer, calculating a ratio between (a) past events matching the first term and the second term and (b) past events that match:
the first term, if the first predefined model is accessed; or
the third term, if the third predefined model is accessed; and
estimating a future number of events for the campaign by multiplying the estimated number of events by the calculated ratio.
2 . The method of claim 1 , wherein the events include serving an impression of an advertisement.
3 . The method of claim 2 , wherein the events further include:
receiving a click on the impression; and
receiving a conversion of the impression.
4 . The method of claim 1 , further comprising.
accessing a fourth predefined model that estimates a number of events that include a fourth term that is a logical subset of the first term, if the first predetermined model and the third predefined model do not exist.
5 . The method of claim 1 , wherein estimating the future number of events in the campaign is further based on inclusion criteria in the user profiles of users in the number of individuals.
6 . The method of claim 1 , wherein estimating the future number of events in the campaign is further based on exclusion criteria in the user profiles of users in the number of individuals.
7 . The method of claim 1 , wherein the first predefined model and the third predefined model were included in a set of predefined models based on a frequency of the first term in queries preceding the query.
8 . The method of claim 1 , wherein the first predefined model and the third predefined model were included in a set of predefined models based on an accuracy of previous estimated numbers of events.
9 . The method of claim 1 , wherein the third term includes the first term in a hierarchy.
10 . A computer-program product for use in conjunction with a computer, the computer-program product comprising a non-transitory computer-readable storage medium and a computer-program mechanism embedded therein, to perform volume forecasting, the computer-program mechanism including:
instructions for receiving a forecast query containing a first term and a second term that specify targeting criteria associated with a campaign;
instructions for accessing one of:
a first predefined model that estimates a number of events that match the first term, if the first predefined model exists; and
a third predefined model that estimates a number of events that match a third term that encompasses the first term, if the first predefined model does not exist;
instructions for calculating a ratio between (a) past events matching the first term and the second term and (b) past content-delivery events that match:
the first term, if the first predefined model is accessed; or
the third term, if the third predefined model is accessed; and
instructions for estimating a future number of events for the campaign by multiplying the estimated number of events by the calculated ratio.
11 . The computer-program product of claim 10 , wherein the events include serving an impression of an advertisement.
12 . The computer-program product of claim 11 , wherein the events further include:
receiving a click on the impression; and
receiving a conversion of the impression.
13 . The computer-program product of claim 10 , further comprising:
accessing a fourth predefined model that estimates a number of events that include a fourth term that is a logical subset of the first term, if the first predetermined model and the third predefined model do not exist.
14 . The computer-program product of claim 10 , wherein estimating the future number of events in the campaign is further based on inclusion criteria in the user profiles of users in the number of individuals.
15 . The computer-program product of claim 10 , wherein estimating the future number of events in the campaign is further based on exclusion criteria in the user profiles of users in the number of individuals.
16 . The computer-program product of claim 10 , wherein the first predefined model and the third predefined model were included in a set of predefined models based on a frequency of the first term in queries preceding the query.
17 . The computer-program product of claim 10 , wherein the first predefined model and the third predefined model were included in a set of predefined models based on an accuracy of previous estimated numbers of events.
18 . The computer-program product of claim 10 , wherein the third term includes the first term in a hierarchy.
19 . A computer, comprising:
a processor;
memory; and
a program module, wherein the program module is stored in the memory and configurable to be executed by the processor to perform volume forecasting, the program module including:
instructions for receiving a forecast query containing a first term and a second term that specify targeting criteria associated with a campaign;
instructions for accessing one of:
a first predefined model that estimates a number of events that match the first term, if the first predefined model exists; and
a third predefined model that estimates a number of events that match a third term that encompasses the first term, if the first predefined model does not exist;
instructions for calculating a ratio between (a) past events matching the first term and the second term and (b) past events that match:
the first term, if the first predefined model is accessed; or
the third term, if the third predefined model is accessed; and
instructions for estimating a future number of events for the campaign by multiplying the estimated number of events by the calculated ratio.
20 . The computer system of claim 19 , wherein the events include serving an impression of an advertisement.